Abstract In this work, we use the external equations facility available in GAMS to incorporate in... more Abstract In this work, we use the external equations facility available in GAMS to incorporate in the optimization model the library packages of a commercial process simulator such as Aspen-Hysys, which provides an extensive component database and reliable physical property methods. To this end, we write a source code in the C programming language that connects with Matlab, which in turn uses the Microsoft Component Object Model (COM) interface to communicate with Aspen-Hysys. The methodology is illustrated with a case study of the reaction section of a methanol plant. The results show that a thermodynamic rigorous optimization can be performed without losing the high index capabilities, few verbose and simple syntax that an AML offers.
Industrial & Engineering Chemistry Research, Feb 13, 2009
ABSTRACT In this paper, the shell-and-tube heat exchangers design is formulated as an optimizatio... more ABSTRACT In this paper, the shell-and-tube heat exchangers design is formulated as an optimization problem and solved with particle swarm optimization (PSO). The objective is to minimize the global cost including area cost and pumping cost or just area minimization, depending on data availability, rigorously following the standards of the Tubular Exchanger Manufacturers Association and respecting pressure drops and fouling limits. Given fluids temperatures, flow rates, physical properties (density, heat capacity, viscosity, and thermal conductivity), pressure drop and fouling limits, and area cost data, the proposed methodology calculates the optimal mechanical and thermal-hydraulic variables. The Bell−Delaware method is used for the shell-side calculations. Some literature cases are studied and results show that in this type of problem, with a very large number of nonlinear equations, the PSO algorithm presents better results, avoiding local minima.
Abstract Superstructure-based optimization models have been used as important approaches in solvi... more Abstract Superstructure-based optimization models have been used as important approaches in solving process systems engineering problems. Despite its promising results, mixed-integer nonlinear programming (MINLP) optimization models are usually complex, once they involve integer and continuous variables, and nonlinear, non-convex functions. For work and heat exchange networks (WHEN) synthesis, even in problems of few process streams, the derived MINLP models have large combinatorial and continuous search spaces. In the present paper, the search spaces of two equivalents MINLP models for WHEN synthesis are analyzed to test their influence on optimization performance. The models are derived from the same superstructure, but one of those uses strategies to reduce the number of decision variables that provides a considerable diminution of combinatorial problem. The same bi-level meta-heuristic optimization approach in which Simulated Annealing deals with the combinatorial level and Particle Swarm Optimization with the continuous one is used to solve both MINLP problems. The mean values of total annualized cost and elapsed time from several optimization runs of both models are compared. The results show that the decision-variable-reduced model is more efficient and consistent than the standard-decision-variable one. It can be concluded that combinatorial search space reduction is important for optimization performance of highly complex decision-making problems such as WHEN synthesis and should be addressed in WHEN modeling because the problem’s complexity increases exponentially with the number of the model binary variables.
This paper introduces a comprehensive study of the Life Cycle Impact Assessment (LCIA) of water m... more This paper introduces a comprehensive study of the Life Cycle Impact Assessment (LCIA) of water management in shale gas exploitation. First, we present a comprehensive study of wastewater treatment in the shale gas extraction, including the most common technologies for the pretreatment and three different desalination technologies of recent interest: Single and Multiple-Effect Evaporation with Mechanical Vapor Recompression and Membrane Distillation. The analysis has been carried out through a generic Life Cycle Assessment (LCA) and the ReCiPe metric (at midpoint and endpoint levels), considering a wide range of environmental impacts. The results show that among these technologies Multiple-Effect Evaporation with Mechanical Vapor Recompression (MEE-MVR) is the most suitable technology for the wastewater treatment in shale gas extraction, taking into account its reduced environmental impact, the high water recovery compared to other alternatives as well as the lower cost of this tech...
This work deals with the optimization of two-stage membrane systems for H2 separation from off-ga... more This work deals with the optimization of two-stage membrane systems for H2 separation from off-gases in hydrocarbons processing plants to simultaneously attain high values of both H2 recovery and H2 product purity. First, for a given H2 recovery level of 90%, optimizations of the total annual cost (TAC) are performed for desired H2 product purity values ranging between 0.90 and 0.95 mole fraction. One of the results showed that the contribution of the operating expenditures is more significant than the contribution of the annualized capital expenditures (approximately 62% and 38%, respectively). In addition, it was found that the optimal trade-offs existing between process variables (such as total membrane area and total electric power) depend on the specified H2 product purity level. Second, the minimization of the total power demand and the minimization of the total membrane area were performed for H2 recovery of 90% and H2 product purity of 0.90. The TAC values obtained in the fi...
