The utilisation of residual solid biomass for energy generation and intermediate compounds has sparked industry interest due to societal and governmental pressures regarding global climate issues. In Brazil, coconut husk, especially the endocarp, is an abundant residual biomass with significant potential for energy utilization. Among various thermochemical conversion routes for biomass, the technology of Supercritical Water Gasification (SCWG) stands out, converting biomass into synthesis gas with higher H2 concentration and low tar and coal content. This technology is relatively understudied in the literature. To enhance SCWG efficiency, an alternative is the impregnation of biomass with nanocatalysts. This thesis investigated the use of a nanostructured nickel-based catalyst impregnated into coconut endocarp for its gasification using supercritical water (T > 375°C and P > 22.1 MPa) as a reactive medium. The Box-Behnken experimental design, following the Response Surface Methodology (RSM), was chosen for the development of SCWG tests on coconut husk. The effects of the following variables on the efficiency and yield of the gasification process were evaluated: temperature (400, 450, and 500°C), residence time (20, 40, and 60 minutes), and feed concentration (20, 25, and 30%). Additionally, characteristics of gas, liquid, and solid products were also analysed. The impact of the presence and concentration of the catalyst on the efficiency and yield of supercritical water gasification of biomass was particularly assessed. From the characterization of biomass impregnated with nickel salt solutions at concentrations of 1 Molar (1M) and 2 Molar (2M), it was observed that nickel was present at 1.6 and 5.6 wt% , with particle sizes of 7.2 and 13.5 nm. Through the application of RSM, it was observed that temperature had the greatest effect on the composition of the gas product. The higher nickel concentration in the 2M sample resulted in higher H2 content (15.2 mol%), process efficiencies, and the transition of nickel ions to the form of nanoparticles (Ni(0)). Additionally, the chemical composition of the liquid product demonstrated the significant ability of nickel to promote lignin decomposition into phenol, facilitating the hydrogenation reaction of phenol and subsequent gas production. This thesis aimed to generate new knowledge in the promising field of the SCWG process by impregnating a nickel nanocatalyst into coconut biomass, aiming to increase the efficiency of its conversion into synthesis gas, with a focus on obtaining a higher concentration of renewable hydrogen.

The Origin of Life is one of the most fundamental questions of Humanity, widely discussed throughout History. Have already been treated in Myths, Arts and Philosophy, today it is intensely studied by modern science, in the interdisciplinary area of Origin of Life. The currently hypothesis claims that a gradual increase in complexity of small molecules from the primitive Earth occurred, and gave origin to larger and functional structures. Such macromolecules, or building blocks of life (such as Nucleotides and Amino Acids), interact with each other to form some type of precellular structure, or Protocell. Such Protocell, although not a living system, has some rudimentary metabolism and hereditary functions, working through chemical and thermodynamic means. The increase in complexity of such protocells would give rise to the first living cells. However, there are still many unanswered questions. For instance, how simple molecules, present on the primitive Earth, gave rise to the building blocks of life, such as Nucleotides, Lipids and Amino Acids? And how this building blocks polymerized into chains of Nucleotides (genetic polymers) or Amino acids (proteins)? Or how these genetic polymers, once formed, would self-replicate?Finally, how a Protocell arises, or how it originates a living cell, are just a few more questions in the current research. The present work presents a computational model for the study of one of these problems: the non-enzymatic polymerization of Nucleotides. Validation of the model was possible using independent experimental data on Nucleotide polymerization. With the simulated results predicting, with reasonable accuracy, the distribution function of the experimental data from polymerization of Nucleotides.

Distributed Energy Systems (DES), also known as microgrids, from renewable energy sources were conceived as a way to reduce the emission of polluting gases into the atmosphere and have become a major incentive for self-producers of energy. Although Brazil has a large availability of natural resources, which creates a strong potential for the application of microgrids based on renewable energy sources such as solar, wind, and biomass, it is still little explored in relation to other countries. This study aims to bridge the gaps in the current literature regarding microgrid design by addressing the impact of energy demands in the sizing of a microgrid and climate on renewable resource efficiency. The study pioneers the application of biogas to all residential energy demands in a microgrid and offers a new approach to analyzing the effects of varying input variables over time in an on-grid microgrid. Therefore the study proposes a decision-making framework for designing and operating residential DES in Brazil, based on mixed-integer nonlinear programming (MINLP) models that take into account the particularities of the country, such as the availability of various renewable resources and the impact of COVID-19 on energy demand. The models optimize the cost of designing and operating a microgrid with integrated pipelines and consider the varying efficiency of different technologies over time, as well as different options for renewable incentive policies. Additionally, it proposes a systematic, cluster-based method to split the time horizon of the model, allowing for a more accurate representation of the dynamics of the input variables of the optimization problem such as energy demand, wind speed, and solar irradiation over time. The framework is tested on a case study of a residential DES of 5 and 10 houses in Salvador, Brazil, comparing pre- and post-COVID-19 scenarios. The results show that the use of distributed energy resources has turned out to be economically and environmentally advantageous compared to using only non-renewable resources. The study also demonstrates the economic viability of using biogas and the new energy trends emerging during the pandemic, and how this impacts the sizing of microgrids. By not considering time-dependent efficiency in the analysis, there may have been a positive impact on the economic gain of around 90% in relation to the baseline scenario, but it may also have contributed to the underestimation of power generation. Also, although the empirical method showed a greater reduction in environmental costs (60%), the clustering method had a greater reduction (80%) in total costs. This highlights the relevance of the innovative approaches utilized in the optimization problem for designing a microgrid.

The power generation around the world is still based on large power plants located far from consumer centers. However, a new model of distributed generation (DG) is emerging in several countries, where the consumer produces his own energy (prosumer) close to the point of consumption, thus allowing greater autonomy and flexibility to users of the Brazilian electricity sector. Among the energy options for DG, solar photovoltaic (PV) stands out, this allows for a decentralized and CO2-free generation. Brazil is located in the intertropical zone, registering high levels of solar irradiation throughout the year, compared to countries that use this technology, which makes it a favorable place for its use. Solar PV distributed generation (PVDG) has gained notoriety in Brazil and has been expanding significantly since 2012, but it has also caused divergences of interests between consumers and energy distributors. In this context, this research aimed to understand the reality of DG in Brazil and to carry out a complete case study on the implementation of a PVDG system connected to the power grid. The methods adopted were: a large bibliographic study; contextualization and analysis of information from the Brazilian DG and the regulatory framework; preparation of previous studies, specifications and actions for the implementation of the PVDG project, ranging from its energy consumption and technical-economic feasibility analysis to its commissioning and monitoring of two first years of operation. The results obtained were: (i) the effective implantation and operation of the PVDG system (installation of the order of 20 kWp for microgeneration) in a nursing home in 2019, where the system was framed under the electric energy compensation regime (net metering), where its economic and financial viability presents: a simple 4-year payback, a 4-year discounted payback; an average monthly savings generated in the electricity bill over a year of R$ 2,074.80; (ii) The establishment of a set of recommended steps for the adequate and qualified realization of a complete project for the implementation of a PVDG system. The conclusions obtained were: (i) the current Brazilian environment is very favorable to the expansion of PVDG, which is evidenced by the growth of the DG market in recent years; (ii) there were divergences of interests between energy distributors and consumers; (iii) there were six scenarios proposed by ANEEL for DG, where in five of them, the benefits of prosumers will be reduced (iv) In 2022, Law No. 14300/2022 (regulatory framework) was approved, which definitively resolved the differences between consumers/prosumers and distributors; (v) the PVDG system is working satisfactorily as planned and its process.

This dissertation addresses the modeling and parameter estimation, including uncertainties and confidence regions, for the Propyl Propionate (ProPro) synthesis process. The study employs a rigorous model that considers the heterogeneous nature of the investigated system, involving a fixed-bed chromatographic reactor
with the solid catalyst AmberlystTM 46. The parameter estimation approach combines Particle Swarm Optimization (PSO) and a Gradient Method (GM) to estimate both thermodynamic and kinetic parameters in two distinct steps. Initially, the estimation of thermodynamic parameters occurred using literature equilibrium data. In the second step, for the estimation of kinetic parameters with the heterogeneous model, author’s experimental data were employed. Uncertainties of the experimental data were evaluated and calculated for use in the estimation of kinetic parameters. Through PSO, parameters were estimated and their confidence regions
determined, providing a comprehensive understanding of their uncertainties. The uncertainties of thermodynamic and kinetic parameters are evaluated and propagated to the activities in the thermodynamic model and to the Arrhenius constants and reaction rate of the heterogeneous kinetic model. The results demonstrate good agreement between the model predictions with the parameters estimated in this work and the experimental data, adequately reflecting the statistical variability of the experimental observations with an expanded uncertainty of 95%. Moreover, the heterogeneous Langmuir-Hinshelwood model presents an improved representation of the experimental data, both in transient and steady states, compared to the Pseudo Homogeneous model used in the literature. The Root Mean Square Deviation (RMSD) for parameter estimation shows a significant improvement compared to the values found using parameters available in the literature.

The cocoa region of Bahia for over 250 years has been improving in the Cocoa Cabruca
Agroecosystem (ACC), bringing with it a strong cultural expression and influence on regional
economic development. Considering the relevance of cabruca for the region and its importance
for the maintenance of forest remnants in the Atlantic forest, it is proposed as a general objective:
To present a process for valuing existing tree species in the ACC and compare with other methods
for valuation of tree species, aiming to contribute to the debate about the conservation of the
remnants of the Atlantic Forest. It aims to highlight the importance of establishing a fair land
pricing method for the construction of a basis for future new forms of rural credit. The study also
intends to discuss the contribution of cultivation methods for the conservation of remnants of the
Atlantic Forest, presenting the main tree species contained in the region, in addition to showing
the economic sustainability of the cabruca cocoa system, through productive conservation in
rural establishments, mainly from family farming. The methodology used was: bibliographic
research; survey of cocoa farming data in the cocoa micro-region of Bahia; survey of the main
tree species found in the cocoa cabruca agroecosystem; forest inventory methods; and methods
for the valuation of tree species in the cocoa cabruca agroecosystem identified and systematized.
In addition to the contribution in the environmental and social aspects, this study intends to
point to a perspective of greater interest in the maintenance of the cabruca areas, envisioning
the future use of tree heritage in a perspective to increase the economic ballast of small rural
establishments, opening the perspectives far beyond shading the cocoa tree. Of the 03 (three)
methods for calculating the Value of the Tree Species Value (VEA) analyzed, the Valuation of
Tree Species for General Use (VEAUG) can be considered one of the most suitable for the cocoa
region in southern Bahia. This observation is due to its conservationist nature and better adapted
to the objectives studied.

This work sought to identify opportunities to implement a Cleaner Production program in the solid bulk storage and loading area at the port terminal in Aratu, Bahia, which is approximately 50 km from the state capital, by evaluating P2 and P+L measures and their methodologies. The geographical location, terrain and climate of the state of Bahia are favorable to the generation of solar energy. Initially, an exploratory study was carried out with the aim of assessing the operational process and the possibilities for improvement in the area. It was found that the implementation of the Cleaner Production (P+L) program aims to reduce the consumption of natural resources, provide operational gains, economic benefits and greater competitiveness for the company, as well as improving its image in the market in relation to environmental management and quality in the port sector. The main results related to the change in technology are speed and productivity in the operation, guaranteeing the safety and integrity of the employees involved in the storage and loading of solid bulk cargoes. Added to the diagnosis carried out at the port is energy efficiency, associated with adapting processes, changing electrical equipment and applying new procedures. The potential for solar energy generation in the region has been identified, and the company is presenting a proposal for a distributed solar photovoltaic generation system (GDFV), with a payback of just over two years for the project. These, combined with good operating practices (BPO), aim to promote actions to minimize drinking water consumption at the port. The results indicate that the economic feasibility study of this project will enable savings of 12% in the use of drinking water, with an estimated return on investment of 4 years. Energy recovery was also indicated, with the installation of capacitor banks connected to the electrical system. This work reveals that the implementation of the Cleaner Production program at the Aratu port terminal in Bahia not only promotes more efficient environmental management, but also offers significant opportunities, including solar energy generation, potable water savings and energy recovery. These actions not only improve the company's competitiveness, but also strengthen its image in the market, while contributing to the preservation of the environment.

Pairs of enantiomers in pharmaceutical drugs are known to might have one enantiomer with the active principle, whereas the other might cause severe side effects. However, enantioresolution is not trivial. Simulated Moving Bed (SMB) chromatographies have been applied in the industrial and lab scales for separation of enantiomers. A representative phenomenological model is a key to a successful design, optimization, and control of the system, that relies on well-estimated parameters. This thesis aims to propose a novel methodology for a global and straightforward parameter estimation of the SMB model coupled with uncertainty analyses. Firstly, parameters are estimated via gradient-based and Particle Swarm Optimization (PSO) methods, whose operating conditions were generated by Latin Hypercube Sampling (LHS). Then, a new parameter estimation is carried out using experimental data from the literature, together with a PSO population-based uncertainty evaluation that enables model validation and definition of the parameter confidence regions. Secondly, this work proposes a method for screening the adsorption isotherm based on minimal system knowledge. This methodology determines a minimum number of experiments to be carried out in an SMB unit to provide a representative model, followed by a new parameter estimation and screened of the best adsorption isotherm equation. Finally, a single isotherm equation Linear + Bi-Langmuir is introduced as a combination of other known equations in the literature in order to carry out estimability analysis together with a comparison with screened isotherm. An estimability analysis based on orthogonalization could determine a subset of uncorrelated parameters which can be estimated, enabling the reduction of computational effort during parameter estimation. The results of this study show that it is possible to perform parameter estimation from SMB chromatography producing a more trustworthy model with minimal system knowledge for different adsorption isotherm equations that could make parameter estimation faster and then, enantiomer resolution simpler.

This thesis developed a methodology to assess the safety of systemic processes for industrial sociotechnical systems. The strong point was the interpretative character that starts from the study of the context through contemporary French ergonomics, relying on the FRAM (Functional Resonance Analysis Method). Through its line of interpretation and detailing and observation of activities, the main and support functions for the construction of instantiations were identified. The thesis thus used results from the application of two different methodological frameworks to identify the critical functions that affect process safety in a chemical industry: FRAM and Performance Shaping Factors (PSF), the latter involving operators’ active participation, were applied on the same sociotechnical process. Three phenotype responses were integrated, based on FRAM, namely timing, precision, and duration. A methodological framework based on human factors had selected the critical key PSF, used as an indicator, to identify the critical activities in the process, by operator’s perceptions. This study demonstrated that some result variability couplings can be different in some aspects in the automated and batch process. The integration of duration phenotypes with integration timing and precision, that can modify the results of variability in a batch process. One key aspect was related to human being management observation, that can adapt and mitigate risks. Particularly, operator competence and knowledge can eliminate function and task time by modifying the work sequence of the process. Comparison results demonstrated the compatibility of both FRAM and PSF analyses. The use of a questionnaire to obtain information on factors that affect human performance proved to be successful, increasing user participation in a sociotechnical system and identifying critical activities of the process. The development of future practical studies, utilizing FRAM in conjunction with other tools, can be served to strengthen new sociotechnical processes.

The use of lignocellulosic biomass for the production of second-generation ethanol, such as the green coconut husk, implies the development and improvement of the stages of conversion of sugars into ethanol using a fermentative pathway. Thus, the execution of the pre-treatment step becomes necessary, responsible for breaking the lignocellulosic matrix, leaving it accessible to enzymatic attack in the subsequent step, the hydrolysis. With the available sugar monomers, the yeast converts them to ethanol in the fermentation step. Thus, this work aims to study the saccharification and fermentation configurations, using coconut cultivation residues as carbon sources, with the objective of evaluating the best saccharification and fermentation conditions for E2G production. Initially, the hydrothermal pretreatment (HPT) was carried out in a PARR type reactor using 15% (m/v) of solids, at 195°C, 10 min and 200 rpm. In parallel, an experimental design was carried out for the acid pretreatment (APT) (factors: H2SO4 concentration and temperature) aiming at the optimization of the pretreatment operational conditions. The function of glucose, conditions of 1% (v/v) H2SO4 at 100 °C for green coconut shell (GCS), 2% (v/v) H2SO4 at 120 °C for coconut-tree leaflet (CLL) and 2% (v/v) H2SO4 at 100 °C for the coconut-tree leaf stalk (CLS) followed for enzymatic hydrolysis, using 7.5 % (m/v) of solids and 20 FPU/g dry biomass of Cellic Ctec2 supplemented with 10% Cellic Htec. After 72h of reaction, glucose concentrations reached 31.85 and 19.07 g/L for the hydrolysis of GCS submitted to PTH and PTA. Regarding the behavior of CLL in hydrolysis, 21.31 and 13.65 g/L of glucose concentration were reached when this biomass was submitted to HPT and APT. For CLS, 45.39 and 21.01 g/L of glucose were obtained after HPT and APT, respectively. These results showed that enzymatic hydrolysis using hydrothermal pretreatment was more efficient than the results obtained for pretreated acidic biomasses. Then, the samples went on to fermentation with the yeast Kluyverkomyces marxianus at 37°C/24 h. In this step, it is possible to verify that practically all the glucose and xylose contents were consumed by the yeast. However, the ethanol yield reached values between 47 and 80%, indicating possible problems of a toxic nature, the production of secondary compounds, acetic acid, furfural and 5-hydroxymethylfurfural (HMF). A preliminary study was carried out to increase the fermentation efficiency in sugarcane bagasse hydrolyzate, known biomass, and submitted to hydrothermal (195 ºC, using 200 rpm for 10 min) and acid (0.5% (v/v) pretreatments.) of sulfuric acid at 121ºC for 15 min) and (10% w/v solids load). The enzymatic hydrolysis of the pre-treated material was performed using the CellicCtec® enzyme complex (60 FPU/dry biomass, 50 mM citrate buffer and pH 4.8) at 50ºC using 150 rpm for 72h. Before the detoxification process, a test was carried out with the species of Saccharomyces cerevisiae to verify if the compounds furfural (1 and 4g.L-1) and acetic acid (1 and 5% v/v) exerted significant inhibition in the tested species. The detoxification process evaluated the concentration of activated carbon (1, 3 and 5% w/v) and the process time (30, 45 and 60 min) at 30 ºC, 150 rpm for 24 h. The presence of furfural and acetic acid had a strong influence on the species considered, affecting more than 90% of the consumption of sugars in the medium. The detoxification process increased the fermentation efficiency by 13% for the hydrolysateobtained hydrothermally, while for the acid there was no significant difference. Thus, it was possible to conclude that the study of process conditions increased ethanol production compared to values already reported in previous studies with green coconut husk. And it identified the potential of the coconut leaf for the production of second-generation ethanol. It also verified that the detoxification conditions can be adapted to the biomass of coconut cultivation to increase efficiency and make the results feasible for industrial production.

