Fisher information on the performance of dynamic systems / Vicente Rico-Ramirez in Industrial & engineering chemistry research, Vol. 49 N° 4 (Fevrier 2010)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 49 N° 4 (Fevrier 2010) . - pp 1812–1821 Titre : Fisher information on the performance of dynamic systems Type de document : texte imprimé Auteurs : Vicente Rico-Ramirez, Auteur ; Reyes-Mendoza, Miguel A., Auteur ; Quintana-Hernandez, Pedro A., Auteur Année de publication : 2010 Article en page(s) : pp 1812–1821 Note générale : Chimie industrielle Langues : Anglais (eng) Mots-clés : Fisher information Dynamic systems. Résumé : Recent attempts to develop sustainability theory propose the use of Fisher information as a sustainability index. The approach has been shown to be suitable for the analysis of ecological models, including dynamic simulations as well as optimal control problems where the objective function involves maximizing or minimizing Fisher information. Nevertheless, Fisher information can also be interpreted as a measure of the degree of variability of a dynamic system. The goal of this work is two-fold. First, we study the scope of using the concept of Fisher information as a sustainability index in dynamic systems different in nature from ecological systems. Then we study the behavior of Fisher information in terms of the variability and performance of the dynamic system rather than using it as a sustainability index. The results of three case studies are presented, including two chemical engineering applications (a continuous crystallization system and a series of three continuous stirred tank reactors) and a dynamic model of immunotherapy (therapeutic optimization). We perform parametric analyses, evaluating the behavior of the value of Fisher information against significant model parameters. In general, although its usefulness as a sustainability index might be difficult to interpret and elucidate in some cases, Fisher information not only can indeed be related to the degree of variability of any dynamic system, but also provides useful insights with potential application in process control. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901220w [article] Fisher information on the performance of dynamic systems [texte imprimé] / Vicente Rico-Ramirez, Auteur ; Reyes-Mendoza, Miguel A., Auteur ; Quintana-Hernandez, Pedro A., Auteur . - 2010 . - pp 1812–1821. Chimie industrielle Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 4 (Fevrier 2010) . - pp 1812–1821 Mots-clés : Fisher information Dynamic systems. Résumé : Recent attempts to develop sustainability theory propose the use of Fisher information as a sustainability index. The approach has been shown to be suitable for the analysis of ecological models, including dynamic simulations as well as optimal control problems where the objective function involves maximizing or minimizing Fisher information. Nevertheless, Fisher information can also be interpreted as a measure of the degree of variability of a dynamic system. The goal of this work is two-fold. First, we study the scope of using the concept of Fisher information as a sustainability index in dynamic systems different in nature from ecological systems. Then we study the behavior of Fisher information in terms of the variability and performance of the dynamic system rather than using it as a sustainability index. The results of three case studies are presented, including two chemical engineering applications (a continuous crystallization system and a series of three continuous stirred tank reactors) and a dynamic model of immunotherapy (therapeutic optimization). We perform parametric analyses, evaluating the behavior of the value of Fisher information against significant model parameters. In general, although its usefulness as a sustainability index might be difficult to interpret and elucidate in some cases, Fisher information not only can indeed be related to the degree of variability of any dynamic system, but also provides useful insights with potential application in process control. DEWEY : 660 ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901220w

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A mathematical programming approach to pollution trading / Francisco Lopez-Villarreal in Industrial & engineering chemistry research, Vol. 51 N° 17 (Mai 2012)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 51 N° 17 (Mai 2012) . - pp. 5922–5931 Titre : A mathematical programming approach to pollution trading Type de document : texte imprimé Auteurs : Francisco Lopez-Villarreal, Auteur ; Vicente Rico-Ramirez, Auteur ; Guillermo Gonzalez-Alatorre, Auteur Année de publication : 2012 Article en page(s) : pp. 5922–5931 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Pollutant treatment Optimization Résumé : Pollutant trading adds flexibility to the pollution abatement decision making and introduces a new alternative to policy makers and industries. The overall goal is to meet environmental conditions equal or better than those obtained through the implementation of pollutant treatment technologies, but at a lower cost. This work proposes optimization models that can guide industries in taking optimal decisions under the flexibility provided by the trading. The mathematical models, formulated as mixed-integer programming problems, are limited to watershed trading and have been implemented and solved through the GAMS modeling environment. Results include optimal decisions for each pollutant source in order to satisfy global environmental regulations. That is, either implementing one of the available pollution abatement technologies or attaining credits through trading. To assess the performance of the optimization models, we consider a mercury trading case study. A comparison among the nontrading solution and the solutions of the various pollution trading models is presented and analyzed. As the environmental constraints become more stringent, the value of the objective function (cost of technology implementation and fines) increases and the configuration of the required technologies changes to avoid high concentrations of pollutants presented in the various discharge points of the watershed. