Student Number : 9611112G - PhD thesis - School of Chemical and Metallurgical Engineering - Faculty of Engineering and the Built Environment / Attainable Region analysis is a chemical process synthesis technique that enables a design engineer to find process unit configurations that can be used to identify all possible outputs, by considering only the given feed specifications and permitted fundamental processes. The mathematical complexity of the attainable regions theory has so far been a major drawback in the implementation of this powerful technique into standard process design tools. In the past five years researchers focused on developing systematic methods to automate the procedure of identifying the set of all possible outputs termed the Attainable Regions. This work contributes to the development of systematic numerical formulations for attainable region analysis. By considering combinations of fundamental processes of chemical reaction, bulk mixing and heat transfer, two numerical formulations are proposed as systematic techniques for automation of identifying optimal process units networks using the attainable region analysis. The first formulation named the recursive convex control policy (RCC) algorithm uses the necessary requirement for convexity to approximate optimal combinations of fundamental processes that outline the shape of the boundary of the attainable regions. The recursive convex control policy forms the major content of this work and several case studies including those of industrial significance are used to demonstrate the efficiency of this technique. The ease of application and fast computational run-time are shown by assembling the RCC into a user interfaced computer application contained in a compact disk accompanying this thesis. The RCC algorithm enables identifying solutions for higher dimensional and complex industrial case studies that were previously perceived impractical to solve. The second numerical formulation uses singular optimal control techniques to identify optimal combinations of fundamental processes. This formulation also serves as a guarantee that the attainable region analysis conforms to Pontryagin’s maximum principle. This was shown by the solutions obtained using the RCC algorithm being consistent with those obtained by singular optimal control techniques.

Goal-setting is indispensable for effective healthcare management. Yet, literature evidence suggests many organisations worldwide do not know how to formulate ‘SMART’ goals. Evidence of how existing theories work in practice is scarce, and the practices in low-income countries are unknown. Therefore, this research explored how leprosy project goals were formulated to describe the theoretical practice framework of The Leprosy Mission Nigeria (TLMN). Using a case-study design, ten managers were interviewed individually concerning their goal-setting knowledge, experience and perspective; and documented goals of six projects were reviewed. A five-step constructionist thematic data analysis generated eleven theoretical frameworks from the concepts of the emergent core themes of ‘stakeholders’, ‘strategies’ and ‘statements.’ Further theorisation reduced them to one general framework. This revealed TLMN’s goal-setting practice as a four-stage centre-led, top-down, beneficiary-focused and problem-based process. The stages were national preparation, baseline needs-survey, centralised goal formulation and nationalised planning. The outcome was the formulation of assigned, ‘non SMART’ objective statements, which are then used for planning projects. Other theoretical models constructed included a Goal Effects Cycle, ‘SMARTA’ goal attributes and hierarchical criteria for differentiating goal-types. A theory developed from TLMN goal-setting postulates that: ‘Assigned non SMART goal formulation directly results from centralised goal-setting practice and is the predictor of unrealistic project planning.’ Therefore, I propose that goal statements will be ‘SMARTA’ and plans, more realistic and relevant if goal setting is done collaboratively by all stakeholders at all stages of the process. Also, ‘Change-Beneficiary-Indicator-Target-Timeframe’ and ‘Change- Beneficiary-Location-Timeframe’ frameworks are recommended as templates for writing SMART objectives and aims respectively.

Master of Regional and Community Planning / Department of Landscape Architecture/Regional and Community Planning / Larry L. Lawhon / This report examines the Town of Frisco, Colorado development process utilized to implement an attainable housing development within a resort style community. This report begins with the review of historic trends in affordable housing initiatives in American culture that has led to the importance of creating a diverse housing stock. The report was conducted by review of articles, government records, private and public reports, and research on the housing demand and analysis in the regional area. This report was conducted to provide resort style communities, similar to the Town of Frisco, a clear process of implementing an attainable housing development through the use of private/public partnerships. Frisco’s private/public partnership with the development team of Ten Mile Partners serves as a plausible process a community can undertake to increase a community’s housing stock diversity and affordability for long term residents.