Modular biorefineries are promising industries for diversifying developing countries’ economies and reducing external dependence on productive inputs. This research aimed to evaluate the techno-economic, environmental, and social viability of modular biorefineries for the production of inputs with high added value for the pharmaceutical, cosmetic, or food industry in Guinea-Bissau, from the processing of Fresh Fruit Bunches of palm oil (FFB) and peeled castor bean seeds. The methodology employed to achieve the proposed objective relies on a multi-criteria multidimensional optimization model built to assess the sustainability of proposed biorefineries and support decision-making. The FFB products evaluated were crude oil, refined oil, palm kernel oil, and stearin; while those from castor oil were crude oil, refined oil, and stearin. In order to serve regional markets with these products, the installation of seven modular biorefineries in Guinea-Bissau was proposed. Data were obtained from secondary sources and compiled in the Python® programming language. Data uncertainty was evaluated from the Pedigree Matrix and its variability through Monte Carlo Simulations. Availability of 3.66  105 t year−1 of FFB and 1.8  104 t year−1 of castor bean seeds was estimated. The solution of the multidimensional model indicated the optimal quantity of each product to be produced in order to reach a gross profit of 5.03  108 US$ year-1 in the optimized scenario. GHG emissions from the processing of raw materials in the base scenario were 1.75  108 kg CO2eq year-1, while in the optimized scenario it was 2.40  108 kg CO2eq year-1. This difference, however, is within the uncertainty range of environmental assessment information. The generation of jobs in the base scenario is 1.24  105 jobs per year; in the optimized scenario, it is 1.80  105 jobs per year. There is a trade-off between maximizing profit and minimizing GHG emissions. By maximizing profit, GHG emissions increase by 148 %, and by minimizing GHG emissions, gross profit decreases by 82 %. Finally, different carbon credit compensation scenarios were simulated with excess GHG emissions by maximizing gross profit at a cost of 0.03 US$/(kg-1 CO2), 0.10 US$/(kg-1 CO2) and total compensation of all GHG emissions generated, which indicated an impact of 0.86 %, 2.86 % and 4.77 % of gross profit, respectively. The economic-financial feasibility analysis made it possible to verify that the project is viable since the Net Present Value is 7.79  107 US$, the Minimum annual Attractiveness Rate of 14 %, the Internal Rate of Return is equal to 34 %, and the deadline for return on the initial investment (Simple Payback and Discounted Payback), is 2.90 years and 3.95 years, respectively.
Keywords: Modular

Providing maximum performance at minimum cost is a major challenge in the design of mechanical systems. One of the key problems is determining the optimal schedule of a set of units operating in parallel that minimizes the overall energy consumption. This is a widely studied problem in the literature known as \economic dispatch" (in power systems) or as \optimal loading problem" (in air-conditioning systems). However, the loading problem requires the units to be previously selected. This work proposes a procedure to solve the selection problem and the loading problem at the same time. The proposal is a novel procedure that allows determining, in a rigorous manner, the units that have to be purchased and the corresponding operation schedule. It was applied to two case studies: i) selection of chillers in cooling plants, and ii) selection of utility plants in oil and gas o_shore platforms. Both cases are analyzed using two alternative optimization approaches. First, a mono-objective optimization of a single cost-based function and, second, a multi-objective optimization of capital cost and energy consumption. The results in all cases showed that the total nominal capacity of the selected units is not necessarily closed to the peak load, which is a common rule-of-thumb guideline for equipment selection. For instance, the total nominal capacity of the solution with three 500 TR chillers in the cooling plant case is considerable greater the peak load (900 TR). Likewise, the solutions obtained in the selection of utility plants in FPSO platforms are better than the standard solution of three aeroderivative gas turbines model GE LM2500+RD (G4) (with a capital cost of 40.05 Millions of USD and a fuel consumption of 9:999 _ 104 TJ at the optimal setting during the lifetime of the system). These counter-intuitive results demonstrate the importance of using a systematic selection procedure.

Abstract of Thesis presented to PEI/UFBA as a partial fulfillment of the requirements for the degree of Doctor of Science (D.Sc.) The use of electrical submersible pumps (ESP) for oil lifting is a widely used method in the oil and gas industry to increase production. Therefore, controlling and optimizing this process to ensure stable and economical production is crucial, minimizing operational costs and maximizing production efficiency. A widely used technique to maximize performance, reduce costs, and define operational goals is real-time optimization (RTO). In order to adequately implement this techinique, it is necessary that the control layer works appropriately and is aligned with the challenges and requirements of the process. Recently, the literature has found excellent results using the advanced model predictive control (MPC) technique due to its ease of incorporating constraints and economic requirements into its formulation. Although it is a powerful technique, a reasonable definition of MPC parameters is necessary for its good operation; otherwise, the system may operate at suboptimal or inefficient conditions. However, tuning the MPC controller is a complex problem requiring specialized knowledge to select controller parameters, such as prediction horizons, control horizons, and control weights. In addition, most of the literature tuning methods are dedicated to specific MPC formulations, performance, or robustness goals, not exploring the impact of tuning on economic indicators. So, it is a need for a generalized tuning method that works for different formulations, processes, and tuning requirements. Besides that, no studies in the literature investigate the effect of MPC tuning on the optimization and operation of ESP-lifted wells, whether by performance, robustness, or economic criteria. Therefore, a generalized MPC tuning method is presented, based on an online receding horizon optimization algorithm capable of encompassing different MPC formulations, constraints, and tuning criteria, from performance to economics. This method provides a new perspective for the online optimization of ESP-lifted oil wells, explicitly addressing the MPC tuning problem. The results show that the proposed approach has potential for the oil and gas industry since it was possible to test different case studies and control formulations in simulated results, achieving a 5.7% improvement in oil production or a 2.1% reduction in energy consumption, depending on the desired criteria.

Monazite is one of the primary light rare earth minerals and is always associated with the presence of thorium. This poses challenges in processing due to the strong radiation present in this mineral. This study addresses the separation of thorium from light rare earth elements in hydrochloric acid medium from desphosphorized monazite. The steps used to obtain an aqueoussolution involved: addition of NaOH to the concentrate, heating at a temperature of 400°C for 3 hours, washing with water, and subsequent leaching of the residue with HCl. Samples from the aqueous phase were analyzed by ICP-OES. To assess the feasibility of alkaline fusion, thermodynamic modeling with different reagents was performed, and thermodynamic calculations of probable reactions were conducted using the HSC Chemistry 6.0 software database. NaOH appears as the most effective reagent from a thermodynamic and energetic standpoint. The separation of thorium from light rare earth elements was carried out through solvent extraction using compounds such as Cyanex 572, 272, 923, 921, and mixtures. Theoretical modeling was conducted using the Spana software to compare conditions in nitric and hydrochloric media. It was observed that Cyanex 572 and its mixtures extract 98% of the thorium in a single stage, while Cyanex 272 extracts 70% of the thorium and 40% of the LREEs. The results show that thorium can be separated from light rare earth elements in hydrochloric medium, both by Cyanex 272 and Cyanex 572, requiring an additional extraction stage when using Cyanex 272. The other extractants did not yield satisfactory results in the separation. The results indicate that extraction capacity can be improved by using long-chain diluents, an acidic pH below 2, and a concentration of 5% for Cyanex 572 and 10% for Cyanex 272.

Inspired by the mathematicalworks developed in Nonadditive Statistical Mechanics, with their
functions, algebra and trigonometry, extensively applied to complex systems, are realized two
proposals in this thesis which imply in consequences in the context of the non- linear dynamic
system and in the thermodynamic of electrolytes, that orbit surround the anaerobic digestion
in reactors. The first contribution talks about the proposition of an algorithm extremum seeking
modified by a function from 𝑞-trigonometry of Borges with consequence in the increase
of the speed in the search of the extreme and the minimum of the external disturbances. This
result is analytically demonstrated by the presentation of the asymptotic stability according
to Lyapunov. The second proposal, is in the context of the long-range interaction context
typically presented by the behavior in electrolyte solutions and modelled by the potential of
Debye-Hückel, which this potential is generalized by the 𝑞-exponential function, which allows,
in a simple way, to represent the superficial tension properties and mean ionic activity
coefficient, important to many applications in chemical, biological and environmental systems.
In the investigation of thermodynamic hypothesis simplifying adopted in the ADM1 to
the balance of the biomethane, it is verified that they are enough to represent the system of
the study case, different from the behavior of the carbon dioxide, which is dependable from
the chemical and electrolyte equilibrium reactions. In addition to that, it is confirmed the increase
of velocity, the breadth of the domain and the reduce of the residual disturbance of the
application of the generalized extremum seeking algorithm. Lastly, it is demonstrated how
the potential of generalized Debye- Hückel is capable of estimate properties such as the superficial
tension and the average of mean ionic activity coefficient to the wide ranges of ionic
concentrations.

The study presented an online technological solution developed to integrate and systematize public data, aiming to enhance the management of Research, Technological Development, and Services in Professional, Scientific, and Technological Education Institutions in Brazil. This system, registered with the National Institute of Industrial
Property (INPI) under the number BR5120230010197, was grounded on theories of innovation, business analysis, and data visualization, employing a quantitative approach to incorporate Business Intelligence techniques such as data warehouses and interactive dashboards. For the case study, data from the Federal Network of Professional, Scientific, and Technological Education was examined, and the proposed solution aimed to overcome the challenges of efficient data management, meeting institutional, productive, and governmental demands (including those from control bodies), which are increasingly vital for ensuring agile and accurate data management to integrate and optimize this process. The methodology employed a quantitative and empirical-deductive approach that included a literature review, user consultation, data source identification, and system
validation by nine experts. The findings indicated that the tool was essential for consolidating information from multiple sources, assisting public and institutional managers in rapidly and reliably responding to the demands of control bodies. The proposed solution also featured a user-friendly design with significant market potential,
adaptable to various institutions within the Brazilian National Innovation System. Furthermore, the system implementation allowed for the observation of specific characteristics of the Federal Network, such as the diversity of disciplines and geographical concentration of research, as well as the need to strengthen collaboration between researchers and the private sector. After a decade, institutions in the Northeast
and North regions began to stand out. The conclusions emphasized the necessity for practical technological solutions for the involved sectors and the importance of ongoing research, suggesting further theoretical deepening and methodological expansion, such as the adoption of data lakes or lakehouses. The study's limitations included difficulties in accessing public data in Brazil and the need for continual system updates to maintain data quality and accessibility.

The landfills generate liquid and gas subproducts that require treatment before being disposed. The liquid generate are the leachate, and this liquid is characterized by the dark color and high concentration of organic matter. Despite these characteristics it’s possible to use the leachate as resource in other process, as the nitrogen recovery. This study is about an investigation about the growth of microalgae using the leachate treated by photo-Fenton process. The leachate was collected at Aterro Metropolitano Centro (AMC), at Salvador Bahia, and treated by photo-Fenton process to reduce the organic matter concentration. To optimize the treatment, the design of experiments was used. The COD and true color on the optimize treatment achieve the reduction of 75,5% and 95,3%, respectively. This treated effluent was used for microalgae cultivation. After a brief adaptation stage of the species Euglena gracilis and Chlorella vulgaris the experiment continued with the monitoring growth for 21 days, using the counting for analyze the growth. After this cultivation a new one was started but some conditions were adapted as the light intensity. Using this last experiment was possible to concluded that Euglena gracilis have growth potential in treated leachate and Chlorella vulgaris had the best growth using the treated leachate with high light intensity and aeration.

Liquid air energy storage system (LAES) is one of the most promising large-scale energy tech-nologies presenting several advantages: high volumetric energy density, low storage losses, and an absence of geographical constraints. The disadvantages of LAES systems lay on the high investment cost and low round-trip efficiency. This work proposes a new configuration using an air Rankine cycle (ARC) to reduce the exergy destruction during heat-exchanging in the liquefaction process while reducing liquefaction power consumption, thus enhancing the round-trip efficiency. In addition, this work assesses two different LAES configuration, with and with-out energy integration, comparing them with the new configuration proposed. The round-trip efficiency of the LAES with the addition of the ARC reached 57.1%, whilst the liquid air yield achieved is 90.7%. The results from the new configuration proposed reveal that the increase in the yield of liquid air is more important to the overall efficiency than the power that is generated by the Rankine itself. The results from exergy analysis show that the overall exergy destruction of the new configuration compared to the simple LAES plant and LAES with energy integration is decreased by 44.8% and 2%, respectively. Furthermore, the effects of compression, storage, and pumping pressure on the new configuration performance are investigated by parametric analysis. From an economic viewpoint, the proposed system has a better economic performance than the LAES system with energy integration, decreasing the levelized cost of storage (LCOS) by almost 2%. The proposed configuration may improve the performance and economic com-petitiveness of LAES systems.

This work proposes filling gaps in three areas of PSE applied to the cyclic process, specifi-
cally, the Simulated Moving Bed Reactor: Dynamic sensitivity analysis, model acceleration
with deep neural networks surrogates, robust optimization and fault diagnosis.
To start, this work proposes two Simulated Moving Bed Reactor (SMBR) units for the synthesis
of n-Propyl propionate (ProPro): the Simulated Moving Bed Reactor with 4 columns
(SMBR-4) and the SMBR-8. Their simulated performance was compared to the True Moving
Bed Reactor (TMBR). This work provides two detailed analyses to assess the system
dynamic behavior of the three units: an orthogonalization based analysis and the process
reaction curve. The first showed that the switching time and feed concentration in uence
the system the most, though at dierent extensions for each unit. The second highlighted
that the SMBR/TMBR commonly used equivalence is not valid during transient conditions.
When it concerns neural surrogates, it is known that Recurrent Neural Networks (RNNs)
are suitable predictors for Nonlinear Output Error (NOE)-type model family. NOE is one
of the most important representations in chemical engineering when long-term predictions
(simulation) are required. Even so, the chemical engineering literature presents notorious
gaps in this topic. Therefore, this work proposes a novel and complete framework for
identifying Deep Recurrent Neural Networks (DRNNs) for NOE representation with focus
on chemical engineering systems. The framework incorporates a novel training method
and the employment of a state-of-the-art automatic hyperparameter selection algorithm.
The results show that by using the proposed framework, DRNNs can model the SMBR
process with satisfactory accuracy, relying exclusively on input signals and past predictions
(free-simulation).
When dealing with model-based optimization of Simulated Moving Bed Reactor (SMBR),
ecient solvers and significant computational power are required. Over the past years,
surrogate models have been considered for such computationally-demanding optimization
problems. In this sense, Artificial Neural Networks have found applications for modeling the
SMB unit, but not yet been reported for the reactive SMB. However, a consistent method
for optimality assessment using surrogate models is still an open issue in the literature. As
such, two main contributions can be highlighted: the SMBR optimization based on Deep
Recurrent Neural Network (DRNN) and the characterization of the Feasible Operation
Region. This is done by recycling the data points from a meta-heuristic technique {
optimality assessment. The results demonstrate that the DRNN-based optimization can
address such complex optimization, while meeting optimality.
Finally, it is well known that Big Data plays a crucial role in Industry 4.0 by oering
tools to improve the decision-making process. Among the industrial sectors, the chemical
process industry already holds mature data management structures, but poorly explored
analytical tools. In this sense, this work proposes an online analytical tool which can deal
with big data to be used for identifying abnormal operation in chemical processes. It deals
with a modified Dynamic Sensitivity Matrix (DSM) and Gram-Schmidt Orthogonalization
(GSO) to prioritize process variables under abnormal behavior and scaling the impact they
have on plant performance.

Currently, microalgae have been widely studied as a source of biomass to produce biofuels due to their high productivity, high lipid content and ability to grow in a wide variety of climates and spaces without competing with food production. The objective of this work is the production of green hydrocarbons similar to the constituents of conventional diesel, from the rapid thermal pyrolysis of the lipid fraction of microalgae of the Halamphora coffeaeformis (Hc), Chlorella vulgaris (Cv) and Nannochloropsis oculata (No) genera. For the latter, the feasibility of its use when subjected to rapid catalytic pyrolysis was studied. This practice emphasizes the important role of catalysis in fast pyrolysis. The catalysts used showed synergy to thermal cracking, amplifying the products of interest. Studies were also carried out using a model molecule, myristic acid, representing the fatty acids that can be found in microalgae. It was verified that the products generated in the micropyrolysis of this molecule in the presence of niobia catalysts (Nb350, Nb700, NbB700,) at two temperature levels, 500 and 600°C, showed formation of ketones and hydrocarbons by fatty acid deoxygenation. Furthermore, experiments using C14 with alumina catalysts ( γ-Al2O3) and niobium supported on alumina (Al700 and AlNb700) were used only at a temperature of 600ºC. The experiments were carried out in a Multi-shot Pyrolyzer Model EGA/PY-3030D micropyrolyser, from Frontier Laboratories LTD, connected online with a gas chromatograph coupled to an Agilent GC-MS 5799A mass spectrometer. All micropyrolysis were performed by the “Single-Shot” (SS) thermal method. Niobium-based catalysts were prepared from hydrated niobium oxide by calcination at 350 and 700°C, the latter sample being modified with boric acid (Nb350, Nb700 and NbB700). From the purely thermal pyrolysis of the lipid fraction of the microlags, conducted at a temperature of 600°C, the best response was verified and then tests with the catalysts (Nb350, Nb700 and NbB700) could be carried out. The products of myristic acid micropyrolysis were identified through the NIST Database, assuming a probability of agreement of parameters equal to or greater than 80%. For the pyrolysis of the lipid fraction of microalgae, 70% agreement was admitted. The main results obtained with the model molecule showed that Nb350 is as efficient as Al700 in pyrolysis at 600°C, producing ketones that can be considered intermediate in the production of olefin and alkane hydrocarbons, and with a larger carbon chain. than the starting acid. In the pyrolysis of the lipid fraction of No, the catalysts Nb350, Nb700 and NbB700 had an important performance, increasing from 18% to 35% the production of hydrocarbons compatible with diesel fuel.

