The objective of this work was to develop a systematic methodology for simultaneously targeting and optimizing heating, cooling, power cogeneration, and waste management for any processing facility. A systems approach was used to characterize the complex interactions between the various forms of material and energy utilities as well as their interactions with the core processing units. Two approaches were developed: graphical and mathematical. In both approaches, a hierarchical procedure was developed to decompose the problem into successive stages that were globally solvable then. The solution fragments were then merged into overall process solutions and targets. The whole approach was a systems approach of solving problems. The methodology was developed from the insights from several state of the art process integration techniques. In particular, the dissertation introduced a consistent framework for simultaneously addressing heat-exchange networks, material-recovery networks, combined heat and power, fuel optimization, and waste management. The graphical approach relied on decomposing the problem into sequential tasks that could be addressed using visualization tools. The mathematical approach enabled the simultaneous solution of critical subproblems. Because of the non-convexity of the mathematical formulation, a global optimization technique was developed through problem reformulation and discretization. A case study was solved and analyzed to illustrate the effectiveness of the devised methodology.

The process industries such as petrochemicals, chemicals and pharmaceuticals, among others, consume large amounts of material and energy resources. These industries are also characterized by generating enormous amounts of waste that significantly contribute to the pollution of the environment. Integrated process design is a very effective technique in conserving process resources and preventing pollution. The design and environmental constraints may involve a variety of component- and property-based restrictions. To date, most techniques have been developed to handle process constraints which is either composition-based (via mass integration) or property-based. No work has been reported to handle the synthesis of resource conservation network that is governed by both constraints. The objective of this work is to develop a systematic and cost-effective design technique that is aimed at minimizing the consumption of fresh resources and the discharge of pollutants simultaneously. Because of the nature of the component- and property-based constraints, this approach is based on mass and property integration and takes into account the process constraints and also environmental regulations. In this research work, a new approach has been developed to simultaneously address component-based recycle constraints as well as property-based discharge constraints. The proposed optimization technique is intended to minimize the consumption of fresh resources, the pollutant content in the waste streams, and the operational and waste treatment costs. Additionally, a mixed-integer nonlinear programming (MINLP) formulation is solved for a case study of phenol production from cumene hydroperoxyde to illustrate the new problem and devised solution algorithm.

A hierarchical procedure is developed to determine maximum overall yield of a process and optimize process changes to achieve such a yield. First, a targeting procedure is developed to identify an upper bound of the overall yield ahead of detailed design. Several mass integration strategies are proposed to attain maximum yield. These strategies include rerouting of raw materials, optimization of reaction yield, rerouting of product from undesirable outlets to desirable outlets, and recycling of unreacted raw materials. Path equations are tailored to provide the appropriate level of detail for modeling process performance as a function of the optimization variables pertaining to design and operating variables. Interval analysis is used as an inclusion technique that provides rigorous bounds regardless of the process nonlinearities and without enumeration. Then, a new approach for identification of cost-effective implementation of maximum attainable targets for yield is presented. In this approach, a mathematical program was developed to identify the maximum feasible yield using a combination of iterative additions of constraints and problem reformulation. Next, cost objectives were employed to identify a cost-effective solution with the details of design and operating variables. Constraint convexification was used to improve the quality of the solution towards globability. A trade-off procedure between the saving and expenses for yield maximization problem is presented. The proposed procedure is systematic, rigorous, and computationally efficient. A case study was solved to demonstrate the applicability and usefulness of the developed procedure.