The availability of kinetic data for the oxidative dehydrogenation (ODH) of n-butane from Téllez et al. (1999a and 1999b) and Assabumrungrat et al. (2002) presented an opportunity to submit a chemical process of industrial significance to Attainable Region (AR) analysis. The process thermodynamics for the ODH of n-butane and 1-butene have been reviewed. The addition of oxygen in less than the stoichiometric ratios was found to be essential to prevent deep oxidation of hydrocarbon products {Milne et al. (2004 and 2006c)}. The AR concept has been used to determine the maximum product yields from the ODH of n-butane and 1-butene under two control régimes, one where the partial pressure of oxygen along the length of the reactor was maintained at a constant level and the second where the oxygen partial pressure was allowed to wane. Theoretical maxima under the first régime were associated with very large and impractical residence times. The Recursive Convex Control policy {Seodigeng (2006)} and the second régime were applied to confirm these maxima {Milne et al. (2008)}. Lower and more practical residence times ensued. A differential side-stream reactor was the preferred reactor configuration as was postulated by Feinberg (2000a). Abstract A.D. Milne Page 4 of 430 The maximum yield of hydrocarbon product, the associated residence time and the required reactor configuration as functions of oxygen partial pressure were investigated for the series combinations of an inert porous membrane reactor and a fixed-bed reactor. The range of oxygen partial pressures was from 85 kPa to 0.25 kPa. The geometric profile for hydrocarbon reactant and product influences the residence times for the series reactors. The concept of a residence time ratio is introduced to identify the operating circumstances under which it becomes advantageous to select an inert membrane reactor in preference to a continuously stirred tank reactor and vice versa from the perspective of minimising the overall residence time for a reaction {Milne et al. (2006b)}. A two-dimensional graphical analytical technique is advocated to examine and balance the interplay between feed conditions, required product yields and residence times in the design of a reactor {Milne et al. (2006a)}.. A simple graphical technique is demonstrated to identify the point in a reaction at which the selectivity of the feed relative to a product is a maximum {Milne et al. (2006a)}. Literature Cited Assabumrungrat, S. Rienchalanusarn, T. Praserthdam, P. and Goto, S. (2002) Theoretical study of the application of porous membrane reactor to Abstract A.D. Milne Page 5 of 430 oxidative dehydrogenation of n-butane, Chemical Engineering Journal, vol. 85, pp. 69-79. Feinberg, M. (2000a) Optimal reactor design from a geometric viewpoint – Part II. Critical side stream reactors, Chemical Engineering Science, vol. 55, pp. 2455-2479. Milne, D., Glasser, D., Hildebrandt, D., Hausberger, B., (2004), Application of the Attainable Region Concept to the Oxidative Dehydrogenation of 1- Butene in Inert Porous Membrane Reactors, Industrial and. Engineering Chemistry Research, vol. 43, pp. 1827-1831 with corrections subsequently published in Industrial and Engineering Chemistry Research, vol. 43, p. 7208. Milne, D., Glasser, D., Hildebrandt, D., Hausberger, B., (2006a), Graphical Technique for Assessing a Reactor’s Characteristics, Chemical Engineering Progress, vol. 102, no. 3, pp. 46-51. Milne, D., Glasser, D., Hildebrandt, D., Hausberger, B., (2006b), Reactor Selection : Plug Flow or Continuously Stirred Tank?, Chemical Engineering Progress. vol. 102, no. 4, pp. 34-37. Milne, D., Glasser, D., Hildebrandt, D., Hausberger, B., (2006c), The Oxidative Dehydrogenation of n-Butane in a Fixed Bed Reactor and in an Inert Porous Membrane Reactor - Maximising the Production of Butenes and Butadiene, Industrial and Engineering Chemistry Research vol. 45, pp. 2661-2671. Abstract A.D. Milne Page 6 of 430 Milne, D., Seodigeng, T., Glasser, D., Hildebrandt, D., Hausberger, B., (2008), The Application of the Recursive Convex Control (RCC) policy to the Oxidative Dehydrogenation of n-Butane and 1-Butene, Industrial and Engineering Chemistry Research, (submitted for publication). Seodigeng, T.G. (2006), Numerical Formulations for Attainable Region Analysis, Ph.D. thesis, University of the Witwatersrand, Johannesburg, South Africa. Téllez, C. Menéndez, M. Santamaría, J. (1999a) Kinetic study of the oxidative dehydrogenation of butane on V/MgO catalysts, Journal of Catalysis, vol. 183, pp. 210-221. Téllez, C. Menéndez, M. Santamaría, J. (1999b) Simulation of an inert membrane reactor for the oxidative dehydrogenation of butane, Chemical Engineering Science, vol. 54, pp. 2917-2925. __________________________________