The Internet and the multitude of new approaches arising from Digital Information and Communication Technology (TDIC) have entered the industrial world, bringing disruptive potential. The impact of the Industry goes beyond the processes associated with production and distribution, going through a more complex form of innovation based on the combination of multiple technologies, impelling companies to rethink the way they manage their businesses and processes. Professionals in this context of the current Industrial revolution - Industry 4.0 (I4.0), need technical knowledge to deal with emerging trends, such as Big Data, Internet of Things, robotics, among others, but they also need behavioral and emotional skills. Considering this scenario, it is important to stress that the current pedagogical processes should be re-examined and improved so as to gradually accommodate these emerging changes when teaching students. Given the case study supported by qualitative research, the goal of this study was centered around the problem: What is necessary for the implementation and evaluation of structural changes in the learning methods to develop student autonomy, via specific skills in the context of Industry 4.0 in public institutions? From this instigation, the methodological process made use of information gathered from the faculty and students of the courses in the area of technology and engineering from two institutions of higher education (IES) in the States of Alagoas and Bahia. The research instrument was the questionnaire that counted with the contribution of one hundred and thirty-seven (137) subjects, 31 professors and 106 students. From the analysis of the data, students believe they have autonomy and say they are prepared for I4.0, however, teachers disagree with these opinions. There were many differences in the opinions of the groups in relation to autonomy and competences, requiring the use of indicators from the National Student Performance Exam for the years 2014 and 2017 to compare them, even so, some differences persisted, described in the thesis. Professors see students as very passive, however, they believe that the use of TDIC and active methodologies can collaborate to develop this autonomy, bringing greater dynamic, as well as a change in the student's posture so that they can become more active, autonomous and participatory. There were also two situations that need to be addressed in the learning process: the need to develop socio-emotional competences in the student's academic life, essential for the professional who will work at I4.0, and the realization of alliances between universities and the industry.

Low salinity water injection (LSWI) is a current, cost-effective, and environmentally friendly method to enhance oil recovery by changing the salinity and/or composition of the injected water. However, the synergistic effect of chemical composition, concentration, and the pH of the injected brine in oil recovery during LSWI remains not well understood. This fact is due to the complexity of the interactions among the crude oil, the formation and injected brine solutions, and the rock surface, for both sandstone and carbonate reservoirs, particularly when they contain a diversity of clay minerals. In addition, there is a lack of low salinity studies in Brazilian sandstone rocks and light paraffinic crude oils to date. This research investigates the oil recovery performance and mechanisms in high and low salinity brine solutions using samples from a siliciclastic reservoir in Recôncavo basin, northeastern Brazil. Zeta potential measurements, oil adsorption analysis in silica, core flooding experiments, and interfacial tension and contact angle measurements are among the main experiments performed in this study. Furthermore, a commercial numerical simulator was used to create a representative model of the coreflooding. The experimental results showed a simultaneous increase in oil recovery and pH of the effluent in the coreflooding during IABS. Zeta potential measurements confirmed a thicker water film was formed on the rock and oil surface with brine dilution. The experimental observations also indicate that when the reservoir pH changes towards the alkaline conditions driven by ionic exchanges during LSWI, it may approximate the isoelectric point (IEP) of pH-dependent surface charges in oil and rock minerals, weakening the electrostatic attraction between their surfaces, and consequently contributing to release of oil in the porous media and increase in oil recovery. Optimization and sensitivity analysis showed that the concentration of Na+ and Ca++, and the water injection rate were the most important parameters in LSWI. Finally, interfacial tension and contact angle measurements in systems containing samples that mimic Recôncavo basin rock, high and low salinity brine solutions, crude oil, and CO2 indicate that low salinity brine favors CO2 solubility, may lead the increase in oil recovery in hybrid applications of LSWI-CO2. The findings of this research contribute substantially to the understanding of oil recovery mechanisms during LSWI. This study also provides useful data for oil
companies that have acquired mature fields and exploration blocks in the Recôncavo basin, supporting them in operational and investment decisions.

In view of the growth of fruit production in the São Francisco Valley (Brazil), the evaluation of technical efficiency represents a potential for improving the allocation of productive resources. This work presents a multi-objective model (Improved Weighted Goal Programming model - Multiple Criteria Data Envelopment Analysis, IWGP - MCDEA), based on Goal Programming (GP) and associated with the infinitesimal non-Archimedean (NAI,ε) which aims to overcome the deficiencies of the classic Data Envelopment Analysis (DEA) (low level of discrimination between the DMUs and the distribution of unrealistic weights), being able to be applied in real situations such as in irrigated fruit growing (IWGP - MCDEA - variable return of BCC scale). The case study comprised an agricultural export company located in São Francisco Valley (Northeast region of Brazil). The performance of the proposed multiobjective model (Improved Weighted Goal Programming model - Multiple Criteria Data Envelopment Analysis, IWGP - MCDEA) was compared to the classic Data Envelopment Analysis (DEA) model based on the Variable Return to Scale (BCC) and the weighted sum goal programming (WGP - MCDEA) model. The analysis of the results involved the use of statistical metrics (p-value, Spearman’s Correlation Test and coefficient of variation) which showed the best performance in discrimination Decision Making Units (DMU’s) through the inclusion of NAI. The sensitivity analysis associated with the stability of the weights of each input/output was performed through the coefficient of variation. The proposed model is capable of overcoming the deficiencies associated with classical DEA and provides the possibility of improving the company's competitiveness by increasing productivity from the reduction of input costs. An additional step comprised the application of a classical technique of non-hierarchical clustering (Fuzzy C-Means, FCM) aiming at the recognition of clusters and patterns of DMUs from their respective inputs and outputs. The results obtained by this unsupervised learning technique demonstrated consistency in relation to the recognition/identification of efficient DMUs obtained by the proposed method (IWGP-MCDEA).

Ionic liquids are non-volatile organic salts that, under standardized conditions, remain in a liquid state and are composed of organic cations and organic or inorganic anions. They have a wide industrial application and sustainable profile and, generally, they are called as "green solvents", however, despite this denomination, there is insufficient information about their aspects related to their toxicity to the environment and to humans. In this context, this work aimed to evaluate the toxicological aspects of some ionic liquids through in vitro bioassays, inaddition to trying to understand their effects on cells, seeking possible biological applications. For this purpose, seventeen protic ionic liquids were synthesized and analyzed by in vitro assays of: cytotoxicity in metabolizing cells (HepG2) and skin cells (HaCat and HDFa); morphological observation of HaCat cells exposed to these liquids; and eye irritation in chicken egg's chorioallantoic membrane (HET-CAM). In order to study a possible biological application, the wound healing potential in HDFa cells was also evaluated. The results obtained were promising, since, in general, the ionic liquids showed a low cytotoxic effect, obtaining IC50 values between 8 and 390 mM, approximately. In addition, it was possible to observe its effect on cells, causing an increase or decrease in volume and/or rupture of cell membrane in HaCat cells, due to osmotic pressure. The eye irritation test showed that the ionic liquids composed of citric acid did not cause eye irritation, while thirteen of them were characterized as mild or moderate irritants, and it is possible to suggest, based on this test, their safe use in living organisms, although there are reservations. It was also confirmed, from a quantitative analysis by the ImageJ software, the classification of eye irritation by the analysis of grayscale images. In addition, no sample tested was able to prevent the healing process evaluated in vitro, which is another indication of safety and, still, the ionic liquid based on oxalic acid stands out for being able to improve cell migration. Therefore, it was possible to conclude that the protic ionic liquids evaluated in this work are, in general, safe, less toxic to human cells than conventionally used solvents and the collected results contribute significantly to science, as they indicate safety parameters of these compounds, related to their chemical characteristics and concentrations and reinforce the need to continue these studies. Also, in this work, a new direction of research is suggested using protic ionic liquids, seeking biological effects for them.

With the worldwide increase in energy demand, natural gas has emerged among other fossil fuels. Once it has a lower environmental impact and a better energetic efficiency, pipeline networks can distribute it. Thus, many authors have developed techniques to predict network gas behavior to increase process performance and competitiveness. Despite that, the usage of more complex centrifugal compressors for network modeling is lacking in the literature. Such equipment plays a pivotal role in network optimization and control applications once they provide degrees of freedom and limits the compressor map process. Of such limits, the most significant one is the surge line, which coincides with the maximum isentropic efficiency and limits the process to stable conditions. From these assumptions, this work contributes by describing the compressor map using a phenomenological model able to predict the gas properties with an equation of state. Thus, the pivotal contributions in this thesis can be summarized as follows: (i) to evaluate the influence of the phenomenological compressor map approach in natural gas network transient simulation and compression systems control, (ii) to analyse the influence on the equation of states in simulations, as well, in the transient states of compressor map, and (iii) to propose surge avoidance control strategies for the compression systems in both lumped parameters and distributed parameters models. The open-loop simulations showed a significant impact of the modeling hypotheses (compression system model and equations of state) on the mass flow and the discharge pressure of the network. In addition, a significant impact of these hypotheses on the surge avoidance constraints was observed, which later proved to be relevant for the efficiency of the process in closed-loop simulations. In addition, an IHMPC with the extended model strategy was proposed with feasibility assurance via slack variables to control compression systems. This strategy proved to be promising compared to a conventional NMPC by having a similar response to it but a significantly lower computational time. In addition, the proposed control law is efficient in simulations of the control of systems while keeping the process in safe conditions in both modelings: lumped and distributed parameters, thus presenting itself as a good option for in loco implementation.

The Pb-Zn mining and Pb metallurgy activities that took place in the interior of Bahia State for more than three decades left soils contaminated with heavy metals that can pose risks to human health and the environment in the region around these former industries. The main objective of this study is to analyze the risk to the environment and human health in industrial areas contaminated by heavy metals in the State of Bahia. Data from three concentration studies were used in this assessment, and a geostatistical analysis identified high levels of potentially toxic elements (i.e., Pb, Cd, and Zn) at these sites, exceeding the regulatory limits for industrial soil, which corroborate the results of the pollution and ecological risk analyses. The results show that the risk of disease from Pb soil contamination is very high for children and moderately high for adults living around the old smelter in Santo Amaro, Bahia. The mining plant produced about 4.5 tons of tailings that were disposed of in a dam. The heavy metal risk analysis of the tailings showed that Pb, Cd and Zn contributed to a high pollution index and Pb and Cd to a potential development of non-carcinogenic diseases. A risk analysis for human health and the environment was also performed around an artisanal ceramic production in the interior of Bahia State. The ecological and health risk indicators showed high values of soil contamination by Pb near the potteries, and the environmental and human health risk in these industrial and artisanal production areas showed that more than 17000 people are exposed to the risk of lead contaminated soil in the state of Bahia.

Vanadium is a chemical element and in vanadium compounds occur naturally in about 65 minerals and in fossil fuel deposits. It is mainly used to produce steel alloys in the metallurgical industry and as catalysts in chemical reactions. It is usually marketed as vanadium pentoxide, which in turn is one of the main raw materials in the production of vanadium electrolytes used in vanadium redox battery systems for energy storage. Among the chemical compounds of vanadium sold, vanadium pentoxide has the lowest cost price, thus becoming the favourite in the manufacturing of vanadium electrolytes. The purpose of this paper is to assess the use of vanadium pentoxide produced at the Vanádio de Maracás S/A (VMSA) plant as a raw material in the manufacture of vanadium electrolytes. Atomic absorption spectroscopy and electrochemical performance tests were carried out in the laboratory, along with analysis of electrolytes by cycle voltammetry and loading-discharge tests. Electrolytes containing 0.114 mol.L-1 vanadium and 3 M H2SO4, and cell potential of 1.14 V, were produced from VMSA vanadium pentoxide. The results of cyclic voltammetry showed that in the V(II)/V(III) electrolyte the oxy-reduction reactions between the pair V2+ and V3+ have characteristics of a quasi-reversible system, and in the V(IV)/V(V) electrolyte the reactions between the pair V4+ an d V5+ have characteristics of a reversible system. It was also observed that when adding sodium and magnesium sulphate in 5 M H2SO4 solutions, there is the precipitation of vanadium pentoxide. In charge-discharge tests with the electrolyte containing 0.114 mol.L-1 vanadium and 3 M H2SO4 in solution, the battery showed 90.1% coulombic efficiency, 98.3% voltage efficiency and 88.5% energy efficiency, compared to other developed energy storage systems. After some charge-discharge tests, strong wear was observed on graphite electrodes, severely compromising the energy efficiency of the cell.

The desalination process using reverse osmosis membranes has provided drinking water for families in the semiarid region of Brazil since the 1990s. Currently, this process is being used by a Federal Program called “Água Doce”. Its predecessor, the Água Boa Program, resulted in the population abandoning part of the systems. Having in mind to collaborate that the same does not happen with the current program, this research proposes to present possible ways to improve the performance of the actions of desalination of saline water from tubular wells drilled on crystalline rock formations. Therefore, in view of the complexity of approaching the reality of this scenario, several methodological instruments were applied, namely: documentary and bibliographic reviews, field research in a community benefited by the Program, risk / failure assessment and technical and economic feasibility analysis. The results obtained allowed to characterize the scenario of this study, to explore the Program management model and technical data of the systems design. This, consequently, allowed us to understand the complexity involved in the implementation and continuity of the Program. It was possible to identify the problems experienced by communities to keep the systems in operation, such as: system outages due to lack of maintenance, lack of spare parts and equipment, lack of chemical products, absence of operators and suspension of payment from operators by the city hall. The application of Risk Management contributed to the development of a) A proposal for a risk methodology aimed at the scenario of the Água Doce Program in the state of Bahia; b) Development of an Analytical Risk Structure for the Program; c) Survey of a list of 36 risks, categorized and ranked according to the urgency of their treatments. The comparison of the results of risk management with the result of the first monitoring of the program in Bahia, evidenced the occurrence of the risks raised, which had the effect of suspending the operation of 31% of the systems of the installed systems. The technical analysis made it possible to verify that being the systems designed to supply 10L / day / person, well flow rates are not being used according to their full production capacity. Total dissolved solids in the purified water of most systems is below 200 mg / L, 80% below that specified for drinking water (1000 mg / L). Regarding the consumption of electricity, of six systems in the municipality of Ipirá in Bahia, there was an average trend of increase of 3.92kWh / m³ between the projected and the measured. The study for the centralization of desalination systems in Uauá, allowed the simulation of the concentration of eight treatment points in a single plant, and thus, the identification of the advantages in relation to the operation, logistics, acquisition and maintenance. On the other hand, the high investment cost for the acquisition and installation of water mains was identified as a disadvantage. Therefore, this work allowed the development of a list of opportunities for reliability in the water supply by the Program, presented in the body of the chapters.

This work seeks to evaluate issues related to the teaching and learning process to improve the
quality of engineering education. Initially the grades and outcomes of ENADE (Exame Nacional
de Desempenho dos Estudantes) for control and automation engineering courses are
analyzed in order to identify common flaws and possible ways to upgrade these courses. The
choice for control and automation engineering was made because of the actual context about
industry 4.0, which is directly related with this area. Among some difficulties found are the
distance between theory and practices, learning gaps in the basic cycle of the course and the
challenges related to the subject with the real engineering context problems. Thenceforth the
active and cooperative methodologies appear as a potential solution to these issues. Some
studies are explored to better understand these innovative methodologies with their challenges
and limitations. Some points guide to adopt mixed methodologies, which considers traditional
and innovative techniques working together. These points are constructed from three key
elements such as the human cognitive architecture, the educational objectives and the learning
styles. They bring some reflections about inflexible choices while preparing classes and
courses. The last part of this research shows important components supporting these
strategies used in the classroom. All of them are part of the complex matrix involved in the
teaching and learning process. This section highlights the context of organizational culture,
curricula, student affiliation, teacher training and assessment programs to the engineering
courses. It also explores their roles and it proposes some actions to work with them.

This work presents results of the development of an alternative rotomolding process with the increase of pre- and post-heating chamber sections, carried out with the construction of a rotomolding prototype-machine. This invention covers some gaps that have limited conventional processes, which are characterized by long cycle times and energy waste. The work was initially focused on the main objective: the reduction of cycle time; from this, consequently, the other gains and modeling of the new process were provided. This was only possible with the manipulation and reuse of the heat generated by the process, thanks to the purpose of a new architectural arrangement. The proposed method included the construction of the prototype for the production of samples, followed by tests to certify the quality of the main physical properties of the product produced and an energetic study of the process. The results showed a reduction in the cycle time and, consequently, a reduction in energy consumption, due to the reuse of the heat itself, which was previously wasted on the environment at the end of each cycle; then, machined parts had their main mechanical properties validated through their measurement uncertainties, evaluated in accordance with the internationally recognized method concerning this task, namely the GUM framework. From the general results obtained from the proposed prototype, it appears that the production maintained the quality of the main physical properties evaluated, including the uniformity of the samples, which proves the guarantee of stability of this prototype in the serial production of parts in scale industrial; also, there was a reduction in production costs; this fact allows a future investor to visualize that, for each monetary unit spent in kWh of energy consumed, a percentage of cost reduction is obtained in each production cycle. These gains prove the feasibility and superiority in efficiency and performance of this prototype machine compared to the other renowned manufacturers of industrial rotational molding machines.

Microalgae are used in different industrial processes, such as atmospheric carbon fixation and effluent treatment, up to the manufacture of industrial products such as animal feed, high added value molecules, biofuels. However, the production of microalgae still faces several obstacles, such as the high cost of production, especially for the manufacture of products with low added value or in environmental remediation processes. In the present work, the development of a porous substrate photobioreactor from clay ceramic named Clay Ceramic Photobioreactor (CCPB), is proposed. The project was built and tested on a bench scale. The CCPB was made with simple and low-cost materials and was designed to cultivate microalgae adhered as a biofilm, immobilized on the surface of the reactor. The proposed system design allows for an almost complete separation between biomass and liquid culture medium. The photobioreactors were evaluated at different mass ratios between clay and sawdust and brought to a burning temperature of 900°C. The results showed that the particle size of the sawdust must be sieved in a 10 mesh and mixed in the mass proportion of 33.3% of sawdust and 66.7% of red clay. 3.95 gm-2.d-1 dry biomass after 7 days of operation, without CO2 injection, at a light intensity of 45 μmol.m−2.s−1. The CCPB allows the biomass to be harvested by simple surface scraping and this process guaranteed a reduced moisture content between 78 and 82%. The production and cultivation of microalgae in the Clay Ceramic Photobioreactor tends to have a lower energy consumption when compared to traditional suspension cultivation, such as tubular and flat plate photobioreactors, as well as open ponds. The maintenance of the system on a laboratory scale presented advantages such as the reuse of the plates and the resistance to high temperatures. Clay appears to be a viable material for the production of new systems for microalgae cultivation.