Orientadores: Jose Vicente Hallak D'Angelo, Roger Josef Zem / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Quimica / Made available in DSpace on 2018-08-06T20:34:11Z (GMT). No. of bitstreams: 1 Andrade_AlexandreAugustode_M.pdf: 1431250 bytes, checksum: 071f09bc36a20d1058f5dcaef7eb20e6 (MD5) Previous issue date: 2006 / Resumo: Na indústria de papel e celulose há uma grande preocupação sobre o consumo crescente de água fresca e também quanto ao volume de efluentes a serem tratados, pois estão estritamente ligados às limitações de expansões do processo, devido a restrições ambientais e capacidade da planta. O objetivo principal deste trabalho é estudar a viabilidade técnica de se usar o efluente gerado nas máquinas de papel, água branca, nas prensas de lavagem do branqueamento, visando uma redução no consumo de água fresca nestes equipamentos. Foi realizado um estudo de caso do processo de produção da Ripasa S.A. Celulose e Papel, uma indústria de papel e celulose localizada em Limeira (Estado de São Paulo). Nesse processo é gerada uma taxa de cerca de 700 m3/h de água branca e devido às propriedades físico-químicas deste efluente, especialmente seu conteúdo de matéria orgânica e sua alta dureza, não é possível a reutilização total dessa água na etapa de branqueamento sem causar problemas operacionais como incrustações em tubos e entupimento das telas. Assim, neste trabalho, um balanço de massa na unidade de branqueamento da Ripasa foi desenvolvido em uma planilha eletrônica, para avaliar a possibilidade de reduzir o consumo de água fresca usando-se uma fração do volume da água branca para a lavagem da polpa nessa etapa do processo. Para tanto algumas propriedades físico-químicas da corrente de água branca e de outras correntes do processo de branqueamento foram determinadas, tendo-se como a mais importante a análise de matéria orgânica. As concentrações máximas de alguns elementos não processáveis (NPE) como Si, Ca, Mn e Fe também foram determinados para estabelecer alguns parâmetros para permitir essa integração de processo, considerando-as como restrições operacionais. Os resultados obtidos mostraram que é possível reduzir aproximadamente 13% do consumo de água fresca, tendose como principais restrições a concentração de matéria orgânica seguida da concentração de Ca presentes na água branca. É importante dizer que esta integração de processo não só contribui para a redução no consumo de água fresca, mas também para a redução do volume dos efluentes gerados no processo / Abstract: In pulp and paper mills there is a great concern about the increasing consumption of fresh water and also the great volume of effluents that need to be treated, since they are represent limitations to new process expansions, due to environment restrictions and plant capacity. The aim of this work is to study the technical viability of using the effluent stream generated in the paper machines, called white water, in the washing presses of bleaching stages, seeking for a reduction in the consumption of fresh water in these equipments. A case study was performed, using industrial data of a real pulp and paper mil!. In its process, white water is produced at a rate of about 700 m3/h and the physical-chemical properties of this effluent, mainly its organic material content and hardness, do not allow its complete reuse in the bleaching process, without causing operational problems like fouling in tubes and clogging in the screens. So, in this work, a material balance of the bleaching unit was developed in an electronic spreadsheet in order to evaluate the possibility to reduce the consumption of fresh water in the washing presses, using a portion of the white water effluent stream. To accomplish the objective proposed, some physical-chemical properties of white water stream and other process streams were determined experimentally, and the most important one is organic material analysis. The maximum concentration of some non-process elements like Si, Ca, Mn and Fe that could accumulate in the process were also determined in order to establish some parameters to perform process integration, considering these concentrations as operational restrictions. The results obtained have shown that it is possible to reduce approximately 13% of fresh water consumption and the main restrictions to this reduction is organic material content and concentration of Ca in white water stream. It is also important to say that this process integration not only contributes to reduce fresh water consumption but also helps to reduce the volume of effluents generated in the process / Mestrado / Sistemas de Processos Quimicos e Informatica / Mestre em Engenharia Química

This dissertation is a complete unifying approach to the fundamentals, industrial applications and software implementation of an important branch of process-engineering principles and practice, called process integration. The latter refers to the system-oriented, thermodynamically-based and integrated approaches to the analysis, synthesis and retrofit of process plants, focusing on integrating the use of materials and energy, and minimizing the generation of emissions and wastes. This work extends process integration to include applications for industrial water reuse and wastewater minimization and presents previous developments in a unified manner. The basic ideas of process integration are: (1) to consider first the big picture by looking at the entire manufacturing process as an integrated system; (2) to apply process-engineering principles to key process steps to establish a priori targets for the use of materials and energy, and for the generation of emissions and wastes; and (3) to finalize the details of the process design and retrofit later to support the integrated view, particularly in meeting the established targets. Pinch technology is a set of primarily graphical tools for analyzing a process plant's potential for energy conservation, emission reduction and waste minimization. Here, we identify targets for the minimum consumption of heating and cooling utilities, mass-separating agents, freshwater consumption, wastewater generation and effluent treatment and propose economical grassroots designs and retrofit projects to meet these goals. An emerging alternative approach to pinch technology, especially when analyzing complex water-using operations and effluent-treatment systems, is mathematical optimization. We solve nonlinear programming problems for simple water-using operations through readily available commercial software. However, more complex, nonconvex problems require sophisticated reformulation techniques to guarantee optimality and are the subject of continuing academic and commercial development. This work develops the principles and practice of an environmentally significant breakthrough of process integration, called water-pinch technology. The new technology enables the practicing engineers to maximize water reuse, reduce wastewater generation, and minimize effluent treatment through pinch technology and mathematical optimization. It applies the technology in an industrial water-reuse demonstration project in a petrochemical complex in Taiwan, increasing the average water reuse (and thus reducing the wastewater treatment) in the five manufacturing facilities from 18.6% to 37%. This dissertation presents complete conceptual and software developments to unify the known branches of process integration, such as heat and mass integration, and wastewater minimization, and explores new frontiers of applications to greatly simplify the tools of process integration for practicing engineers. / Ph. D.