ABSTRACT This work applies the concepts of the attainable region for process synthesis in comminution. The attainable region analysis has been successfully applied for process synthesis of reactor networks. The Attainable Region is defined as the set of all possible output states for a constrained or unconstrained system of fundamental processes (Horn, 1964). A basic procedure for constructing the attainable region for the fundamental processes of reaction and mixing has been postulated in reaction engineering (Glasser et al., 1987). This procedure has been followed in this work to construct the candidate attainable region for size reduction processes as found in a size reduction environment. A population balance model has been used to characterise the evolution of particle size distributions from a comminution event. Herbst and Fuerstenau (1973) postulated the dependency of grinding on the specific energy. A specific energy dependent population balance model was used for the theoretical simulations and for the fitting of experimental data. A new method of presenting particle size distributions as points in the Euclidian space was postulated in place of the traditional cumulative distribution. This allows successive product particle size distributions to be connected forming a trajectory over which the objective function can be evaluated. The curve connects products from successive batch grinding stages forming a pseudo-continuous process. Breakage, mixing and classification were identified as the fundamental processes of interest for comminution. Agglomeration was not considered in any of the examples. Mathematical models were used to describe each fundamental process, i.e. breakage, mixing and classification, and an The application of the attainable region analysis in comminution Abstract algorithm developed that could calculate the evolution of product particle size distributions. A convex candidate attainable region was found from which process synthesis and optimisation solutions could be drawn in two dimensional Euclidian space. As required from Attainable Region Theory, the interior of the bounded region is filled by trajectories of higher energy requirements or mixing between two boundary optimal points. Experimental validation of the proposed application of the attainable region analysis results in comminution was performed. Mono-sized feed particles were broken in a laboratory ball mill and the products were successfully fitted using a population balance model. It was shown that the breakage process trajectories were convex and they follow first order grinding kinetics at long grind times. The candidate attainable region was determined for an objective function to maximise the mass fraction in the median size class 2. It was proved that the same specific energy input produces identical products. The kinematic and loading conditions are supposed to be chosen as a subsequent event after the required specific energy is identified. Finally the fundamental process of classification was added to the system of breakage and mixing. The attainable regions analysis affords the opportunity to quantify exactly the reduction in energy consumption due to classification in a comminution circuit, thus giving optimal targets. Classification showed the potential to extend the candidate attainable region for a fixed specific energy input. The boundary of the attainable region is interpreted as pieces of equipment and optimum process conditions. This solves both the original process synthesis and successive optimisation problems.