The management of urban solid waste (MUSW) comprises a set of actions for the planning and development of public policies. This thesis aims to develop a theoretical model to assess the socioeconomic metabolism of solid waste (Socioeconomic Metabolism of Waste, SEMw) through an exploratory study and Structural Equation Modeling (SEM), adopting technical variables (metric) and social variables (not metric) from the GRSU process. The end-of-life tires (ELTs) or scrap tires case study of a city of 300,000 inhabitants was adopted. The first contribution of the thesis work was the development of a database through deductions and exploratory analysis from public sources (Institute of Geography and Statistics (IBGE) and National Traffic Department (DENATRAN)), to carry out a prediction and preliminary diagnosis of the mass balance of ELT flows in the city. The second contribution, which represents the main innovation of the thesis work, was the development of MEE through technical (Direct Material Flows, DMF, and Reverse Material Flows, RMF) and social constructs (Socioeconomic Factors or Socioeconomic Environment, SEF, and Sociodemographic Factors, SDF) to guide GRSU. For MEE, a sampling was performed using a structured questionnaire (with Likert scale) and, later, modeling in the SmartPLS software using the partial least squares (PLS) approach. The results obtained confirmed 70% of the hypotheses presented in the theoretical framework for SEMw evaluation. The model comprises an innovative approach, capable of relating objective (metric) and subjective (non-metric) variables. In the MEE analysis of SEMw, the initial diagnosis of the ELT flows adopted in the mass balance was confirmed, which presents useful information to guide researchers and public managers in the development of scenario analysis procedures related to the generation, management and disposal of solid waste. MEE is an analysis tool that can be adopted to support the execution of the ELT management plan or similar waste management guidelines.

The textile dyeing industry generally uses traditional processes, which tend not to be
environmentally friendly. This industry is the most chemically intensive, and the second
polluter of clean water (after agriculture). Traditionally, they use large amounts of water
together with large quantities of chemical additives, which can have a huge environmental
impact and could be harmful to human health directly or indirectly. Recently, papers
has been published in the scientific literature in order to improve the sustainability of
the process, focusing in finding alternative solvents and techniques to reduce the amount
of water and chemicals used, as well as improve the quality of the dyeing and keep the
cost of the process low. Ionic Liquids come into the light as new versatile media for many
chemical syntheses, enzymatic catalysis and green engineering processes. They are made
of a collection of positive and negative ions, but unlike conventional molten salts, these
materials are liquid at room temperature. The group of protic ionic liquids show additional
advantages, because of low cost, usually biodegradable and simple synthesis, so they are
known for their acid-base reaction mechanism, corresponding to the formation of those
salts. In this work, it was optimized an alternative procedure available in open literature
to dye different types of fabrics with reduced number of dyeing agents: textile dyes, a
cationizer pretreatment fiber technique, and protic ionic liquids as solvent or additive in
aqueous solution. Therefore, the objective is to reduce environmental impact and increase
the dye quality of this procedure, which was used to dye six different fibers in order
to analyzed the effectiveness of the dyeing agents in terms of different dyeing quality
measurements such as absorption of color and wash fastness standards of the dyed fiber.
Cytotoxicology assays of the fabrics treated with protic ionic liquids were also evaluated
and they did not presented any toxicology. The tests results with protic ionic liquids as
the only additive with 30% m/m in aqueos solution shows color strenght until 250 times
bigger than the alternative procedure available in open literature, and cationization played
a fundamental role in color fixation of the fibers. Furthermore, an innovative proposal is
presented using reactive dye as a “universal dye”, aiming at a more sustainable and safe
profile for the textile industry.

Greenhouse Gas (GHG) emission reduction projects, arising from the Kyoto Protocol, should have as a complementary purpose the delivery of co-benefits for sustainable development. Research carried out in developing countries has pointed out the limitations of these projects in order to achieve this objective. Considering that the energy sector plays a critical role in the reduction of GHG emissions, the purpose of this thesis is to analyze opportunities and challenges for the expansion of the co-benefits for sustainable development generated by the wind power CDM projects in Northeast Brazil. The research privileges qualitative research strategies and techniques, being divided into five methodological phases: 1) documentary research carried out in the main CDM database (CDM Pipeline) and in the ABEEólica database on Brazilian wind farms; 2) construction of the research analysis model (framework) and elaboration of the data collection instrument necessary to assess the co-benefits from the projects; 3) ex-ante analysis of the co-benefits declared in the 50 Project Design Documents (PDD) selected; 4) ex-post analysis of the co-benefits perceived by the managers of the 10 projects visited; 5) comparison between ex-ante and ex-post analyzes and identification, categorization and analysis of the opportunities and challenges for increasing the co-benefits delivered. The results show the importance of conducting co-benefits’ studies after the implementation of CDM projects, since the co-benefits declared in the PDDs were much lower than those perceived by the managers. Considering the political-institutional dimension, the main opportunity identified comes from the global level and it is the creation of the Sustainable Development Mechanism (SDM) based on the Paris Agreement. And the biggest challenge to be faced is the improvement in the performance of the Brazilian Designated National Authority (DNA). In the environmental dimension, the main co-benefits are the improvement of air quality and the protection of natural resources. Opportunities arise from legal instruments at the national level: the legal reserve and environmental licensing. And the biggest challenge is to improve water management for communities. As for social co-benefits, the main finding is the creation of new jobs, even if they are limited. The opportunities are related to the Corporate Social Responsibility (CSR) policies and the challenges to be faced are the increase in community participation in the projects and the improvement of their health and safety. Finally, in the economic dimension, the greatest co-benefit is the incentive for local economic growth. The great opportunity that is still underexplored is found at the project level: the possibility of reconciling wind generation with other economic activities, notably solar generation and agricultural activities. And the main challenge, coming from the national level, is the increase in technology transfer.

The process of universalization of basic sanitation reveals as an inducer of a better quality of life and population health according to the specialized literature. Public policy-making and stimulating public and private investment have come to play a prominent role in providing access to piped water and basic sanitation facilities. This is especially in developing countries and as part of a recent global effort which aim at universalizing, by 2030, the drinking water supply services and the sanitation conditions, both fundamental for human life and sustainable development goals. Given this situation, the aim of this study is to estimate the performance of integrated management of basic sanitation in Brazilian municipalities and its impact on population health in regions with low human development. Empirical model is developed that relates three aspects of this issue: evaluation of the relationship between performance and low coverage of basic sanitation provision in Brazilian municipalities, analysis of the dynamics of the basic sanitation sector in Brazil between 2008 and 2016, regarding productivity from the national regulatory framework, and the evaluation of the role of the expansion of basic sanitation in municipalities of a Brazilian region which is widely known for its low social development and a high level of child mortality. The Multiple Data Envelopment Analysis (M-DEA) and Structural Equation Analysis (SEA) approaches are used in this study with microdata from the Brazilian Basic Sanitation Information System, Demographic Census, Basic Education Census, Brazilian Unified Health System Information Technology Department and United Nations Development Programme. The main results corroborate that the lack of basic sanitation infrastructure in households is potentiated by the inefficiency of managing the sector's operational and financial resources, causing perverse effects on the high level of child mortality in the Brazilian poorest regions. It is estimated that the analyzed sanitation companies may increase their operational and service coverage results by more than 60% in the municipalities where such companies operate and that the 10% increase in access to household sanitary sewage is associated to a reduction of 5.7 deaths per 1,000 born alive. The results found provides subsidies to support decision making by sanitation managers and public policy makers in the country at microanalytic level. This enables a better competitive position in the sector for integrated sanitation management and its universalization in Brazil, as solid support in favor of prioritizing public investment on basic sanitation projects particularly in the poorest regions.

Climate risks can have significant economic and financial implications for companies in all sectors and addressing them requires effective and urgent responses. Therefore, companies need to understand these risks, identify them, evaluate them and take steps to manage them. The main objective of this study was to investigate the potential factors that influence the implementation of climate change strategies by corporations, in the light of the Theory of Legitimacy, Agency, and Stakeholders. To achieve this, an empirical study was carried out in Brazilian, French, and US companies, listed on stock exchanges, which answered the questionnaires of the Carbon Disclosure Project (CDP), in the period between 2016 and 2018, totaling 639 observations. Evidence suggests that although awareness of climate risk exposure by companies surveyed is embryonic, 97%, 96%,
and 88%, respectively, of French, American, and Brazilian organizations integrate climate risk management into the global and interdisciplinary risk management process. It was also discovered that numerous multinational companies claim that they have not identified any climate risk with the potential to impact their business. Globally, the companies analyzed are 1.41 times more exposed to regulatory risk than to physical risk. On the other hand, they are 3.12 times more exposed to regulatory risks than to market risks. Also, 31% of Brazilian companies did not have any projects effectively implemented; this percentage is 15% in France and 8% in the USA. In addition, 30%, 7%, and 8% had no climate initiative implemented, respectively from Brazil, France, and the USA. The overwhelming majority of the initiatives implemented in all countries is “energy efficiency” while the least implemented were solar and wind energy. Thus, companies are increasingly betting on energy efficiency as the most efficient way to reduce gas emissions, the main cause of global warming. It was concluded that the climate change efforts of the analyzed companies are still timid and incipient. The modeling results showed that of the 14 factors analyzed, 13 influence differently from one country to another. There are 4 key factors that, regardless of the country or region, determine the implementation of climate strategies by
companies: profitability, size of the board of directors, climate regulation, and the auditing company. Evidence revealed that, despite the low level of maturity in the management of climate risks and very timid and incipient efforts regarding the strategies to deal with climate change of the analyzed companies, if incentive measures are adopted that increase economic and financial performance (incentives for example), or increasing the size of the board of directors, or creating new climate regulations or tightening existing ones, as well as encouraging the adoption of an audit process would directly increase the implementation of climate change strategies.

Information on the quantities of green coconut shells produced in coastal regions is not well known, which can make it difficult to manage these frequently wasted materials, as well as the understanding that they can be included in a production process as a raw material, with various possibilities of use and income generation. Given this situation, the objective of this research is to develop a diagnosis of the potential for valorization of green coconut shells, after water consumption, in public places in municipalities on the southern and southern coast of Bahia. It is also intended to identify the future demand of the potential possibility for the recovery of the bark, providing subsidies that can be used to organize the use of this material. In this context, following the research method, consisting of five steps, it was possible to obtain the following results: (i) characterization and diagnosis of bark waste in the region; (ii) amount of bark generated per hut over the months; (iii) equivalences in fiber mass and occupied volume; (iv) bark handling logistics among merchants; environmental disposition of the shells in the visited places; (v) analysis of the availability of cooperation between entrepreneurs and researchers from universities or research centers; analysis of strengths and weaknesses and opportunities and threats (SWOT); (vi) identification of the main groups of possibilities for the application of green coconut husks in the market and a potential product for valorization – tubes for the creation of cocoa seedlings; (vii) obtaining future demand for tubes in the region through quantitative techniques for predicting time series; and (viii) the evaluation of the uncertainty of all quantitative information dealt with in the research. The main scientific contributions of this work consist, therefore, (a) in the diagnosis of the waste of green coconut shells in the region; (b) the possibilities of application of coconut shells; (c) in the demand forecasting method elaborated for time series without trends and with high variability; and (d) in assessing the uncertainty of the quantitative information obtained. Thus, the study developed can be used as a subsidy, either for replicating the research process in other types of waste allocated in any region, or for the adoption of public policies to manage these materials, or even for the encouragement and creation of an appropriate productive scenario for the management of green coconut shells in the study region, which contributes to the understanding of the potential for generating environmental, economic and social value from the use and processing of these wasted materials

Brazil is the world's largest producer of sugarcane, accounting for almost 41% of production, followed by India (17%) and China (6%). Sugarcane quality is an important factor in the yield of the sugarcane industry and one of the main indicators of sugarcane quality is the sugar content (°Brix). In addition to oBrix, Total Recoverable Sugar (ATR) is a typical productivity indicator that provides the mass of sugar (kg) present in a ton of cane produced. Currently, the methods most used by the sugar and alcohol industries to measure °Brix are the °Brix refractometer, the MIR spectroscopy (middle infrared spectroscopy) and the NIR (near infrared spectroscopy). In turn, the ATR analysis is performed in the sucrose laboratory through physical processes such as clarification and filtration, among others. The technologies for measuring °Brix and ATR are based on sampling and laboratory analysis, which makes it impossible to monitor in real time the quality and productivity of sugarcane and the consequent decision-making in production management. This work presents two innovative proposals for real-time monitoring of sugarcane oBrix and ATR. In the first case (oBrix), two electronic devices (Dendometer and UltraBrix) were developed that provide a non-destructive alternative for measuring the diameter of the stem and sugar content of the cane directly in the field. In the second case (ATR), a pseudo-dynamic model based on Artificial Neural Networks (ANN) was identified to estimate the ATR throughout production, based on meteorological measurements. Stem diameter measurements obtained by the device had a mean error of ±3 mm (approximately 10% at an average diameter of 30 mm) using a standard caliper measurement as a reference. The sucrose content meter (UltraBrix) employs the continuous wave technique and the estimates provided a coefficient of determination (R2) of 0.83, taking as reference values measured by a refractometer. The neural models identified for six cultivars (C0997, RB92579, RB93509, RB845210, RB867515 and SP791011) provided an average error in estimating the final ATR (kg/ton) of the crop of 2,60 (2,01 %), 3,99 (2,86 %), 3,42 (2,49 %), 2,95 (2,09 %), 3,41 (2,53 %) and 3,37 (2,47 %), respectively. Empirical models based on ANN include input variables (accumulated solar radiation, accumulated rainfall, leaves and number of days of planting) that are easy to measure/monitor, which allows the estimation of the evolution of the sugarcane ATR throughout the harvest and the identification of the appropriate time to carry out the harvest, enabling an estimated increase of around 20% in sucrose production.

Supply chains are silent engines of economic globalization. There is a broad consensus in the literature and in professional practice that supply chains are increasingly complex and vulnerable to risks that cause disturbances, disruptions, and critical reactions from society. In this thesis it has been aimed to analyze the opportunities and limitations of a modeling based on multicriteria decision-making/analysis and artificial intelligence (MCDM/A-AI) for supply chain risk management (SCRM), developed through systematic selection, validation and system testing of the hybrid Fuzzy Analytic Hierarchy Process (Fuzzy AHP) method applied in the oil and natural gas industry. Specifically, it was sought to: a. carry out the state of the art by systematic review of the literature network on the SCRM modeling; b. propose and validate a new computational system for supplier selection considering risks based on the Fuzzy AHP method; and, c. propose and systematically test a holistic framework for assessment of typical and sustainable risks of the supply chain with computational support of the Fuzzy AHP method. To this end, an applied research was conducted, with exploratory, descriptive and predictive purposes, of combined approach [qualitative and quantitative], using literature research, theoretical and conceptual development, modeling and case studies. The state of the art of SCRM modeling, performed using bibliometric methods and tools, allowed for the establishment of a systemic understanding of the flow of research in the field over time, providing future research directions. The analysis and interpretation of research gaps and trends in the field enabled the identification, selection, and systematic implementation of the conceptual, mathematical, and computational modeling developed. The proposition and validation of a new computational system for supplier selection based on the Fuzzy Extended AHP (FEAHP) method constituted a proof of concept to verify the feasibility of implementing the SCRM modeling. From the case study of an oil and natural gas company with onshore assets, it was found that the modeling of the FEAHP computational approach was able to automate the supplier selection process in a rational, flexible and agile way, meeting all the necessary performance requirements, thus promoting the choice of the best suppliers in an environment of risk and uncertainty. After the validation of the developed software, the proposition and system test of a holistic framework for the assessment of typical and sustainable [multidimensional risks] supply chain risks with computational support of the FEAHP method was performed. Through multiple case studies of ten oil and natural gas companies with onshore operations [mainly in mature and/or marginal fields], it was found that the results of risk identification and assessment contribute to the creation of risk mitigation and control strategies [predictive action versus proactive action], fostering the development of a Supply Chain Risk Management System. Finally, the results of the system test of the FEAHP tool showed that all its elements combine correctly and present an effective overall performance, promoting in an integral, flexible, failure-free and/or error-free way the improvement of supply chain risk assessment. It was concluded that the various opportunities and/or potentialities of using an MCDM/A-AI based modeling for SCRM overtake the main limitations and/or challenges. Despite the restrictions of this thesis, it is admitted that it contributes to the fruitful field of SCRM research and professional practice by promoting the improvement of the design, understanding, reflection and practice of supply chain network and operations management.

The urban distribution of goods is increasingly impacting cities. Understanding the process of urban distribution of goods is indispensable for the development of policies that provide a balance between the needs of the population, regarding urban supply and the negative impacts generated by this activity. This has led some countries to the development of alternative projects for distribution in the urban area, called city logistics, in which the areas of planning and management of logistics flows are addressed as means to find solutions to problems in search of parity between responsiveness and costs (social and process). However, the literature is still insipid of research in the analysis of the performance of city logistics. Thus, the present work aims to develop a model to evaluate the performance of city logistics and its component parts, with ponderation of which are considered to be of greater relevance in the configuration of efficient, responsive and sustainable activities. The study is of the qualitative and quantitative exploratory-descriptive type, using the self-administered cross-sectional survey procedure, in which the questionnaire was available online. The 575 professionals of companies were questioned, divided between shippers, logistics operators and carriers operating in the Brazilian scenario, selected them randomly. The data obtained were analyzed by the Structural Equation Modeling (SEM) technique based on Partial Least Squares (PLS). A mathematical model was presented, forming 3 exogenous latent variables: (i) relationship history, (ii) meetings and (iii) urban parameters; and, 3 endogenous: (i) collaboration, (ii) key factors and (iii) city logistics performance. After testing the model using structural equations, 5 of the 8 hypotheses proposed in the theoretical model were supported, however, 7 hypotheses were maintained in the final model. The results showed that the latent collaboration variables, key factors and urban parameters had significance to foresee the performance of city logistics by 57,8%, highlighting the magnitude of the external factor loadings of the latter and still demonstrating the importance of integrated solutions. The model presented relevant contributions to the refinement of theory and practical contributions to support the management of the distribution of goods in the urban area.