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2009197 [article] A mathematical programming approach to pollution trading [texte imprimé] / Francisco Lopez-Villarreal, Auteur ; Vicente Rico-Ramirez, Auteur ; Guillermo Gonzalez-Alatorre, Auteur . - 2012 . - pp. 5922–5931. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 17 (Mai 2012) . - pp. 5922–5931 Mots-clés : Pollutant treatment Optimization Résumé : Pollutant trading adds flexibility to the pollution abatement decision making and introduces a new alternative to policy makers and industries. The overall goal is to meet environmental conditions equal or better than those obtained through the implementation of pollutant treatment technologies, but at a lower cost. This work proposes optimization models that can guide industries in taking optimal decisions under the flexibility provided by the trading. The mathematical models, formulated as mixed-integer programming problems, are limited to watershed trading and have been implemented and solved through the GAMS modeling environment. Results include optimal decisions for each pollutant source in order to satisfy global environmental regulations. That is, either implementing one of the available pollution abatement technologies or attaining credits through trading. To assess the performance of the optimization models, we consider a mercury trading case study. A comparison among the nontrading solution and the solutions of the various pollution trading models is presented and analyzed. As the environmental constraints become more stringent, the value of the objective function (cost of technology implementation and fines) increases and the configuration of the required technologies changes to avoid high concentrations of pollutants presented in the various discharge points of the watershed. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie2009197

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Simplified methodology for the design and optimization of thermally coupled reactive distillation systems / Fernando Israel Gómez-Castro in Industrial & engineering chemistry research, Vol. 51 N° 36 (Septembre 2012)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 51 N° 36 (Septembre 2012) . - pp. 11717-11730 Titre : Simplified methodology for the design and optimization of thermally coupled reactive distillation systems Type de document : texte imprimé Auteurs : Fernando Israel Gómez-Castro, Auteur ; Vicente Rico-Ramirez, Auteur ; Juan Gabriel Segovia-Hernandez, Auteur Année de publication : 2012 Article en page(s) : pp. 11717-11730 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Distillation with reaction Optimization Design Résumé : New intensified schemes have been recently proposed as an attempt to reduce energy requirements and equipment costs in reaction-separation processes. A design methodology for thermally coupled reactive distillation systems is proposed in this work. To design the columns, a method based on the Fenske―Underwood―Gilliland (FUG) equations is proposed and tested. The FUG equations, the mass and energy balances, and the phase equilibrium equations are used to formulate the model of the intensified systems. Such a model is then solved as a nonlinear programming problem; the objective function is the minimization of the heat duty in the column. Biodiesel production through the esterification of oleic acid with supercritical methanol is used as a case study. Results show the feasibility of obtaining designs with low energy requirements by using the proposed methodology. Because of nonconvexities present in the formulation, the estimated interlinking flows for the reactive Petlyuk column might not correspond to a minimum for energy requirements. Nevertheless, the resulting designs not only show low heat duties, with a difference of less than 2% from that minimum, but also have the capacity of achieving the desired conversion and purities. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26350340 [article] Simplified methodology for the design and optimization of thermally coupled reactive distillation systems [texte imprimé] / Fernando Israel Gómez-Castro, Auteur ; Vicente Rico-Ramirez, Auteur ; Juan Gabriel Segovia-Hernandez, Auteur . - 2012 . - pp. 11717-11730. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 36 (Septembre 2012) . - pp. 11717-11730 Mots-clés : Distillation with reaction Optimization Design Résumé : New intensified schemes have been recently proposed as an attempt to reduce energy requirements and equipment costs in reaction-separation processes. A design methodology for thermally coupled reactive distillation systems is proposed in this work. To design the columns, a method based on the Fenske―Underwood―Gilliland (FUG) equations is proposed and tested. The FUG equations, the mass and energy balances, and the phase equilibrium equations are used to formulate the model of the intensified systems. Such a model is then solved as a nonlinear programming problem; the objective function is the minimization of the heat duty in the column. Biodiesel production through the esterification of oleic acid with supercritical methanol is used as a case study. Results show the feasibility of obtaining designs with low energy requirements by using the proposed methodology. Because of nonconvexities present in the formulation, the estimated interlinking flows for the reactive Petlyuk column might not correspond to a minimum for energy requirements. Nevertheless, the resulting designs not only show low heat duties, with a difference of less than 2% from that minimum, but also have the capacity of achieving the desired conversion and purities. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26350340

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Strategic capacity allocation under uncertainty by using a two-stage stochastic decomposition algorithm with incumbent solutions / Sergio Frausto-Hernandez in Industrial & engineering chemistry research, Vol. 49 N° 6 (Mars 2010)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 49 N° 6 (Mars 2010) . - pp. 2812–2821 Titre : Strategic capacity allocation under uncertainty by using a two-stage stochastic decomposition algorithm with incumbent solutions Type de document : texte imprimé Auteurs : Sergio Frausto-Hernandez, Auteur ; Vicente Rico-Ramirez, Auteur ; Ignacio E. Grossmann, Auteur Année de publication : 2010 Article en page(s) : pp. 2812–2821 Note générale : Industrial Chemistry Langues : Anglais (eng) Mots-clés : Strategic Capacity  under Uncertainty  Stochastic  Decomposition  Algorithm  Incumbent Résumé : This paper addresses the optimization of strategic capacity allocation problems under uncertainty. Uncertain parameters include the availabilities and the demands of chemicals. The optimization problem is formulated as a two-stage mixed-integer stochastic program (first-stage integer) that maximizes the expected net present value of the project over the time horizon. The net present value includes the discounted investment costs, operating costs, and revenues from sales in the markets. The decisions about the selection of processes and about the plant capacities are defined as the first stage decision variables; given such first stage decisions, recourse is then provided by calculating the operating costs in the second stage. The paper presents the two-stage model and the solution framework. A stochastic decomposition algorithm (SD) based on incumbent solution is used as the solution algorithm. The use of incumbent solutions as convergence criterion allows us to solve the problem in reasonable computational time. Two capacity allocation problems are used as case studies: the first one is a small size problem and is used to compare the stochastic optimal solution against other solution methods; the second one is a larger problem, with an increased number of variables and stochastic parameters. The results show that the stochastic decomposition algorithm with incumbent solutions is stable and robust and greatly reduces the number of samples required for convergence. Note de contenu : Bibiogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901021b [article] Strategic capacity allocation under uncertainty by using a two-stage stochastic decomposition algorithm with incumbent solutions [texte imprimé] / Sergio Frausto-Hernandez, Auteur ; Vicente Rico-Ramirez, Auteur ; Ignacio E. Grossmann, Auteur . - 2010 . - pp. 2812–2821. Industrial Chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 6 (Mars 2010) . - pp. 2812–2821 Mots-clés : Strategic Capacity  under Uncertainty  Stochastic  Decomposition  Algorithm  Incumbent Résumé : This paper addresses the optimization of strategic capacity allocation problems under uncertainty. Uncertain parameters include the availabilities and the demands of chemicals. The optimization problem is formulated as a two-stage mixed-integer stochastic program (first-stage integer) that maximizes the expected net present value of the project over the time horizon. The net present value includes the discounted investment costs, operating costs, and revenues from sales in the markets. The decisions about the selection of processes and about the plant capacities are defined as the first stage decision variables; given such first stage decisions, recourse is then provided by calculating the operating costs in the second stage. The paper presents the two-stage model and the solution framework. A stochastic decomposition algorithm (SD) based on incumbent solution is used as the solution algorithm. The use of incumbent solutions as convergence criterion allows us to solve the problem in reasonable computational time. Two capacity allocation problems are used as case studies: the first one is a small size problem and is used to compare the stochastic optimal solution against other solution methods; the second one is a larger problem, with an increased number of variables and stochastic parameters. The results show that the stochastic decomposition algorithm with incumbent solutions is stable and robust and greatly reduces the number of samples required for convergence. Note de contenu : Bibiogr. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie901021b

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