O amendoim (Arachis hypogaea L.) é originário da América do Sul e foi amplamente disseminado pelo mundo, provavelmente por causa do seu sabor agradável e valor nutritivo. A cultura do amendoim é uma alternativa em sistema de rotação de culturas em áreas de cana-de-açúcar no momento da reforma dos canaviais, sendo esta a razão pela qual o Estado de São Paulo, principal produtor de cana, seja também o principal produtor brasileiro de amendoim. A aplicação do conceito da eficiência de produção agrícola para avaliação da cultura do amendoim pode fundamentar análises estratégicas para o setor. Uma das ferramentas usadas para este tipo de aplicação são os modelos baseados em processos. Dentre os modelos de crescimento para a cultura do amendoim já existente, destaca-se o incluído no sistema computacional DSSAT, denominado CROPGRO, que tem sido bastante aplicado em todo o mundo por pesquisadores da área. O desenvolvimento de modelos próprios por pesquisadores intensifica o processo de aprendizado e auxilia na redução de incertezas. O objetivo deste trabalho foi gerar conhecimento sobre a cultura do amendoim quanto a necessidade hídrica, conciliado ao desenvolvimento e calibração de modelos de simulação para quantificação da eficiência de produção agrícola nas principais regiões produtoras do Estado de São Paulo. A calibração do modelo CROPGRO-Peanut foi eficiente em simular a fenologia, para as variáveis vegetativas o índice d de Wilmott foi satisfatório para IAF (0,88 a 0,90), N° de folhas (0,58 a 0,85), AF específica (0,82 a 0,98), massa vegetativa (0,94 a 0,98) conforme a reposição hídrica aplicada, com valores de r2 acima de 0,65. Quanto as variáveis produtivas, embora os índices d e r2 foram satisfatórios, a EF foi baixa para ambos os tratamentos. Já o Simulador agronômico simplificado para Arachis hypogaea (SASAH), modelo inicialmente proposto neste trabalho pode ser considerando ainda em fase de construção e necessita de ajustes adicionais em seus algoritmos, não sendo utilizado na tese para simulação da produção potencial e atingível do amendoim. A eficiência média da produção no estado de São Paulo é de 52%, variando entre 33% em Ribeirão Preto até 72% em Marília. / Peanut (Arachis hypogaea L.) originates from South America and was widely disseminated throughout the world, probably because of its pleasant taste and nutritional value. The peanut crop is an alternative in a system of crop rotation in areas of sugarcane at the time of sugarcane reform, which is why the State of São Paulo, the main producer of sugarcane, is also the main producer Brazilian peanut. The application of the concept of agricultural production efficiency to evaluate the peanut crop can support strategic analysis for the sector. One of the tools used for this type of application is process-based models. Among the growth models for the existing peanut crop, the one included in the DSSAT computer system, called CROPGRO, has been widely applied by researchers in the area. The development of own models by researchers intensifies the learning process and helps reduce uncertainty. The goal of this work was to generate knowledge about the peanut crop as the water requirement, the development and calibration of simulation models to quantify the agricultural production efficiency in the main producing regions of the São Paulo State. The calibration of the CROPGRO-Peanut model was efficient in simulate the phenology, for the vegetative variables the Wilmott index was satisfactory for LAI (0.88 to 0.90), N° of leaves (0.58 to 0.85), Specific AF (0.82 to 0.98), vegetative mass (0.94 to 0.98) according to the applied water replacement, with r2 values above 0.65. Regarding the productive variables, although the indices d and r2 were satisfactory, the EF was low for both treatments. The simplified agronomic simulator for Arachis hypogaea (SASAH), a model initially proposed in this work, can be considered still in the construction phase and requires additional adjustments in its algorithms, and it is not used in the thesis to simulate the potential and attainable yield of peanuts. The average efficiency of production in the state of São Paulo is 52%, ranging from 33% in Ribeirão Preto to 72% in Marília.