Agroecology emerges as an alternative to add value to production and generate better results for producers. However, family farming faces several barriers to the commercialization of its products implying financial sustainability. In turn, the Agroecology Networks that commercialization aims to establish as an organized and dynamic way to connect with the market in a strategic way, making it possible through the commercialization circuits to access new markets. The dissertation aims to study the context of family farming in the southern coast of Bahia, identify the main bottlenecks, opportunities and trends of the segment, evaluate how and how marketing networks have contributed to the development of sustainable financially family businesses in the region. The method used in the research is deductive, accompanied by verification, with exploratory and descriptive approaches. For the composition of the study, research was conducted in eight rural producers associations in the region and in an agroecology network. For this, the main management and marketing processes were mapped, information was collected and document analysis was performed and the results obtained. In order to validate its relevance, the impact and competitiveness of the Atlantic Forest Peoples Agroecology Network. The results indicate that family farming enterprises do not have a level of organization and management, and do not use modern technologies or technological innovation, while the People of the Atlantic Forest Agroecology Network has a financially and sustainably successful business model, which has achieved significant results for family farming in TLS through a well-structured and organized management and marketing model adding value to family farming by facilitating access to new markets through marketing circuits.

Saltwater desalination has proven to be a promising alternative to supply the high demand for drinking water around the world. In Brazil, lack of water is a recurrent problem, especially in the Brazilian semi-arid region, predominantly located in the Northeast. The use of renewable energies as energy source has many benefits and, among them, solar energy is very abundant and has a great potential for use in Brazil. The present work aims to evaluate the technical and economic feasibility of a desalination plant coupled with solar energy as the energy source. The desalination technique chosen was the multi-effect distillation (MED), a process that requires a high amount of thermal energy and therefore adapts well with solar energy. The city chosen for the case study was Bom Jesus da Lapa (BA), a city with a high incidence of solar radiation during the year and which also suffers from the lack of water. The solar collector model chosen was flat plates and a tank system for thermal energy storage was included to ensure the continuous operation of the desalination plant. The 90% brine recycle combined with treatment of the remaining brine was proposed seeking to solve a problem which is present in many desalination plants, the proper destination of the brine reject. Technical feasibility results show that water production of the 72 m³/day plant capacity with 2822 m² of solar collectors’ area presented satisfactory results. Results show that the tanks can keep the water hold up and temperature at the end of the day, indicating that the continuous production of water is technically feasible. In the economic feasibility study, the water sale’s price of US$ 5.97/m³ for a useful plant’s life of 20 years resulted in positives Net Present Value (NPV) and internal rate of return to plant implementation. A Monte Carlo analysis indicated that the NPV is very likely to be positive, even with the uncertainties inherent to the capital investment, operational costs and water sale prices. It is expected that the present work can contribute to the desalination investments in the Brazilian semiarid region, providing economic and social development.

Air pollution has been one of the main topics of interest in the scientific
environment in view of its involvement in the quality of human health,
ecosystems and constructed goods, identifying itself with a fundamental
dimension in the search for development Sustainable. The unbridled growth of
cities, the continuous increase in the population and the intense industrialization
are factors that have driven the scenario that we have today. transmissions in
the Salvador Region for 2018. Carbon monoxide (CO), nitrogen oxides (NOx)
and particulate matter (MP) were considered, evaluating and comparing the
methodologies and results of the latest studies in this region. To achieve this
objective it was necessary to quantify the inventory of vehicular emissions,
which employed the calculation method of the European Environment Agency
(EEA) using emission factors associated with vehicular mileage to estimate the
issuance of Pollutants. Such data, coupled with meteorological and topographic
information, was fed into AERMOD View to simulate the behavior of pollutant
dispersion. The results obtained indicated the contribution of vehicular
emissions to air pollution in the city of Salvador indicating the locations most
impacted by this activity. It is expected that the results of this project will serve
as a guiding parameter for the management of air quality in the city of Salvador,
validating the location of existing air quality monitoring stations and proposing
new locations to be monitored.

In Brazil, the building sector is the highest electricity consumer, accounting for 50% of all electricity consumed. In Brazilian Federal University buildings, the electric expenses are one of the highest among the items of monthly expenses. It indicates the need for improvement in the use of energy, especially, considering the increasing budgetary constraints faced by these institutions. Due to this fact, this research with a case study at the Polytechnic School of the Federal University of Bahia proposes an investigation on the energy efficiency in university buildings, identifying the main opportunities for the rational use of electric energy. It was carried out a literature review focusing on the analysis of energy management methods applied to university buildings. Then, an energy review of the building was carried out following the ABNT NBR ISO 50001 standard. The analysis of energy use and energy consumption indicated that electricity is the institution's main source of energy and that the electricity consumption is concentrated on air conditioning systems, with 73% of representativeness. It was identified that the building´s laboratories are responsible for 45% of electricity consumption. The energy indicators were calculated to permanently monitor energy performance through comparisons with the baseline. The energy performance indicator “Energy Use Intensity” resulted in 55 kWh /sf /year, while the indicator “Average Consumption per Student” resulted in 62 kWh/student /month. Two significant opportunities for improving energy performance in the building were identified: the retrofit of lighting (replacement of fluorescent lamps with LEDs), and the retrofit of the laboratories' air conditioning (replacement of existing equipment with inverter air conditioning). Together both measures would result in a 24% reduction in annual electrical consumption, which corresponds to a cost reduction of R$ 379,573/year. The payback time of investment for these measures was calculated at seventeen months. Based on the results obtained, it was observed that the Polytechnic School of UFBA has the potential to improve its energy performance based on feasible and economically viable proposals. It is recommended for the institution to implement an Energy Management System (EMG) according to ABNT NBR ISO 50001 standard.

The production of high molecular weight polyethylene by suspension polymerization using the Ziegler type catalyst supported on inorganic materials produces polymers with mono, bimodal and multimodal molecular weight distribution, however the production of multimodal high molecular weight polyethylene involves several complex strategies. In this study, the ethylene polymerization reaction and the synthesis of high density polyethylene nanocomposites with clay, graphite or talc were carried out using direct in situ polymerization in solvent and a Ziegler type catalytic system (TiCl4 and triethyl aluminum in hexane) without inorganic support in a batch reactor. The polymer produced showed thermal degradation in an inert atmosphere at a temperature above 400°C, having a thermal stability similar to the commercial high-density polyethylene produced by Braskem. The melting temperature of the polymer produced indicates that it has a high molecular weight and a degree of crystallization of about 52%. The molecular weight distribution of the obtained polymer has a wide dispersion and varies from a molecular weight (log M) 2 to 7.2, composed of four peaks which indicates a multimodal distribution. In the oxidizing atmosphere, the polymer produced has three thermal oxidation events above 400°C due to the combustion of low, medium and high molecular weight molecules. The thermal oxidation of the nanocomposites is displaced and reduced to high temperatures, indicating an improvement in the thermal stability of the polymer matrix due to the barrier effect of the clay for gases and volatile compounds and the flammability tests showed an effect of reducing the progression of the flames for all nanocomposites.

The growth in global air traffic in recent years and the prospect of growth in the coming decades call for ever more efficient and safe air traffic management, as well as contributing to the workload of its controllers. In this scenario, solutions are increasingly needed to assist these professionals in the decision-making process in the different activities performed during all phases of flight. The en-route phase comprises the most enduring phase of flight, in which controllers perform the monitoring, detection and resolution of conflicts between aircraft. These activities involve purely “human-centric” procedures, i.e., all actions are defined by the human being, even considering the availability of automatic alarms. This work proposes a hybrid model, using artificial intelligence and heuristic techniques, to detect and resolve longitudinal conflicts during en-route flight in order to reduce the workload of the traffic controller and enable greater efficiency in conflict detection and resolution, with the consequent increase in airspace security. The scope of this work is limited to one-way airways located in the upper airspace (above 25×103 ft) and the proposed approach comprises the detection and resolution of longitudinal conflicts through horizontal speed adjustments and flight level (altitude) changes of aircraft. The hybrid model proposes an innovative metric based on a fuzzy inference system to quantify the conflict level between two aircraft. A recursive algorithm for clustering conflicting aircraft is applied to define flight level exchanges through a genetic algorithm-based optimization problem. The model was simulated and tested through different case studies involving the existence of conflicts between aircraft, taking as reference the control actions based on the rules and restrictions defined by the International Civil Aviation Organization (ICAO). Comparison between the results obtained by the proposed model and standardized air traffic controller actions shows the potential of the proposed model in improving the safety and optimization of airspace use, providing greater efficiency and anticipatory capacity for conflict detection and resolution.

The methyl methacrylate polymerization (MMA) in the presence of supercritical carbon
dioxide (scCO2) was studied as an alternative technique to incorporate the copaiba oil
(Copaiba ssp.) in particles of methyl polymethacrylate (PMMA). The traditional process
of drugs incorporation in PMMA using organics solvents bring a problem: the presence
of residual solvents in the final product. The use of scCO2 for the micronization of
particles and the encapsulation of compounds in the pharmaceutical area offers a
perspective of big advances, eliminating the number of steps in the process and allowing
better control of system properties. In this paper, the PMMA particles were produced
through the polymerization of MMA by dispersal in scCO2 in the presence of poly
(dimethyl siloxane) terminal vinyl (PMDS-V) as surfactant agent and benzoyl peroxide
as initiator. In polymerization by dispersal, the conditions should ensure a unique phase
in the polymerization initiation, what requires that the monomer, the initiator, and the
surfactant be completely miscible in CO2, forming a homogeneous system. To determine
the pressure, temperature and composition conditions whose system is single-phase
before polymerization, a previous study of the system phase balance under study was
carried out at high pressure, because there was not enough data available in the literature.
The phase balance data for binary system CO2 + MMA and to the ternary system CO2 +
MMA + PDMS-V were executed using a syntactic-static method in a stainless-steel
balance cell with variable volume, including a piston and sapphire window, in
temperatures of 50, 60, 70 and 80ºC and the molar fraction ranging from 0,6949 to 0,9499
to the binary system and 0,6833 a 0,9444 to the ternary system. In the binary system, i
was observed a high miscibility of CO2 in the MMA with a significant volumetric
expansion of the liquid phase. The surfactant PDMS-V was added to this binary system
to investigate its effect in the phases equilibre. To the ternary system CO2 + MMA +
PDMS-V, the results indicate that the addition of PDMS-V induced to a small increase in
the transition pressure and, to the liquid-liquid equilibrium region , occurred a large
increase in the system transition phase in all temperatures. Ensuring the homogeneous
system before polymerization, as the polymer is formed, it is insoluble in the reaction
medium, and the precipitation of its particles occurs. To guarantee a unique phase to the
polymerization start, were adopted pressure ranges at 160 to 180 bar to 80 ºC and the
reactions were performed for four hours. The experiments were realized with different
surfactants percentages regarding to the monomer and from the monomer to the total
volume, to observe the surfactant initial concentration and monomer effect in the PMMA
particles sizes distribution and morphology the experimental racings occurred with a
permanent initial concentration and to PDMS-V at 7,02% e 10% (w/w) and to the MMA
at 10, 12,5 and 15 % (w/w) concentrations. The concentrations were defined from existing
studies in the literature that obtained satisfactory results. The PMMA microparticles were
characterized by gel permeation chromatography (GPC), by scanning electron
microscopy (SEM) and by dynamic light scattering (DLS). The monomer residual content
evaluation was determined by gas chromatography (GC), meanwhile the functional
groups and the chemical structure of the polymer sample were identified by infrared
spectroscopy by Fourier transformed (FTIR) and proton nuclear magnetic resonance
(RMN H1), respectively. The results obtained indicate that the PMMA spherical particles
containing up to 5% w/w of copaiba oil, 10% w/w of PDMS-V, 2% w/w of BPO regarding
the monomer and 10% m/m of MMA applied in this work. The results also indicates that
the copaiba oil presence affected the polymerization, because the particles medium
diameters containing the copaiba oil ranged from 151,8 to 257,1 μm. They were larger
than the particles medium diameters obtained with 10% of PDMS-V (28,6 μm to 34,1
μm) and 10% w/w of MMA (42.5 μm to 48.4 μm). This increase in the average particle
diameter occurred due to the formation of a relatively smaller number of nuclear locals
or an increase in the coalescence rates, possibly due to the addition of copaiba oil that
changed the proportion of the surfactant in the reaction, making it impossible to form a
more stable drop which may have led to a disorderly growth of polymer chains. The data
obtained showed that using PDMS-V as a surfactant it was possible to obtain spherical
particles of PMMA with size distribution in a narrow range an the use of BPO as an
initiator did not alter the reaction kinetics. No studies were found in the literature on the
dispersion polymerization of MMA in the presence of scCO2 is investigated using PDMSV
and BPO, as surfactant and initiator, respectively

Systems reliability is applied for failure prediction. The results of the prediction models
include the effects of (i) the sampling process, (ii) the prediction model definition process,
and (iii) operational and environmental factors that determine intrinsic operational reliability.
The assessment of the impact of the sources that determine reliability led to the
choice to assess the impact of the human factor. The objective of this work was to develop
a methodology to continuously evaluate the probability of human error. Regarding sampling,
it was verified the difficulty in obtaining complete data, and a multivariate evaluation
by Structural Equation Modeling was developed. The results showed a low influence of
human errors in the record and a strong influence of the record structure of failures. As
investments in updating records can be high, a solution is to have samples without using
historical data. Regarding the forecasting models, a process flow was elaborated and the
complexity for the analysts was identified. A case study was used to demonstrate that any
method has intrinsic uncertainties that are not always considered. Regarding operational
reliability, it is the result of elements such as the variation of raw material and inputs,
environment, operational context, organizational structure and human factor. They were
assessed how the elements interact with each other. As a result, a low independence of the
elements, and a model in which the output was the Human Factor, directly determined by
the Organizational Factor. As the organization is decisive, one solution would be to use
the task as the center of the analysis.The participation of the human factor led to how to
assess the probability of human error, and vulnerabilities were identified in the assessment
methods. The most used methods adjust influencing factors for the context of the tasks,
and there is diversity in the nominal probabilities of error. A model was proposed to judge
the risk of failing to use drugs, and demonstrated the complexity of including a factor in
the assessment of probability. Regarding the nominal probabilities, two types of human
errors were identified, one is stochastic and the other related to the context. Given that the
context leads to variation in probability, one solution would be to estimate the probability
of error by monitoring the context. Considering the identified solutions, a methodology was
proposed to estimate the probability of error using the task analysis and the monitoring of
equipment variables. Initially, it was proposed to evaluate the frequency of deviations from
the task, indicated by the oscillations of monitored parameters. The method was applied
to a gas compressor and error probabilities were obtained. In a second study applied to a
set of pumps over a record period of 11 years, the variable was the vibration monitored at
each textit ms. It was found that reliability increased over time and success was attributed
to actions on the task. It was possible to measure the probability of human errors and a
process for continuous use was established, demonstrating the potential for applying the
method.

The basic requirements for the implementation of model predictive controllers can be summarized as stability, feasibility, performance, and robustness. One of their main purposes is the plantwide optimization so that different strategies can be applied to achieve it, either in two-layer schemes, as Real-Time Optimization (RTO), or one-layer schemes, as MPC+RTO and Economic Model Predictive Control. These strategies can be implemented in centralized, decentralized, or distributed schemes, but for large-scale systems, the centralized one can be intractable, and distributed control schemes are preferable. Additionally, some controllers design may result in an infeasible optimization problem in some scenarios, e.g. when a small control horizon is applied in design based on terminal invariant sets. In this context, this thesis focuses on stabilizing model predictive controllers with economic objectives, applying solely terminal equality constraints associated with design mechanisms to improve the feasibility of the optimization problem, in addition to their integration into centralized and cooperative-distributed control schemes. The contributions of this thesis are summarized as: (i) a one-layer model predictive controller whose optimization problem is always feasible, suitable for systems with open-loop unstable states, applying slacked terminal equality constraints, (ii) a cooperative-distributed model predictive controller suitable for stable systems, which stabilizing properties are integrated with its tuning, and (iii) a stabilizing cooperative-distributed gradientbased economic predictive control based on terminal equality constraints suitable for non-stable systems, with design mechanisms to enlarge its domain of attraction. The stabilizing properties are guaranteed by Lyapunov arguments, and the feasibility targets the fulfillment of constraints, in addition to the solution of the optimization problem at all time steps even with small control horizons. In order to exemplify the aforementioned features of these strategies, case studies are assessed using scenarios where the controllers have small control horizons and, in the distributed scheme, a short time frame for communication and conflicting objectives among the agents. 

This research aims to evaluate the volume of investment in wind farms in 22 municipalities
of the State of Bahia, located in the central axis of the state, using the TOPSIS muticriter
decision method. To define the criteria and the most appropriate method, a Systematic
Review of Literature - RSL was carried out at Compendex and Scopus bases according
to the protocol that was structured. For the application of the decision method, the
following criteria were defined: investments by Mega Watts (MW) produced, investments
by quantities of plants and MW by quantity of plant; the weight vector was determined to
be equal to 0.33 for all the criteria. Next, the standardization was done, weighting of the
decision matrix, calculation of the ideal positive and negative solution, calculation of the
distance and coefficient of approximation with the aid of software R and spreadsheet. With
the results obtained from the RSL, it was verified that the number of publications on the
multicriteria theme is increasing. The collaboration of European countries, the Middle
East and Asia, mainly China, has the largest collaborative network and the TOPSIS
method presented itself as the best tool for the problem structured in this work. The order
was established where Sento Sé was the best evaluated while Casa Nova occupied the last
place. By spatially distributing the arrangement it was possible to observe two groups
spatially distributed in opposite ways. Thus, it is concluded that the RSL contributed
to the understanding of what a decision-making process is based on multicriteria, its
importance and how Brazil falls short in the discussion of this theme. In addition, it can
be concluded that the best evaluated municipalities are: Sento Sé; Pindaí; Itaguaçu da
Bahia; Caetité; Xique-Xique; Riancho de Santana and that there are municipalities with
potential of generation but that is not being completely taken advantage of.