Made available in DSpace on 2016-06-02T19:55:43Z (GMT). No. of bitstreams: 1 6624.pdf: 8550248 bytes, checksum: 5ec0bd60b54af457950d157adeb2bc97 (MD5) Previous issue date: 2015-03-13 / Universidade Federal de Sao Carlos / Este trabalho visa a otimização não-linear restrita usando o Método das Tolerâncias Flexíveis (FTM) e na aplicação do mesmo na síntese de sistemas de integração mássica. A integração mássica é uma técnica que permite a compreensão global do fluxo de massa dentro do processo, e emprega tais conhecimentos na identificação de melhorias de desempenho e otimização da geração e mapeamento de espécies ao longo do processo. A integração de massa baseia-se nos princípios fundamentais da engenharia química combinada com a análise do sistema usando ferramentas gráficas e de otimização. Neste contexto, o método direto de otimização foi usado como base para melhorias a fim de tornar possível sua aplicação em problemas de síntese de processo, especialmente a integração de massa. O Método das Tolerância Flexíveis é um método direto de otimização que apresenta algumas vantagens como simplicidade e a capacidade de lidar com igualdade e desigualdade sem empregar o cálculo de derivadas. O método utiliza duas buscas para satisfazer a restrição de viabilidade. A busca externa é uma variação do método de Nelder-Mead (ou o método Poliedro Flexível ou FPM) que minimiza a função objetivo. A busca interna minimiza o valor da função formada pelas restrições de igualdade e/ou desigualdade do problema. Esta busca interna pode ser realizada por qualquer método de otimização não linear irrestrita. Neste trabalho, o método das tolerâncias flexíveis foi hibridizado com diferentes métodos irrestritos para realizar a busca interna: BFGS (Método de Broyden, Fletcher, Goldfarb and Shanno) e Powell modificado. O método estocástico do Enxame de Partículas (PSO) também foi empregado para efetuar a inicialização e geração do ponto de partida viável para sequencial aplicação do método deiii terminístico (FTM e modificações). Outras modificações testadas foram o escalonamento de variáveis, a utilização de parâmetros adaptativos Nelder-Mead e a adição de uma barreira. Os algoritmos propostos neste trabalho foram aplicados a um conjunto de problemas nãolineares restritos que compreende problemas de otimização reais. Os códigos que apresentaram melhor desempenho foram o Método Modificado das Tolerâncias Flexíveis com variáveis escalonadas (MFTMS) e o híbrido FTMS-PSO (o Método das Tolerância Flexíveis com escalonamento de variáveis e hibridizado com PSO). Estes melhores códigos foram aplicados com sucesso na solução de problemas de integração em massa. Os resultados encontrados neste trabalho demonstram a capacidade de métodos simples e diretos em lidar com problemas de otimização complexos, como os problemas de integração mássica. Além disso, um problema inédito de integração mássica proposto neste trabalho, a integração mássica de uma biorefinaria de cana-de-açúcar incluindo 1G, 2G e 3G, foi resolvido com êxito com os métodos propostos neste trabalho (MFTMS e FTMS-PSO). A primeira geração (1G) inclui a produção de etanol utilizando o caldo da cana-de-açúcar e produção de vapor e eletricidade pela cogeração. A segunda geração (2G) utiliza a biomassa lignocelulósica para produção de etanol pela rota bioquímica. A terceira geração (3G) inclui a utilização de algas para produção de biocombustíveis (etanol e biodiesel). Os resultados deste estudo de caso fornecem uma indicação de uma forma economicamente viável de conseguir avanços substanciais em termos de consumo de água e redução da poluição. / This work is focused in constrained nonlinear optimization using the Flexible Tolerance Method (FTM) and in applying in systems synthesis of mass integration. Mass integration is a technique that allows an overall understanding of the mass flow within the process, and employs such knowledge in identification of performance improvements and optimization of the generation and mapping of species throughout the process. The mass integration is based on the fundamental principles of chemical engineering combined with system analysis using graphical and optimization tools. In this context, the direct method of optimization was used as the basis for improvements in order to make possible the application in process synthesis problems, especially mass integration. The Flexible Tolerance Method is a direct method of optimization that present some advantages as simplicity, the ability to lead with equality and inequality constraints without employ derivative calculus. The method uses two searches to satisfy feasibility constraint. The external search is a variation of the Nelder-Mead method (or the Flexible Polyhedron method or FPM). This one seeks to minimizes the objective function. The internal search minimizes the value of the positive function for all equality and/or inequality constraints of the problem. This internal search can be performed by any unconstrained nonlinear optimization method. In this work, the Flexible Tolerance Method was hybridized with different unconstrained methods to perform the inner search: the BFGS (Broyden, Fletcher, Goldfarb and Shanno Method) and the modified Powell. The stochastic PSO method was also employed to perform the initialization and generation of the feasible start point to sequential application of the determination method i (FTM and modifications). Others