A utilização de controladores preditivos multivariáveis na indústria de processos cresceu significativamente nos últimos anos principalmente devido à versatilidade e a confiabilidade que essa ferramenta proporciona em termos de controle avançado. No entanto, aspectos relacionados à aplicação prática do que vem sendo desenvolvido no meio acadêmico possui pouca difusão na indústria devido às configurações clássicas adotadas, como sistemas quadrados (com o mesmo número de variáveis controladas e manipuladas), modelos lineares, utilização de setpoint e etc. diferindo daquilo que está disponível e é amplamente utilizado industrialmente: sistemas não-quadrados (geralmente com mais variáveis controladas do que manipuladas), modelos não-lineares e utilização de soft-constraints. Esse trabalho propõe uma metodologia para ajuste dos parâmetros presentes em um controlador preditivo, atento à variedade de algoritmos presentes na indústria de processos. Essa metodologia se baseia na obtenção do melhor desempenho alcançável para cada cenário de um modelo global do processo, atendendo as restrições de Número de Desempenho Robusto relativo (rRPN), Máxima Sensibilidade e restrições nas ações de controle. Baseado em um desempenho que é alcançável, o modelo linear global é escalonado (assim como a planta não-linear) e os pesos que levam o sistema para a melhor condição operacional são estimados. Essa técnica abrange controladores operando em faixas e/ou setpoint e configurações não-quadradas, i.e., com mais variáveis controladas do que manipuladas. A abordagem proposta foi testada em uma planta de quatro tanques esféricos com aquecimento apresentando resultados coerentes, corroborando seu potencial de aplicação industrial. / Due to their versatility and reliability, Model Predictive Controllers (MPCs) are the standard solution for advanced process control in the process industry. However, there is a gap between the academic developments and the actual industrial applications, since the most academic studies focus on systems working with set-points and same number of manipulated and controlled variables, whereas the industrial application cope with non-squared configuration usually with several controlled variables in ranging and a reduced number of manipulated variables. This work proposes a tuning methodology for the countable parameters presents in a typical industrial predictive controller, considering the variety of the algorithms presents commercially in the process industry. This methodology is based on the estimation of the best attainable performance for each scenario of the global model of the process, constrained by the relative Robust Performance Number (rRPN), Maximal Sensitivity and restrictions in the control actions. Based on a performance that is attainable, the linear global model is scaled (and the non-linear) and the weights that lead the system to the best operational condition are estimated. This technique covers controllers operating in zones of control and/or set-point tracking and non-square configurations, i.e., with more controlled variables than manipulated. The proposed approach was tested in a Quadruple-Spherical tanks heating system presenting coherent results indicating its potential for industrial applications.

A utilização de controladores preditivos multivariáveis na indústria de processos cresceu significativamente nos últimos anos principalmente devido à versatilidade e a confiabilidade que essa ferramenta proporciona em termos de controle avançado. No entanto, aspectos relacionados à aplicação prática do que vem sendo desenvolvido no meio acadêmico possui pouca difusão na indústria devido às configurações clássicas adotadas, como sistemas quadrados (com o mesmo número de variáveis controladas e manipuladas), modelos lineares, utilização de setpoint e etc. diferindo daquilo que está disponível e é amplamente utilizado industrialmente: sistemas não-quadrados (geralmente com mais variáveis controladas do que manipuladas), modelos não-lineares e utilização de soft-constraints. Esse trabalho propõe uma metodologia para ajuste dos parâmetros presentes em um controlador preditivo, atento à variedade de algoritmos presentes na indústria de processos. Essa metodologia se baseia na obtenção do melhor desempenho alcançável para cada cenário de um modelo global do processo, atendendo as restrições de Número de Desempenho Robusto relativo (rRPN), Máxima Sensibilidade e restrições nas ações de controle. Baseado em um desempenho que é alcançável, o modelo linear global é escalonado (assim como a planta não-linear) e os pesos que levam o sistema para a melhor condição operacional são estimados. Essa técnica abrange controladores operando em faixas e/ou setpoint e configurações não-quadradas, i.e., com mais variáveis controladas do que manipuladas. A abordagem proposta foi testada em uma planta de quatro tanques esféricos com aquecimento