The Southern Coastal Territory of Bahia (TLS), until the end of the 1970s, had cocoa as one of the pillars of the Bahian economy, with production based on the con centric model of income, where many workers lived on the cocoa plantations in semi-slavery. From the 1980s, with the appearance of the witch's broom pest, the cocoa culture began to lose economic, political and social influence. This dissertation intends to make a study about the socioeconomic reality of the solidarity economy in the TLS and what is the technological content used in the productive process of these enterprises against the decline of cacauicultura. This analysis is the result of a survey involving 147 charitable economic enterprises mapped in TLS. The degree of formality, level of entrepreneurship, associativism and cooperativism were evaluated, among others; the degree of financial and technological independence; the relationship with the training of its participants and the role of teaching, research and extension institutions in supporting the projects addressed. The method used in the research is the deductive, accompanied by verification with exploratory and descriptive approaches. The results indicate that these enterprises do not have an entrepreneurial culture and do not use modern technologies or technological innovation, besides having an artisanal matrix of the means of production. In order to overcome this reality, it is necessary that the public power structure programs for the development of cooperative enterprises of the solidarity economy with high added value, focusing on research, science and technology, as well as on the formation of human capital

The multiple contact miscible floods involving CO2 injection into reservoirs represent one of the most efficient enhanced oil recovery (EOR) processes widely used in mature fields and currently of great interest in Brazilian pre-salt reservoirs. Due to the high levels of CO2, which for environmental reasons cannot be released to the atmosphere, the main solution in pre-salt is its reinjection into the well. In addition to increase the oil recovery, the reinjection allows trapping the gas confined in the reservoir. However, CO2 injection and depletion may induce precipitation of asphaltenes, the heaviest and most complex fraction of the oil, causing its gradual deposition in the reservoir and facilities, which can stop the oil production and transportation, with significant economic losses. Therefore, predicting the asphaltene onset precipitation and the amount precipitated under CO2 injection or depletion is a scientific and technological challenge. This dissertation contributes to a better understanding of the main aspects of modeling asphaltene precipitation to accurately calculate the onset of precipitation and the amount of asphaltene precipitated, under reservoir conditions and with few experimental data. The effect of different characterizations methods for the residual oil fraction on the calculation of the asphaltene onset precipitation and the amount precipitated is critically evaluated as a function of the CO2 molar fraction by using the Hirschberg model. In addition, a new method is proposed to determine the asphaltene onset precipitation based on modeling and simulation of the density of the mixture oil-CO2 using the Hirschberg model and the SRK equation of state. Also, the asphaltene precipitation envelope is simulated using the Hirschberg model from a limited amount of experimental data. The results indicate the success of both models in correlating the available experimental data, but their predictive capabilities were not enough explored, because it would require a larger amount of experimental data. The experimental determination of the asphaltene onset pressure (AOP) for different conditions of CO2 injections would also allow the construction and simulation of more complete and comprehensive Asphaltenes Precipitation Envelopes.

The harvest of sugarcane with the use of harvesting machines directly influences the raw material demand required by the industries for the production of sugar, ethanol biofuel and bioenergy. The study of times to failure through proper reliability calculations can help avoid unwanted operational outages. Five systems of sugarcane harvesters called extraction, sugarcane transport, propulsion, drive and electronic are analyzed through a comparison of four models of lifetimes: q-Weibull, Weibull, q-exponential and exponential. The q-Weibull model, which has a connection with nonextensive statistical mechanics, is the generalization with four parameters of the usual three-parameter Weibull model. The q-Weibull model recovers as particular cases the Weibull, q-exponential and exponential distributions. A q-Weibull is asymptotically a power law and becomes an exponential in a limit condition. As a power law, the q-Weibull distribution is able to model complex systems and becomes flexible enough to unify two types of nonmonotonic behavior in their failure rate function that are not possible with the other three models: a bathtub and unimodal curves. These two types of shapes are described continuously, with a fixed set of four parameters. The application of the models to the practical examples is done with the estimation of parameters using probability plotting method, least squares and maximization of the coefficient of determination. The Akaike Information Criterion is used to support selection of models. Analytical expressions applications and graphical illustrations of the reliability and failure rate functions are presented.

The occurrence of overflows in industrial effluent retention systems is an important environmental and operational aspect in most industries. The objective of this work was to analyze and classify the behavior of rainfall and overflows, and to propose a predictive model of overflows into a basin of the industrial effluent retention system in an oil refinery. The cluster analysis for precipitation and tank level time series is analyzed from the perspective of similarity between clusters and the detection of change points to determine the behavior of time series. A constructed predictive model was also proposed for rainwater drainage systems in industrial areas using supervised machine learning with the objective of indicating whether the containment basin will overflow within 24 hours, using the techniques used k-nearest neighbors (KNN) and Random Forest. The set of unsupervised machine learning methodologies used allows information to be obtained on hydrological and process events in scenarios with low data availability without the need to increase the information. It was identified that, in the absence of precipitation or occurrence of low daily precipitation volumes, the system failed, and the percentage of overflows is higher than the expected natural value. In addition, there are no overflows in rainy periods if there is satisfactory operation of the system. Scenarios and variations in sampling techniques for training the classification models were used. The best results were obtained from the Random Forest algorithm using the oversampling, undersampling and ROSE re-sampling techniques.

The demand for energy sources is increasing due to the harmful effects of using fossil fuels. Biomass is a sustainable energy source suitable for replacing them and torrefaction, briquetting and drying are thermal and thermo mechanical processes capable of reducing the cost of the energy generated with it. Some of the benefits of these processes include the increase in combustion efficiency due to chemical changes caused by torrefaction and the reduction of the required excess air due to briquetting. Besides, the increase in energy density due to torrefaction reduces transportation costs, because it allows more energy to be produced with the same volume of biomass. Also the production of a fuel with properties more suitable for storage, among others. This work aims to evaluate the technical and economical feasibility of these processes when used to convert the eucalyptus right before the transportation by trains or trucks to thermoelectric plants. The calculations were made with data obtained from the literature such as the relationship between moisture content and density or the heating value of the wood, between moisture content and the composition of the wood and the efficiency of the boiler where combustion takes place, among others. Data provided from related companies was also used such as the prices and characteristics of the machines. By calculating the net present values and the times of return on investment we evaluated which processes result in the greatest returns on investment and lower times of return on the investment. The processes were organized into three production routes. Route 1, which can be summarized to chopping and drying the wood, route 2, which can be summarized to chopping, drying and briquetting and route 3 which can be summarized to chopping, drying, torrifying and briquetting. The use of the briquetted eucalyptus from route 2 results in a higher energy cost and the only dried eucalyptus from route 1 or the torrified eucalyptus from line 3 may result in lower energy costs and greater and faster returns on the investment, depending on the climatic conditions, the distance between the thermoelectric plant and the conversion plant and the mode of transportation used. The variation in the cost of the steam generated, depending on the climatic conditions, in dollars per ton, for road transportation and the distance of 1 km for lines 1,2 and 3 is from US$ 52 to US$ 81 , US$ 85 to US$ 56 and US$ 49 to US$ 55, respectively. For 500 km it is from US$ 67 to US$ 93, from US$ 71 to US$ 98 and from US$ 59 to US$ 66 respectively. For railroad transportation and the distance of 1 km it varies from US$ 50 to US$ 79, from US$ 54 to US$ 84 and from US$ 47 to US$ 53. For a distance of 500 km it varies from US$ 52 to US$ 81, from US$ 56 to US$ 86 and from US$ 49 to US$ 55 respectively.

Transportation of bulky loads in the Brazilian territory demands stiff planning due to cargo
dimension and weight that trespasses what is permitted by law. Added to that, logic
infrastructure has many problems, from bureaucratic issues to lack of maintenance on roads,
ports and airports. Such problems can hinder transportation and, in difficult access locations,
can make projects unfeasible due to high costs. Proposing airships for cargo transportation is
not new, but it has been disregarded because of its existing technical limitations. Today, thanks
to the latest technological advances, airships can prove to be a niche alternative for acting in
niches in which logistics conditions are adverse to conventional transportation, where access
ways are necessary due to cargo dimension or even route change or due to walkways and towers,
which hinder transportation. Airships can be an intermediate solution between speed and cost,
as well as the reduction of greenhouse gas emissions and minimal dependence of landing and
loading/unloading infrastructure. This paper does a technical comparison between aircrafts and
highway models. From these analyzes it is possible to conceive that airships can be a viable
alternative both economically and technically.

Among the measures to deaccelerate global warming the application of renewable sources to
generate electrical power, such as solar power systems, is indispensable. Concentrating Solar
Thermal Power (CSP) generation is an alternative with a growing potential tha can complement
the electrical grid at places with proper geoclimatic conditions. CSP systems have high efficiency
and larger production capacity when compared to photovoltaic systems, and also the possibility of
thermal storage, allowing them run at periods with no solar radiation. Dish Stirling (DS) parabolic
concentrator systems are the most efficient CSP systems, and their modularity enables their use
in distributed generation. These systems, however, are not yet commercially attractive mainly
due to their high cost of production and low reliability. Thus, the development of more efficient
design methods for DS systems is an important measure to make them a viable alternative for
renewable electricity generation. So, in this work a simple method to design and simulate DS
systems is proposed in order to ease DS systems development. To determine the energy input
of a Stirling engine the ideal isothermal Schmidt model, the ideal adiabatic model, and the
Simple model are compared through the simulation of the GPU-3 Stirling engine, and contrasted
with experimental data. In order to determine solar energy availability, a model of estimation
of the Direct Normal Irradiance (DNI) based on the Linke atmospheric turbidity factor is used.
This model is tested for three Brazilian cities: Salvador, Marília and Porto Alegre. Its results
are compared to measured data from the National Meteorology Institute (INMET - Instituto
Nacional de Meteorologia). The data obtained through these models are applied to the parabolic
concentrator sizing and design based on the energy input of the Stirling engine and considering
the maximum DNI values. The design method of DS systems proposed in this work is successful
and usable for initial assessments of the DS system dimensions, nonetheless the application of
more accurate models for Stirling engine simulation and for DNI estimation, in the absence of
measured data, is necessary.

Virtual analyzers play a strategic role in the petrochemical industry due to its capacity to estimate control variables through mathematical models. Yet, in order to guarantee the model output, it is essential to ensure the availability and reliability of input data, which implies greater financial efforts to guarantee the maintainability of the measuring devices used to generate model input. The aim of this work is to propose a new approach to variable selection for Partial Least Square (PLS) models through the introduction of an indicator which evaluates the gain in predictive power of a model as a function of the increase in its combined costs due to the addition of a process variable as model input. For that, process variables are ranked with VIP (Variable Importance in Projection) scores and, one by one, introduced in different PLS models. The new indicator measures the ratio between the difference in correlation coefficient (𝑟) of the observed and predicted output from the models with and without the input variable, and the difference between the combined standardized costs of the respective models. Thus, it quantifies the ration between gain in performance and increase in costs due to the introduction of an input variable in the model. The proposed approach is used to select input variables for a model that estimates nine temperature points (initial point of distillation 5%, 10%, 30%, 50%, 70%, 90%, 95% vaporized mass, and final point of distillation) of a naphtha, which are used as parameters to determine the naphtha’s quality. There was an availability to select data from 121 process variables (PV), which include flow, temperature, pressure and level variables. The PLS model built under the new approach selected 37 out of the 121 PVs, with a combined cost (𝑐𝑇) that accounts for 34% of the 𝑐𝑇 of the combined cost for the model with 121 VPs, and 88% of the combined cost with variable selection through VIP. The root mean square error of prediction for the model varied between 1.184 °C and 3.108 °C for variables whose values ranged from 90°C to 155°C. The 𝑟 for the validation group varied between 0.875 and 0.932, with the exception of the point with 95% vaporized mass, which displayed an 𝑟 of 0.753. Thus, the variable selection through the new proposed approach was able to develop an empirical model with adequate predictive power to be used in a virtual analyser. As such, the results suggest that the presence of an economic trait during the process of selecting variables, which tends to be purely statistical, contributes to procedures which are more data oriented in the decision-making process of complex industrial environments, particularly in the petrochemical industry.

The growth of medium-sized cities and urban concentration is a worldwide trend.In Brazil, this rapid concentration and the demand for housing, mobility, and infrastructure have seen generated negative impacts on the quality of urban life with increased pollution, waste generation, and neighborhood nuisances.The construction industry is an important agent in this process, in which the demolition, renovation, and construction of buildings involve a complex network of actors and activities.Despite technological advances and regulatory milestones, the industry is still far from implanting a low-impact crop in its construction sites.Most of the difficulties are directly related to the characteristics of the sector: the diffuse character of the production sites; the variety of activities and inputs; the intense use of transport and movement; the quality and productivity problems; the informality and low environmental commitment.

The construction process is not restricted to the urban lot under construction since the various flows (materials, people, and services) impact the environment and it creates "virtual construction sites".These are also important Generators Poles of Travel - PGT (loads, equipment and people), restricting mobility, blocking roads, damaging sidewalks and generating risks.In front of this context, this research presents a method for predicting environmental aspects generated by construction sites, through the integration between a cost base and environmental performance evaluation indicators.Initially, the model development required a comprehensive review of the state of the art related to environmental performance evaluation tools to identify the main problems about qualification and quantification of environmental aspects and impacts of the construction sites.The study then analyzed a set of construction cost databases to answer how to transform cost data into environmental information and this information into knowledge in building practices.To adjust the method, a field survey was carried out to analyze the local impacts of construction sites in the city of Feira de Santana, and how their construction management models and construction practices influence environmental performance.The analysis of the relationships between activities/services, environmental aspects and impacts was based on the model proposed by the EU Eco-Management and Audit Scheme (EMAS), supporting the development of the method and its mathematical representation.A case study was implemented to validate the method using the quantitative list (BOQ) from two residential buildings to measure their environmental aspects.The results validate the usefulness of the method to support the decision-making process in the choice of constructive activities and in the allocation of control systems, such as recommending the execution of off-site services to reduce impacts in the neighborhood.

In addition, the method was easy to apply for evaluation of construction sites, as well as flexible to incorporate other activities, adapting to the demand of builders and public agents to reduce the environmental impacts of construction sites.The results of the application of the method on the case study reinforce its viability as an instrument of environmental evaluation and as a tool to aid the decision making by the control agents and construction management.The choice of cost database as the basis of the method points to greater ease of implantation of the method and diffusion of environmental knowledge, contributing to promoting the reduction of the impacts of these construction sites.

Application of energy efficiency measures is one of the most hopeful solutions to face global environmental challenges, to minimize natural resources consumption and the greenhouse effect. However, the level of implementation in the industrial sector is far below of what theoretically could be achieved due to several barriers, one of which is the behavior of industrial workers. This paper presents a new structural model with variables that predict individuals’ behavior, and analyses a framework proposal to improve the energy efficiency implementation In the first study, a survey was carried out to identify the factors that determine the intention of the workers to adopt actions to improve energy efficiency, based on the theory of planned behavior (TCP). A survey gathered the data to assess the model and a structural equation modeling (SEM) was fitted. The results showed that the attitude and the perceived behavioral control were the latent variables that had significance to anticipate the individual's intention to act. The inclusion of new variables - (i) personal norms and (ii) performance shaping factors increased the the predictive relevance. In the second study, the behavioral intervention protocol allowed to adopt a new procedure to shut down a reactor, that reduced energy losses in the process, as well as to decreased the contaminants’ concentration in the effluent. The results showed that the protocol can be used to influence the behavior of the workers. Finally, it can be assumed that the behavioral intervention protocol can be adopted with real results in other industrial units to improve energy efficiency.

The companies producing wood furniture generate large volumes of waste that are not always properly discarded, generating losses for companies and environmental damage due to increased consumption of raw materials. From this, the objective of this work is to propose design parameters to minimize waste in the production process of eucalyptus wood furniture, seeking greater use of the raw material. By means of the studio of a chair made of eucalyptus wood furniture company, we apply the methodology of Cleaner Production focused on reducing the consumption of raw material and energy, this methodology presents proposals for application of principles of Ecodesign with which the chair is redesigned with a view to reducing the generation of wood residues and making better use of the raw material. Life Cycle Assessment was carried out from the cradle to the grave for the initial chair and redesigned chair comparing environmental impacts and energy consumption.

The redesign proposal allowed a decrease in the generation of waste from 43.81% to 32.20%; reduction in wood consumption of 29.95% and decrease in energy consumption from 5 KWh to 3.23 KWh. Based on the results, the design parameters for the reduction of wood residues generated in the production of wooden furniture are proposed. The proposals have addressed parameters to reduce, facilitate, select and value the redesigned product modifications. To do this, a step-by-step approach is proposed based on a sequence of activities: product definition, manufacturing process, Cleaner Production, mass balance, Life Cycle Assessment, Ecodesign (solution proposals) and Life Cycle Assessment of the proposal. The implementation of design parameters, considering material characteristics, modulation of parts and redesign, as well as the identification of the most relevant sources of waste, through the application of Cleaner Production, allows the reduction of material and energy consumption. The potential of applying the Cleaner Production and Ecodesign parameters to reach micro and small wood furniture companies can be evidenced, helping to reduce waste generation.

A major problem for the oil production industry is the amount of water produced (PA) generated during the operation of its industrial processes, being considered the largest stream of effluents and has complex composition such as high salinity, suspended solids, chemical additives. , heavy metals, considered to be oil and grease (TOG) content and other contaminants. The TOG is a parameter that deserves attention, as regulatory agencies regulate the discarding of PA from this parameter. The present work aimed to evaluate the potential of the coalescence and adsorption process in the treatment of real oil produced water supplied by Petrobras, Pilar-AL Unit, using an integrated system composed of a horizontal bed coalescer in combination with a fixed bed of adsorption. The parameters evaluated in the coalescer were the flow velocity and the bed type. The materials evaluated to compose the coalescedor bed were: coconut fiber, considered a byproduct of the industry and the vegetable bushing (Luffa cylindrica), an easy material to be found in the Northeast region. The fixed bed column (adsorption process) used biochar and activated carbon produced from ouricuri (Syagrus coronata), a regional raw material. The biomasses used (coconut fiber, vegetable bushing and ouricuri, as well as biochar and activated charcoal) were characterized by the following techniques: humidity, thermogravimetric analysis, X-ray dispersive energy (EDX), X-ray diffraction and infrared by Fourier transform. Initially, the type of bed and the flow rate of the coalescing bed were evaluated: 40, 60 and 80 L / h, which corresponds, respectively, to superficial velocities 5,8; 8.7 and 11.5 m / h in relation to the diameter of the coalescer. The TOG at the coalescer inlet and outlet was evaluated and the oil and grease removal efficiency calculated. The coalescer pressure drop was also evaluated. Coconut fiber and 40 L / h flow rate showed higher efficiency, removing around 80% of TOG. Then, as mentioned earlier, coals were produced from ouricuri and activated with phosphoric acid, sulfuric acid and sodium hydroxide. The adsorptive capacity evaluation experiments were carried out in a finite bath system. The results showed that NaOH activated carbon has higher adsorptive capacity. Defined the best bed type and coalescer feed rate, plus the activated bed activated carbon type; Studies with the integrated system (coalescer and fixed bed column) could be initiated. The experimental design consisted of a complete factorial system 23 for the experimental runs in the integrated system, where the evaluated variables were: coal type (biochar and NaOH-activated carbon), mean particle diameter (0.149 - 0.3 mm and 0.3 - 0.5 mm) and fixed bed column flow rate (2.2 and 4.4 L / h). The best result was obtained with the experiment that used biochar, particle diameter between 0.149 - 0.3 mm and flow rate of 4.4 L / h, achieving a TOG removal of around 84%. The results showed that the integration of adsorption coalescence processes using biomass and biochar can be an alternative for the treatment of petroleum produced water, meeting the environmental requirements for disposal and reinjection.