modifications tested were the scaling of variables, the use of Nelder-Mead adaptive parameters and the addition of a barrier. The algorithms proposed in this work were applied to a benchmark of constrained nonlinear problems that comprises real world optimization problems. The best codes obtained were the Modified Flexible Tolerance Method Scaled (MFTMS) and the hybrid FTMS-PSO (the Flexible Tolerance Method with scaling of variables hybridized with PSO (Particle Swarm Optimization)). These best codes were applied with success in the solution of mass integration problems. The results found in this work demonstrate the capacity of simple and direct methods in deals with complex optimization problems, as the mass integration problems. Additionally an inedited problem of mass integration proposed in this work, the mass integration of 1G, 2G and 3G sugarcane biorefinery was successful solved with the methods proposed in this work (MFTMS and FTMS-PSO). The first generation (1G) includes the ethanol production using the sugarcane juice and production of vapor and electricity throughout cogeneration. The second generation (2G) includes the ethanol production using the lignocellulosic biomass feedstock via the biochemical route. The third generation (3G) includes the algae use for production of biofuels (ethanol and biodiesel). The findings of this study case provide an indication of an economically viable way of achieving substantial advances in terms of water consumption and pollution reduction.

La conception des procédés industriels doit s'adapter à la raréfaction des ressources naturelles à bas prix et au durcissement des réglementations visant à limiter leur impact environnemental. Ainsi, pour améliorer leur rentabilité économique et leur soutenabilité, leurs effluents doivent être considérés comme des ressources potentielles de matière et d'énergie qui peuvent être valorisées localement ou à un plus grande échelle en les partageant avec d'autres industries voisines en formant un écoparc industriel.Cette thèse présente une nouvelle approche systémique et systématique pour concevoir des réseaux de valorisation d'énergie et de matière optimisés simultanément. Trois modèles linéaires de complexité croissante ont été développés pour concevoir ces réseaux à l'échelle locale. Le premier modèle (M1) détermine la consommation minimale nécessaire de ressources fraîches. Le second modèle (M2) introduit une nouvelle superstructure permettant l'optimisation simultanée des besoins énergétiques et matière pour atteindre le minimum de coûts de fonctionnement. Le troisième modèle (M3) conçoit les réseaux optimaux d'allocation de matière et d'échangeurs de chaleur simultanément. Sa fonction objective est le coût total annualisé incluant les coûts d'investissement et de fonctionnement.L'utilisation des unités de régénération est rendu possible dans la structure des trois modèles précédents. Tous les types d'unités peuvent être représentés par un modèle simple avec des paramètres génériques utilisant des objets déjà définis dans la formulation du modèle M3.Finalement, l'application du modèle M3 est étendue à la conception d'écoparcs industriels grâce à de nouvelles notions (sites, clusters, réseaux intermédiaires de matière et de chaleur), obtenant ainsi un nouveau modèle M4. Ce modèle inclut dans sa fonction objective les coûts d'investissements des réseaux liés à leur topologie.Des cas d'études issus de la littérature sont utilisés pour valider la pertinence et les performances des modèles présentés. / The design of industrial processes needs to be adapted as cheap natural resources are scarcer and environmental standards are more stringent to limit their environmental footprints. In order to improve their cost-effectiveness as well as their sustainability, industrial effluents must considered as potential heat and mass resources whether they are recycled locally or at a larger scale by sharing them with other industrial companies; thus forming an eco-industrial park (EIP).This thesis presents a new systemic and systematic approach to design optimal mass allocation and heat exchanger networks simultaneously. Three linear models of incremental complexity have been developed to design optimal recovery networks at a local scale. The first linear model (M1) looks for the necessary minimum fresh resource consumption. The second linear model (M2) presents a new superstructure that allows optimizing mass and heat requirements simultaneously, targeting the minimum annual operating costs. The third linear model (M3) allows designing optimal mass allocation and heat exchanger networks simultaneously. Its objective function is the total annualized cost considering operating and capital costs.The opportunity to use regeneration units is added to the structure of the three previous models. Any type of these units can be represented by a simple model with the generic parameters based on objects already existing in the previous models formulations.Finally, a M3 model applicability is extended to the design of collaborative eco-industrial parks with additional concepts (sites, clusters, indirect heat and mass networks) to obtain a new M4 model. In this model, the capital costs related to the topology of the networks are taken into account in the objective function.The relevance and performances of the proposed models are validated with several case studies taken from the literature.