apresentando resultados coerentes, corroborando seu potencial de aplicação industrial. / Due to their versatility and reliability, Model Predictive Controllers (MPCs) are the standard solution for advanced process control in the process industry. However, there is a gap between the academic developments and the actual industrial applications, since the most academic studies focus on systems working with set-points and same number of manipulated and controlled variables, whereas the industrial application cope with non-squared configuration usually with several controlled variables in ranging and a reduced number of manipulated variables. This work proposes a tuning methodology for the countable parameters presents in a typical industrial predictive controller, considering the variety of the algorithms presents commercially in the process industry. This methodology is based on the estimation of the best attainable performance for each scenario of the global model of the process, constrained by the relative Robust Performance Number (rRPN), Maximal Sensitivity and restrictions in the control actions. Based on a performance that is attainable, the linear global model is scaled (and the non-linear) and the weights that lead the system to the best operational condition are estimated. This technique covers controllers operating in zones of control and/or set-point tracking and non-square configurations, i.e., with more controlled variables than manipulated. The proposed approach was tested in a Quadruple-Spherical tanks heating system presenting coherent results indicating its potential for industrial applications.

A utilização de controladores preditivos multivariáveis na indústria de processos cresceu significativamente nos últimos anos principalmente devido à versatilidade e a confiabilidade que essa ferramenta proporciona em termos de controle avançado. No entanto, aspectos relacionados à aplicação prática do que vem sendo desenvolvido no meio acadêmico possui pouca difusão na indústria devido às configurações clássicas adotadas, como sistemas quadrados (com o mesmo número de variáveis controladas e manipuladas), modelos lineares, utilização de setpoint e etc. diferindo daquilo que está disponível e é amplamente utilizado industrialmente: sistemas não-quadrados (geralmente com mais variáveis controladas do que manipuladas), modelos não-lineares e utilização de soft-constraints. Esse trabalho propõe uma metodologia para ajuste dos parâmetros presentes em um controlador preditivo, atento à variedade de algoritmos presentes na indústria de processos. Essa metodologia se baseia na obtenção do melhor desempenho alcançável para cada cenário de um modelo global do processo, atendendo as restrições de Número de Desempenho Robusto relativo (rRPN), Máxima Sensibilidade e restrições nas ações de controle. Baseado em um desempenho que é alcançável, o modelo linear global é escalonado (assim como a planta não-linear) e os pesos que levam o sistema para a melhor condição operacional são estimados. Essa técnica abrange controladores operando em faixas e/ou setpoint e configurações não-quadradas, i.e., com mais variáveis controladas do que manipuladas. A abordagem proposta foi testada em uma planta de quatro tanques esféricos com aquecimento apresentando resultados coerentes, corroborando seu potencial de aplicação industrial. / Due to their versatility and reliability, Model Predictive Controllers (MPCs) are the standard solution for advanced process control in the process industry. However, there is a gap between the academic developments and the actual industrial applications, since the most academic studies focus on systems working with set-points and same number of manipulated and controlled variables, whereas the industrial application cope with non-squared configuration usually with several controlled variables in ranging and a reduced number of manipulated variables. This work proposes a tuning methodology for the countable parameters presents in a typical industrial predictive controller, considering the variety of the algorithms presents commercially in the process industry. This methodology is based on the estimation of the best attainable performance for each scenario of the global model of the process, constrained by the relative Robust Performance Number (rRPN), Maximal Sensitivity and restrictions in the control actions. Based on a performance that is attainable, the linear global model is scaled (and the non-linear) and the weights that lead the system to the best operational condition are estimated. This technique covers controllers operating in zones of control and/or set-point tracking and non-square configurations, i.e., with more controlled variables than manipulated. The proposed approach was tested in a Quadruple-Spherical tanks heating system presenting coherent results indicating its potential for industrial applications.