Renewable energies have been occupying a larger portion of the world energy matrix due to a series of factors, primarily the environmental one. Although the technological development related to this type of energy is moving at a rapid pace, the adjustment between the renewable energy supply and demand is not always possible due to the inherent dependence on natural factors. To bridge this supply and demand adjustment one of the available alternatives is the large-scale energy storage. This paper aims to propose a methodology for the evaluation of energy resources and reserves in salt caves, using P2G (Power to Gas) and CAES (Compressor Air Energy Store) technologies. To meet this objective, bibliographic research on the proposed theme, document analysis (ordinances, resolutions, laws, among others), consultation with experts in the energy storage area, and a comparative analysis were used as methodological basis. Also, the proposed methodology was tested using real data obtained from the literature. As a result, two existing methodologies have been identified to be used as references: the Petroleum Resources Management System (PRMS) and the CO2 Storage Resources Management System (SRMS). As in the methodologies taken as reference, in the proposed methodology, a storage project is divided into two phases: sub-commercial, where the analyzes and calculations are made from information obtained in the literature; and commercial, where the analyzes and calculations are made according to information obtained from the actual implementation of the project. Three stages were established for the subcommercial projects: Total Possible Resource (R3), Total Probable Resource (R2) and Total Proved Resource (R1). Information from saline massifs in Portugal and the compressed air storage technology were used to exemplify the methodology used at this phase. The R3 volume was calculated with informations from Carriço Massif and it resulted in a volumetric value of 3,000,000 m3. The Diapiro Rio Maior, considering the geological and regulatory variables, was used as an example for the R2 calculation, and its final value was 321,951 m3, the equivalent to an energy potential of 4.3 GWh. Finally, the value of R1 was calculated by analyzing the type of gas used and the efficiency of the associated plant, obtaining a volumetric value of 95,619.45 m3. This value is equivalent to a total energy potential of 1.3 GWh, and a power of 326 MW for a 4h production and 162 MW for a 8h production. Such as for the sub-commercial phase, three stages were also established for projects classified as commercial: Total Possible Reserve (Re3), Total Probable Reserve (Re2) and Total Proved Reserve (Re1). In order to test the proposed methodology for the commercial phase, data from a rock salt mining company in the city of Maceió, state of Alagoas, was used. The Total Possible Reserve (Re3) was estimated at 11,046 m3 while the Total Proved Reserve (Re2) at 234,000 m3, which is equivalent to an energy potential of 4.3 GW. For the Total Proved Reserve (Re1) the value of 69,498 m3 was found, which is equivalent to an energy potential of 1.28 GWh, which when divided by a production in 4 hours or 8 hours provides a power of 320 MW and 160 MW respectively. The values found are close to those presented by plants operating commercially around the world, confirming the robustness of the proposed methodology and its adherence to the reality. As observed, the proposed methodology can be applied to real cases and the values found in this article point to the possibility of implantation of a CAES project in the studied mineral concession. In order to accomplish this, it is necessary to develop a real case study with the company data including all limiting aspects in the calculation of Re3, using the sonic profiling data to calculate Re2 and choosing the type of CAES technology to calculate Re1. It is also necessary to prepare an Technical and Economic Feasibility Study (TEFS) considering diverse types of power supply for the compression to be implemented through the CAES project.

Sustainability has become a competitive factor for organizations where studies on
sustainability assessment and optimization are a key requirement in the management of
organizations throughout their supply chain. In a more specific perspective there is a gap
regarding the models of evaluation and optimization of sustainability performance. Given
this context, this thesis aim to development of a model for evaluation and optimization
of organizational sustainability. This thesis was elaborated as a collection of articles.
The first paper is a study that is based on a systematic review, involving the most
renowned and prominent works of the scientific community, as well as an analysis of
quantitative approaches to assessment and optimization of organizational sustainability.
The second paper is a comparative analysis of the multi-attribute decision making
models The Preference Ranking Organization METHod for Enrichment of Evaluations
(PROMETHE), Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and
Technique For Order Preference by Similarity to Ideal Solution (TOPSIS), the goal
is to identify the most appropriate ranking method for model development. The third
paper is the combination of the multicriteria evaluation model, PROMETHEE, with
multiobjective optimization model. The fourth paper is the second combination of the
PROMETHEE multi-attribute model and the multi-objective priority programming model
for the evaluation and optimization of organizational sustainability performance. The
second, third and fourth articles are experimental case study applications. As a result,
a ranking of organizational sustainability was obtained through the years, combining
with optimization models to support decision making. The contribution of this work is
the structure of an applied and validated hybrid model that can be easily replicated in
other companies as the results guide decision making for organizational sustainability.

The organization of a mega event such as the Carnival of Salvador offers risks that deserve special attention in terms of its identification and control. Mainly because it gathers more than 500 thousand visitors, between Brazilians and foreigners. This research aims to perform the risk analysis of the Carnival of Salvador 2016, from the application of the tools: Scenario Analysis, APR, Risk Matrix, FTA and Bowtie. The research also intends to describe the results of the applied questionnaires and to discuss some relationships from the analysis of the multiple correspondences. This research is the result of a concern of a research group of the Department of Mechanical Engineering of UFBA in dynamic risks (GRODin), being used as references the standards of the Brazilian Association of Technical Standards - ABNT through NBR 31000: 2009_Risk Management and NBR ISSO / IEC 31010_Risk Assessment Techniques. Among the advantages of performing the risk assessment process is the identification of hazards in a preliminary phase, which saves time and expense in the eventual replanning or even during the course of the event. Following the identification of the risk scenarios, some recommendations are suggested, such as: increased surveillance in all areas for all processes and table simulations, with all the bodies involved with Carnival, with security protocol creations, such as emergency situations, materials to be used, that is, protocols that standardize and prepare processes and how people act in those situations.

The management of organizations with complex operational structures involves many critical factors that may contribute to the occurrence of undesirable events generating from a small degree of dissatisfaction to a life-threatening situation for system users. In this way, managers of these organizations need to be equipped with efficient management methods to deal with these fault occurrences in order to mitigate their root causes and prevent their recurrence, contributing to a more reliable and efficient system. In this sense, this work presents a method of integrated management of occurrences and makes use of Itaipava Arena Fonte Nova as an application environment. This work is justified due to the need for a more rational use of organizational resources and the obligation to develop processes with levels of safety and quality in line with current norms and standards. Thus, an integrated event database was constructed, a mathematical model of prioritization was developed and, finally, a systematization of the proposed method was elaborated as a flowchart. The results of applying the prioritization model in the years 2013, 2014 and 2015 converged with the traditional prioritization method only in the security dimension, something that was already expected. In the year 2013, no occurrence was classified as a priority. In the year of 2014 two occurrences were prioritized: 1) Precarious orientation and; and 2) Unprepared attendants of bars/ snack bars. In the year of 2015 five occurrences were prioritized: 1) Irregular sellers; 2) Conflicts between users; 3) Overcrowding of sectors/ aisle; 4) Queues in bar/ snack bar; and 5) Precarious internet access. Brainstorming sessions and an Ishikawa diagram were used to identify and present the root causes related to the prioritized occurrences. In the recommendation of corrective actions, specific documents for multipurpose arenas were used, in addition to international standards of the areas of safety and quality. Two scenarios were simulated in order to verify the behavior of the pr

Fault Tree Analysis (FTA) has been widely used since its inception, especially in the industrial environment (or in high severity or high risk applications, which have the legal obligation to develop risk analysis) for providing in-depth knowledge of the system/ equipment and its reliability. Although its application is still very restricted when it comes to activities with minor severity, there are already studies that recommend the use of this tool for other areas besides the industrial environment, such as service processes (tertiary sector). This work aims to propose an approach for the analysis of Fault Trees (FT) with a focus on improving their applicability to the tertiary sector. The main techniques of fault tree construction were evaluated and the approach developed here proposes a dynamic construction of FT and the expansion of the multidisciplinary team that participates in this construction, based on the concept of multi-stakeholders i n s e r t e d i n t h e c o l l a b o r a t i v e p a r a d i gm o f We b 2 . 0 . The n ew approach was used in a case study at the 2014 FIFA World Cup (governed by the fifth edition of the FIFA normative document) and has potential for cost reduction, or at least its dilution over time. In addition, it also offers the possibility of practicing insertions of more than one regulatory standard of the service in the FT, as well as the monitoring of the evolution of the normative documents and the identification of the scenario of regulation tendencies of the service in question, being constituted in an additional alternative and an improvement to the Service Tree Analysis (STA) method. In addition to the aforementioned case study, this paper also presents an evolutionary analysis of the normative documents within the same context of the case study. That is, the analysis of the evolution of the technical requirements of the FIFA World Cup was elaborated from the fault tree analysis. This evolutionary analysis used the five existing editions of the FIFA requirements and pointed out which items underwent major changes, which items ceased to exist and which new items were inserted. This evinces both the evolution that has occurred over time as it offers a scenario of regulatory tendencies for the next editions, and may also support future decision making for the managers of the arenas, in order to obtain a positive and beneficial legacy in the post-event. The proposed approach also presents potential benefits for the Dynamic Fault Tree Analysis (DFTA) and for analyzes that consider a great influence of human reliability.

Microalgae are considered a promising source of energy for the production of biofuels because they are fast growing, do not require arable land for their cultivation and do not contribute to global warming or the emission of greenhouse gases. In this context, the objective of the present work is to develop a methodology for the production of bioethanol from biomass of the microalga E. gracilis (species not yet studied). Some parameters were evaluated in order to increase the production of paramylon as a culture medium (mineral and lactate), methods of separation of biomass (centrifuge and rotavaporator) and stress with FeCl2. In addition, types of hydrolysis (acid and enzymatic) were evaluated aiming at increasing the production of bioethanol. The hydrolysis step was important for the production of reducing sugars. Dilute sulfuric acid (0.06% (v / v)) was used in the acid hydrolysis and it was performed in a vertical autoclave at 127 ° C and 10 minutes. The enzymatic hydrolysis was performed by Cellulase (50 mL / L) for 72 h. The hydrolyzed samples were fermented by Saccharomyces cerevisiae yeast and the bioethanol production was evaluated at different fermentation times (3h, 1 h and 30 minutes). Bioethanol was characterized and quantified by gas chromatography (GC-FID). Centrifugation method for biomass separation resulted in higher concentrations of reducing sugar. The fermentation time of 30 minutes generated higher concentrations of ethanol and the highest yield of the fermentation (50%) was obtained starting from a mixotrophic culture and enzymatic hydrolysis from an initial concentration of about 15 g/L of dry biomass. These results may become E. gracilis one potential feedstock for the production of bioethanol.

Modeling residential water consumption is an important step towards knowledge about users behavior and, later, for the proposition of realistic goals that lead to the conscious consumption. The information provided by the smart meters enabled the detection of the equipment triggered, through flow measurements in short time intervals. Thus, the objective of this project is to develop an algorithm to identify the use of devices, with both pattern classification, as well as identification and separation of simultaneous uses. The classifier was built based on k-nearest neighbor concept, including the evaluation of the similarity measure that best suited the data among DTW, EDR, ERP and LCSS. The measures adopted were sensitivity - which indicates the percentage of the total events correctly classified - and precision - which indicates the percentage of the data correctly assigned by the classifier. They were calculated based on number of events and volume consumed. The ERP measure was chosen as the one that reached the best performance measures values and that produced the smaller percentage of tie results. The sensitivity average, in terms of volume, for the toilet, shower and internal tap were 71.1%, 67.3% and 78.2% respectively, and for more than half of the residences, it was possible to achieve more than 70% detection between these devices. For external tap the performance measure value was below-expected with an average of 26.6%, mainly due to confusion with the internal tap. In terms of accuracy with regard to the number of events, the classifier achieved for the toilet, shower, external tap and internal tap average of respectively 72.2%, 51.1%, 59.0% and 88.4%; in some homes, the detection capacity for the external tap reached more than 90%. The algorithm of identification and separation of simultaneous uses was able to differentiate particular uses from simultaneous uses and realize separations, obtaining an average 83% of correct outcomes among all the residences. The integration of these sections was tested in one of the houses and 78% of the water flows were correctly matched. These results indicated that the proposed tool showed potential to be used, both because of the interesting results obtained and the fact that there was no intervention of the researcher throughout the process.

Currently, the intensity of routine work does not allow an analysis of best practices in energy efficiency and their need for adjustments.The identification of these best practices in energy efficiency depends on criteria and measurements resulting in their classification. Each practice causes individual energy loss which in the aggregate results in large losses. Looking to fill this gap, the present work aimed to elaborate a model to calculate the index of good practices in energy efficiency, pointing out its component parts and how they are structured.The study was based on bibliographical and empirical research, identifying the existing lack. In order to reach the objectives, a methodology was developed with seven steps. There were used two different methods to evaluate good practices, as mathematical support was used Solver Excel software and Fuzzy Logic toolbox, implemented in MATLAB. Preliminarily, two parts of good practices were established based on literature and empirical research with the interaction of specialists from the industries related to the operational part.The model was implemented to evaluate the good practices, using the Likert scale to assess the properties of its component parts, where the consistency of the results was verified, achieving 98.52% accuracy when comparing the results obtained by the Excel tabulator and the Fuzzy Inference System. Among the results achieved, the following can be mentioned: identification of the component parts of good practices, definition of the priority weights of these parts, properties of the component parts, and a mathematical equation for measuring the index of good practices in energy efficiency. All of these concepts and properties have resulted in a Model for Evaluating Good Practices.

With the pursuit of energy efficiency in automotive vehicles, taking into account the need to minimize the environmental impact of the use of these vehicles, recent efforts to improve fuel combustion control systems have become a prominent strategy in the automotive industry. The aim of this work is the development of models for prediction of the proportion of ethanol present in a fuel blend used in a flex vehicle equipped with a three-cylinder engine. The models are developed with the use of the information based on measurements made by the control system of a three-cylinder engine and a threedimensional accelerometer coupled to the engine. The experimental methodology applied for the signal acquisition from the operation of a three-cylinder engine, installed in a passenger vehicle, is described. The acquired signals were treated and used in models based on Multiple Linear Regression and Artificial Neural Networks for the prediction of the ethanol volume ratio on the fuel blend. The models proved to be efficient in predicting the proportion of ethanol in the fuel blend, presenting a better approximation between the predicted values and the actual values when compared with the data provided by the engine control system.

Besides the production control, the development of new technologies or the improvement of existing ones are some of the main reservoir engineering challenges, whose main objective is to increase oil recovery, especially when the primary recovery methods become unviable technical and economically. In this context, simulators are an important tool because they allow inferring the productive behavior of the reservoirs. In this work BOAST, a free simulator, black-oil, three-dimensional and three-phase, was investigated for a more comprehensive understanding of this tool and its applicability. A supplementary extended manual was developed based on the detailed study of this simulator, which can serve as a guide for its use or to incorporate improvements in the program code during future work. It is worth emphasizing this contribution of this work since the existing BOAST manuals are not very detailed. This work also presents in detail some case studies that exemplify the applicability of BOAST, such as: sensitivity analysis of PVT properties and input variables related to rock properties and production parameters in the reservoirs simulation; and technical evaluation of the advanced recovery method called water alternating gas injection (WAG). These studies also allowed a theoretical discussion of reservoir simulation features, for instance: efficiency, three-phase permeability, permeability hysteresis concepts and description of recovery methods such as WAG.

Quality of information (QI) was created by the Clean Technology Network (TECLIM). They created that to overcome the infeasibility of performing classical data reconciliation in water balances due to the lack of redundancy in measurement of the aqueous streams. The concept of QI is made empirically for each process, so that its associated uncertainty could impact the corresponding data reconciliation results. The main purpose of this dissertation is to propose an improvement in the reconciled water balance of the TECLIM methodology by considering the impact of the uncertainty of the QI in the uncertainties of the reconciled flows rate. These reconciled flows rate used in environmental performance indicators allow estimating the uncertainty of the indicator and guaranteeing better credit in decision making in water management. The contribution to robustness of the TECLIM methodology was assayed with the case study application in a methanol industrial plant. The company in study is located in Petrochemical Complex of Camaçari, Bahia. As a preliminary result, a specific QI scale was developed for the study plant and its use allowed the closure of the water balance, which it has 64% of its aqueous streams with little or no confidence in its source information. The application of the robust TECLIM methodology based on the preliminary results enabled to evaluate the uncertainty of the reconciled flows rate and to draw with better consistent the water profile of the methanol plant. There was identifying that the deaerator, the boiler and the cooling tower were the main water consumptions. Moreover, the more than half of the water losses in the plant came from the evaporation of the cooling tower. Two reconciled flows rate resulting from the robust TECLIM methodology application were used in the reformulation of an operational performance indicator about water make-up consumption in the methanol industrial plant. The uncertainty evaluation of this indicator verified its relevance in the proper analysis over the effective goals and actions necessary to manage the consumption. Targets of up 2% must not be imposed by the company’s environmental system because it is within the coverage interval of the indicator. Targets above 2% are going to not effectively meet the stipulated target because of the uncertainty margin. It will occur only if more effective actions and maneuvers happened in the process.

Climate change in the last decades from anthropogenic action has led to an increase in the volume of evidence related to climate change actions in the annual reports of the companies participating in the Carbon Disclosure Project (CDP). However, the evidence-determining factors related to actions in the face of climate change remain obscure given the complexity of the impacts of the climate change phenomenon and the diversified interests of stakeholders for information, which in turn are associated with the expectations of the society in which the company operates. The objective was to propose a model for measuring the level of evidence of actions to cope with climate change based on determinants identified in reports (mandatory and voluntary) and the opinion of experts and managers through which it was possible to meet specific objectives of work. In order to do so, we identified the 32 determinant factors pointed out by Brazilian specialists and managers, and their presence was investigated in 463 annual reports of 48 Brazilian companies participating in the CDP between 2014 and 2016 through the Nvivo® document analysis software. Finally, the data were submitted to a semi-structured interview with managers. It was presented the classification of the determinants of actions in the face of climate change, reflecting the companies' options to privilege, in their disclosure process, namely: pollution prevention, GHG emissions volume, environmental asset management, strategic climate change, environmental management system, field of activity, business strategy, level of regulation and company size. Based on this, it is possible to identify the most determinant factors as well as the correlation between them, the most important stage in the construction of the Index of Evidence of Actions in the face of Climate Change of CDP companies, Brazil (IEAMC-CDP). The IEAMC-CDP represents a mechanism capable of classifying the level of evidence of climate change actions for CDP Brazil companies, which is composed of factors that represented 71.52% of all references used in the annual reports during the period studied. The result of the application of the method inherent to the IEAMC-CDP in the available data of the sample presents the company América Latina Logística (ALL) as highlight in the period, and its structure allows the application in companies of diverse sizes, including those that are not part of the CDP. Knowing about the determining factors is still important to improve the decision on mitigation strategies and adaptation to climate change, but more importantly, how to disclose such information in order to direct the resources in the maintenance of the social contract (legitimization) through the most evident determining factors and captured by the IEAMCCDP, especially the companies with lower scores in the hierarchy scale presented in this research.

Agricultural and forestry production in Brazil stands out in relation to other countries due to
the country’s edaphoclimatic conditions, the use of degraded areas and the use of agricultural
and forestry technologies. However, the management of these resources causes
environmental impacts, mainly due to the indiscriminate use of synthetic fertilizers, fossil
fuels, water and electricity. Knowledge of the environmental performance of these
agricultural and environmental processes enables us to identify new material and product
routes to meet increasingly stringent environmental requirements, restricting the use of
natural resources and emissions to the environment. This thesis is organized into four
chapters, each with an independent introduction, development, references and appendices.
Chapter I presents a review addressing the main environmental effects of agricultural and
forestry production, focusing on CO2 emissions into the atmosphere. Chapter II in article
format is an excerpt from a publication in the Journal of Cleaner Production assessing the
environmental and economic performance of irrigated carrot production in the Brazilian
semiarid. Chapter III, also in article format, unpublished until the defense of this thesis, is a
study of the environmental and economic performance of short-cycle eucalyptus production,
including an analysis of an alternative forest production system integrated with farming and
livestock. Chapter IV presents the general considerations regarding the two studies. The
overall objective of this paper is to present a new analytical approach for the environmental
and economic assessment of agricultural and forestry systems. This approach integrate
Cleaner Production (CP) and Life Cycle Assessment (LCA) to provide more detailed crop
information of irrigated carrots and eucalyptus production, using data collected on site and
including a life cycle analysis. The use of CP and LCA is advantageous because it combines
complementary aspects of these two tools and they are open about the development process,
can be expand from new studies that add value and enhance the benefits of each method. The
combined use of both methods has proven feasible as LCA identifies the key environmental
impact points of the system under analysis, while CP supports practices that reduce costs and
the use of inputs such as water, energy, fertilizers, seeds and pesticides. Life Cycle Impact
Assessment was performed using the Reference Lifecycle Data System Method (ILCD,
2011), including data uncertainty. Potential environmental impacts of carrot cultivation are
related to the use of nitrogen fertilizers. It has also been found that water and electricity
consumed during irrigation are also wasted. CP measures provided a higher level of
compliance with the technical requirements for the system studied and proved to be more
economical and environmentally efficient than end of pipe practices. The main results for the
eucalyptus production systems, including a sensitivity analysis, showed that soil tillage, field
input emissions and timber harvesting were responsible for the largest impact contributions 

Considering the average input to the system, the implementation of a Crop-livestock-forestry
integration system would reduce the use of inputs and increase gross revenue compared to the
conventional production system. The complementary use of CP and LCA has shown that
good operating practices can reduce the potential environmental impacts and production costs
of the systems analyzed, supporting more sustainable production for the conditions analyzed.

Most plant species form mutual associations between certain soil fungi and their roots, and these associations are called mycorrhizae. As part of the research on Arbuscular Mycorrhizal Fungi (AMFs), it is important to detect the presence and estimation of the amount of spores of these fungi after extraction. The difficulty in counting these spores is due to the fact that it is still done manually, using a microscope (magnifying glass) and sometimes with a digital counter. Counting spores requires the expert’s ability to differentiate spores from other elements that remain after extraction, such as mineral particles and fragments of hyphae. This is because the portion of soil under analysis, even undergoing a mechanical cleaning process, remains with impurities in the sample under the microscope. These impurities can confuse the detection and subsequent counting of the spores, besides the difficulty of the expert to follow an order not to count repeated spores or to stop counting some. The detection and counting of AMF spores are important methods, for example, to control the application of inputs in a given area. Using these associations and with the prior knowledge of the present quantity of AMF, it is possible to define the appropriate quantities of inputs, ensuring that the plant is able to absorb them to the maximum, reducing waste. The automation of the AMF spore counting process provides reliability and agility in the results presented by the experts. The objective of this study is to propose and investigate the efficiency of an automatic counting method with the application of models with architectures based on Artificial Neural Network (ANN). The work evaluates the performance of a semiautomated counting system, based on the application of two models used as identifiers and classifiers of the images of the AMF spores. The Circular Hough Transform (CHT) is used as a preprocessing tool for the images to be classified by the ANNs. The results showed that the two models, based on neural networks, are characterized as good classifiers. Both models achieved high classification rates, when compared to the manual counting system, and can be applied in an automation system of the spore counting process of AMFs. As a way to benefit this process it is proposed the development of a software-based model that can automate it, exploring image processing techniques and artificial neural networks.

Biocide injections are often used in mature oil fields as well.
an attempt to control sulfate-reducing bacteria (BRS) and sulfide production
(acidification). Failure or unpredictable results of such practices have been associated with
increased metabolic resistance of BRS in situ. However, as concentrations
biocides and monitoring strategies are typically based on
the dynamic relationship between dilution and metabolic recovery is not tested
for such experiences. The BRS are responsible for the biological production of sulfide,
however, few inhibition tests are performed with mixed cultures grown on biofilm.
porous media reactor under conditions that mimic the dynamic equilibrium of a
oil reservoir. This type of test has advantages over experiments.
carried out in batches of test tubes in laboratories, since they offer the
opportunity to measure biofilm response in situ and in real time. To solve this
problem, this research aimed to develop an anaerobic biological system
in dynamic equilibrium, in relation to the consumption of organic substrates, to test and
quantify the effect of four new sulfetogenic inhibitory substances
(souring) and a known biocide within a dynamic system (bed bioreactor
fixed). The bioreactor was operated for 591 days in 72-hour batches. The results
showed that (BRS) has the ability to recover and re-produce sulfide in
a period that may vary from 15 to 60 days after injection of the tested biocide. The oil of
(NO) (1.5% v / v) and the biocide Dazomet, (DZ) (0.5% v / v) were the most efficient
controlling BRS activity. Oil (NO) was 1.2 times more efficient in controlling
BRS activity than Dazomet, which is a biocide commonly used in industry
of oil. The results suggest that NO and DZ biocides should be reapplied in the
system in the period before 60 and 48 days, respectively. Immiscible biocides seem
have a longer effect. Therefore, data indicate that consortium control
of BRS in dynamic equilibrium biofilm systems does not only depend on the
concentration of the applied substances, nor is it associated only with the toxicity of the
compounds. It also depends on their chemical characteristics and the frequency of
application. Immiscible biocides killed the cells, and controlled the rates of
BRS recovery.

Industrial effluents by their own composition can cause serious environmental damage.
Notwithstanding this fact, in Brazil there is no specific federal law on the treatment and final
disposal of industrial effluents, as is already the case with solid waste. The largest integrated
industrial complex in the Southern Hemisphere is located in the state of Bahia, however,
there is also no specific local law on this legal matter. This PhD thesis investigates the
regulations and federal legislation of the State of Bahia and the municipalities of Salvador
and Camaçari, regarding the treatment and final disposal of industrial effluents, as well as
the protection of bodies in the light of the concepts of cleaner production, industrial ecology
and environmental balance. The normative structure based on the activities of the Industrial
Development Committee of Camaçari/Bahia (COFIC), concerning the treatment and final
disposal of industrial effluents, and the supervision of the water balance of the industries are
evaluated. The role of the organization CETREL S. A. was also investigated, through
interviews with representatives and technical visits to CETREL. The regulation of the
protection of water bodies at a federal level in the State of Bahia was evaluated, including
the State Policy for the Administration of Environmental Resources and the State Policy for
Water Resources, as well as the correlation in the municipalities of Salvador and
Camaçari/BA. The qualitative methodology was applied, through the study of legislation,
bibliographical considerations, interviews and documentary analysis. Results show that a
considerable number of industries did not present reports related to the Water Resources
Management Program in the RTGSs of 2015 to 2017. This paper presents a legislative
proposal for the regulation of industrial effluents in Camaçari, regarding the future creation,
by the competent bodies, of a Municipal Policy of Industrial Effluents, which brings greater
security to the quality of life and to the environment of this unit of the Federation.

Coconut shells are characterized as the main solid co-products generated in the coconut derivative industry, contributing greatly to the amount of materials discarded in landfills. The State of Bahia is the largest producer of coconuts and co-products generated by coconut agroindustry in Brazil, with 98.087 tons/year. The thermal utilization of this biomass in the form of chips, for the generation of energy through gasification, can be an economically viable alternative and favorable to the environment. The objective of this work was to identify the thermal conversion potential of this biomass through thermogravimetric analysis (TG), thermogravimetric derivative analysis (DTG), differential thermal analysis (DTA), energy dispersive X-ray spectroscopy (EDX), proximate analysis, ultimate analysis, calorific value; To characterize the gas produced by the gasification from the stoichiometric equilibrium modeling and simulation of the process, and compare it with literature data. The simulation of the process was performed using the EES (Engineering Equation Solver) computational plataform. The following were obtained in the proximate analysis: moisture, 9.87 %; Ashes, 13.24 %; Volatiles, 68.49 % and fixed carbon, 8.78 %. In the ultimate analysis were obtained: C = 44.03 %; H = 4.85 %; N = 0.51 % and O = 50.61%. Through the EDX analysis it was verified a higher concentration of the minerals potassium and calcium. The values obtained for HHV (high heat value) and LHV (lower heat value) were 15.11 MJ/kg and 13.90 MJ/kg, respectively. From the results obtained, it can prove a possibility of using this product to obtain a combustible gas. It was obtained the gas composition, gas LHV, mass conversion efficiency (Em), cold efficiency (Ef) and hot efficiency (Eq): 24.45 % of H2, 27.86 % of CO, 12.41 % of CO2, 0.66 % of CH4 and 34.62 % of N2; LHV = 6.39 MJ/kg; Em = 51.03 %; Ef = 50.30 % e Eq = 22.13 %. Thus, comparing the results found with the data of the literature, it was verified that the developed model showed reasonable accuracy in the prediction of the characteristics of the gas.

Essential oils are volatile, natural, complex mixture of compounds with a high content of terpenes and they are known for their fragrance, medicinal properties or insect control effect. In addition, oils have low solubility in aqueous media. Citronella oil is rich in citronellal, geraniol and citronellol and it is recognized for its insect control effect. However, citronella oil is highly volatile and chemically unstable when exposed to both air and light. So, different approaches to improve its biological effect have involved micro or nanoencapsulation. In that context, encapsulation polymeric systems have shown a promising perspective towards cosmetic and pharmaceutical applications. Furthermore, they can be produced by in situ polymerization in a single step, facilitating the scale up. Polymethyl methacrylate (PMMA) was the polymer of choice based on its biomedical and pharmaceutical application, as well as biocompatibility and long-term stability. So, the aim of this work was to produce and characterize citronella oil incorporated into PMMA nanoparticles produced by miniemulsion in situ polymerization. The results showed that it is possible to obtain stable latex with nanoparticles on a nanometric size range, between 70 and 375nm. There is viability in the encapsulation of essential oil of citronella by getting different efficiency values depend on the concentration of oil (2,5 a 15% w/w), was evidence that the bioactive no interacted with the polymeric matrix, reducing the possibility of loss of insect repellent activity. Nanoparticles produced were embedded in cosmetic O/W type emulsion that remained stable during accelerated stability tests. Thus, this study showed promising results for cosmetic applications of citronella oil encapsulated.

Polymeric systems, whether reactional or no reactional, are usually quite complex due to the very structure of the chains of their molecules and the existence of various interactions between them. The thermodynamic approach of these systems is fundamental for the equipment sizing, definition of operational conditions and optimization of processes. Some of these issues can be addressed in the investigation of the High Pressure Polyethylene process (HPPE) which low density polyethylene (LDPE) and poly [(ethylene) -co- (vinyl acetate)] (EVA) are produced. Although it is a relatively simple process, it is composed of a series of stages where the phenomena present can be well described by the thermodynamic laws. In this sense, this thesis aims to thermodynamically model some phenomena present in the reaction and separation stages of the HPPE process. It is investigated the liquid-liquid equilibrium at high pressure present in the reactor, properties of the LDPE/ethylene and EVA/ethylene/vinyl acetate mixtures when undergoing isenthalpic decompression, as well as the liquid-vapor equilibrium present in high and low pressure flash separators. For the modeling of the phase equilibria investigated in this work, it is used the equation of state PC-SAFT (Perturbed-Chain Statistical Associating Fluid Theory), which has better performed than its predecessors. The validation of the models is done by adjusting the binary interaction parameter kij of the PC-SAFT model, using experimental data and industrial data, according to availability. This work is organized into ten chapters and four appendices, structured in such a way as to allow independent reading of each one.

The ethene polymerization in solution uses significant amount of solvent. Due to economic and environmental issues, this solvent is recovered in a distillation train consisting of three columns. The operational flexibility of the reactor brings challenges to the solvent recovery section, especially to the first column which has to undergo frequent operational changes as flow and feed stream composition. Just the knowledge of operators and engineers are not enough to maximize the profit while keeping the desired product quality. Strategies based on modeling and optimization are, then, suggested. The goal of this dissertation is to model this distillation train and to determine the operational conditions that maximize the operational profit, satisfying the processes constraints. The columns were model in PRO/II, commercial software by Invensys. The process data were treated and the flow values were reconciled. The model was validated for different operational conditions with plant data, ensuring thereby, the elaboration of a reliable model, which is representative of the process. A sensibility analysis was performed to investigate the process behavior and to determinate the degrees of freedom to the optimization. This step was performed in ROMeo (Rigorous On-line Modeling and equation-based optimization), commercial software that allows the importation of the model from PRO/II. The results indicate that it is possible to increase the operational profit, taking into account each constraint, tolerance and limits of the process.

The environmental impacts associated with the use of fossil fuels, rising prices, potential limitations on supply and concerns about regional and national security are driving the development and use of biomass for bioenergy, biofuels and bioproducts. However, the use of biomass does not necessarily imply that its production, conversion and use are energy efficient. To operationalize energy efficiency ratings in Biomass, it is crucial to identify critical criteria, but keeping the number and measuring the acceptable level, as well as his clear understanding through the employment indicators. The selection of these indicators may vary according to the specific application of the industrial sector to analyze and the geographic region where they work and are focused. In this context, this research aims to evaluate energy efficiency in biofuel production sector industries in Bahia. Indicators of Energy for Sustainable Development (EISD) and the Global Association of Sustainability Indicators for Bioenergy (GBEP) were applied. It was found that the production of bioethanol has unfavorable values in 86% of the indicators, positive values in 40% of models of combined indicators, an average energy efficiency of 68%, and an increase between the years 2012 and 2013 negative when compared to the values of Brazil and positive when compared to the state of São Paulo. Biodiesel has unfavorable values in 60% of the indicators, positive values in 80% of combined indicators of models and an average energy efficiency of 91%, but this biofuel for lack of disaggregated data was not possible developments of the year 2012-2013. In addition, it was shown that the indicators can be supplemented with qualitative aspects through open questions and check on issues related to the identification of potential problems in the energy area, labor quality, identification of impacts in the region in which it is installed plant and the identification of possible impacts independently of the distribution and direct sales to end-market demand .By these questions, it was found that the biodiesel industry has improved in the current production and has implemented improvement projects in energy efficiency as well as making a positive contribution to rural economies where it operates the plant. With getting data through disaggregated models was able to play a certain reality more reliably and also been found that the indicators of the tools most used the ICE indicators are complementary. The results provide a basis for future discussions to develop energy efficiency ratings on systems and projects related to bioenergy and development assessments in individual bioenergy projects within their context and geographic scale.

Fault Detection, Diagnosis and Correction Systems (FDDC) applied to industrial systems are becoming increasingly important due to the growing demand for reliable, efficient and automated processes. The natural gas processing industry has gained increased attention due to its growing importance in the Brazilian and wide-world energy sector. So, ensuring products specification, increasing plant safety and reliability and reducing processing costs are some of the key benefits sought by the industry with the implementation of FDDC systems. Therefore, the main objective of this work is the development of a FDDC system for a deethanizer column of a natural gas processing plant which is capable of real time monitoring and, in addition to the steps of detection and diagnosis, performing also the step of automatically correction. A mathematical model of the column was built in process simulator EMSO and it was used to generate failure data. The FDDC system was implemented using MATLAB/Simulink for failures in the sensor of the reboiler temperature control loop. First the system was developed with a simple algorithm with decision logic structure and after a neural network trained with data provided by the column dynamic model then was used. The interconnection between the FDDC system (MATLAB/Simulink) with the column (EMSO) was carried through the EMSO/Simulink interface communication available in EMSO. In both cases the developed system was able to detect all faults and perform an efficient corrective action, avoiding unit performance loss and showing how a suitable FDDC system can promote the benefits listed above.