O amendoim (Arachis hypogaea L.) é originário da América do Sul e foi amplamente disseminado pelo mundo, provavelmente por causa do seu sabor agradável e valor nutritivo. A cultura do amendoim é uma alternativa em sistema de rotação de culturas em áreas de cana-de-açúcar no momento da reforma dos canaviais, sendo esta a razão pela qual o Estado de São Paulo, principal produtor de cana, seja também o principal produtor brasileiro de amendoim. A aplicação do conceito da eficiência de produção agrícola para avaliação da cultura do amendoim pode fundamentar análises estratégicas para o setor. Uma das ferramentas usadas para este tipo de aplicação são os modelos baseados em processos. Dentre os modelos de crescimento para a cultura do amendoim já existente, destaca-se o incluído no sistema computacional DSSAT, denominado CROPGRO, que tem sido bastante aplicado em todo o mundo por pesquisadores da área. O desenvolvimento de modelos próprios por pesquisadores intensifica o processo de aprendizado e auxilia na redução de incertezas. O objetivo deste trabalho foi gerar conhecimento sobre a cultura do amendoim quanto a necessidade hídrica, conciliado ao desenvolvimento e calibração de modelos de simulação para quantificação da eficiência de produção agrícola nas principais regiões produtoras do Estado de São Paulo. A calibração do modelo CROPGRO-Peanut foi eficiente em simular a fenologia, para as variáveis vegetativas o índice d de Wilmott foi satisfatório para IAF (0,88 a 0,90), N° de folhas (0,58 a 0,85), AF específica (0,82 a 0,98), massa vegetativa (0,94 a 0,98) conforme a reposição hídrica aplicada, com valores de r2 acima de 0,65. Quanto as variáveis produtivas, embora os índices d e r2 foram satisfatórios, a EF foi baixa para ambos os tratamentos. Já o Simulador agronômico simplificado para Arachis hypogaea (SASAH), modelo inicialmente proposto neste trabalho pode ser considerando ainda em fase de construção e necessita de ajustes adicionais em seus algoritmos, não sendo utilizado na tese para simulação da produção potencial e atingível do amendoim. A eficiência média da produção no estado de São Paulo é de 52%, variando entre 33% em Ribeirão Preto até 72% em Marília. / Peanut (Arachis hypogaea L.) originates from South America and was widely disseminated throughout the world, probably because of its pleasant taste and nutritional value. The peanut crop is an alternative in a system of crop rotation in areas of sugarcane at the time of sugarcane reform, which is why the State of São Paulo, the main producer of sugarcane, is also the main producer Brazilian peanut. The application of the concept of agricultural production efficiency to evaluate the peanut crop can support strategic analysis for the sector. One of the tools used for this type of application is process-based models. Among the growth models for the existing peanut crop, the one included in the DSSAT computer system, called CROPGRO, has been widely applied by researchers in the area. The development of own models by researchers intensifies the learning process and helps reduce uncertainty. The goal of this work was to generate knowledge about the peanut crop as the water requirement, the development and calibration of simulation models to quantify the agricultural production efficiency in the main producing regions of the São Paulo State. The calibration of the CROPGRO-Peanut model was efficient in simulate the phenology, for the vegetative variables the Wilmott index was satisfactory for LAI (0.88 to 0.90), N° of leaves (0.58 to 0.85), Specific AF (0.82 to 0.98), vegetative mass (0.94 to 0.98) according to the applied water replacement, with r2 values above 0.65. Regarding the productive variables, although the indices d and r2 were satisfactory, the EF was low for both treatments. The simplified agronomic simulator for Arachis hypogaea (SASAH), a model initially proposed in this work, can be considered still in the construction phase and requires additional adjustments in its algorithms, and it is not used in the thesis to simulate the potential and attainable yield of peanuts. The average efficiency of production in the state of São Paulo is 52%, ranging from 33% in Ribeirão Preto to 72% in Marília.