This paper fits into the process system engineering field by addressing the optimization of a two... more This paper fits into the process system engineering field by addressing the optimization of a two-stage membrane system for H2 separation in refinery processes. To this end, a nonlinear mathematical programming (NLP) model is developed to simultaneously optimize the size of each membrane stage (membrane area, heat transfer area, and installed power for compressors and vacuum pumps) and operating conditions (flow rates, pressures, temperatures, and compositions) to achieve desired target levels of H2 product purity and H2 recovery at a minimum total annual cost. Optimal configuration and process design are obtained from a model which embeds different operating modes and process configurations. For instance, the following candidate ways to create the driving force across the membrane are embedded: (a) compression of both feed and/or permeate streams, or (b) vacuum application in permeate streams, or (c) a combination of (a) and (b). In addition, the potential selection of an expansion...
Abstract In this work, we use the external equations facility available in GAMS to incorporate in... more Abstract In this work, we use the external equations facility available in GAMS to incorporate in the optimization model the library packages of a commercial process simulator such as Aspen-Hysys, which provides an extensive component database and reliable physical property methods. To this end, we write a source code in the C programming language that connects with Matlab, which in turn uses the Microsoft Component Object Model (COM) interface to communicate with Aspen-Hysys. The methodology is illustrated with a case study of the reaction section of a methanol plant. The results show that a thermodynamic rigorous optimization can be performed without losing the high index capabilities, few verbose and simple syntax that an AML offers.
Industrial & Engineering Chemistry Research, Feb 13, 2009
ABSTRACT In this paper, the shell-and-tube heat exchangers design is formulated as an optimizatio... more ABSTRACT In this paper, the shell-and-tube heat exchangers design is formulated as an optimization problem and solved with particle swarm optimization (PSO). The objective is to minimize the global cost including area cost and pumping cost or just area minimization, depending on data availability, rigorously following the standards of the Tubular Exchanger Manufacturers Association and respecting pressure drops and fouling limits. Given fluids temperatures, flow rates, physical properties (density, heat capacity, viscosity, and thermal conductivity), pressure drop and fouling limits, and area cost data, the proposed methodology calculates the optimal mechanical and thermal-hydraulic variables. The Bell−Delaware method is used for the shell-side calculations. Some literature cases are studied and results show that in this type of problem, with a very large number of nonlinear equations, the PSO algorithm presents better results, avoiding local minima.
Abstract Superstructure-based optimization models have been used as important approaches in solvi... more Abstract Superstructure-based optimization models have been used as important approaches in solving process systems engineering problems. Despite its promising results, mixed-integer nonlinear programming (MINLP) optimization models are usually complex, once they involve integer and continuous variables, and nonlinear, non-convex functions. For work and heat exchange networks (WHEN) synthesis, even in problems of few process streams, the derived MINLP models have large combinatorial and continuous search spaces. In the present paper, the search spaces of two equivalents MINLP models for WHEN synthesis are analyzed to test their influence on optimization performance. The models are derived from the same superstructure, but one of those uses strategies to reduce the number of decision variables that provides a considerable diminution of combinatorial problem. The same bi-level meta-heuristic optimization approach in which Simulated Annealing deals with the combinatorial level and Particle Swarm Optimization with the continuous one is used to solve both MINLP problems. The mean values of total annualized cost and elapsed time from several optimization runs of both models are compared. The results show that the decision-variable-reduced model is more efficient and consistent than the standard-decision-variable one. It can be concluded that combinatorial search space reduction is important for optimization performance of highly complex decision-making problems such as WHEN synthesis and should be addressed in WHEN modeling because the problem’s complexity increases exponentially with the number of the model binary variables.
This paper introduces a comprehensive study of the Life Cycle Impact Assessment (LCIA) of water m... more This paper introduces a comprehensive study of the Life Cycle Impact Assessment (LCIA) of water management in shale gas exploitation. First, we present a comprehensive study of wastewater treatment in the shale gas extraction, including the most common technologies for the pretreatment and three different desalination technologies of recent interest: Single and Multiple-Effect Evaporation with Mechanical Vapor Recompression and Membrane Distillation. The analysis has been carried out through a generic Life Cycle Assessment (LCA) and the ReCiPe metric (at midpoint and endpoint levels), considering a wide range of environmental impacts. The results show that among these technologies Multiple-Effect Evaporation with Mechanical Vapor Recompression (MEE-MVR) is the most suitable technology for the wastewater treatment in shale gas extraction, taking into account its reduced environmental impact, the high water recovery compared to other alternatives as well as the lower cost of this tech...
This work deals with the optimization of two-stage membrane systems for H2 separation from off-ga... more This work deals with the optimization of two-stage membrane systems for H2 separation from off-gases in hydrocarbons processing plants to simultaneously attain high values of both H2 recovery and H2 product purity. First, for a given H2 recovery level of 90%, optimizations of the total annual cost (TAC) are performed for desired H2 product purity values ranging between 0.90 and 0.95 mole fraction. One of the results showed that the contribution of the operating expenditures is more significant than the contribution of the annualized capital expenditures (approximately 62% and 38%, respectively). In addition, it was found that the optimal trade-offs existing between process variables (such as total membrane area and total electric power) depend on the specified H2 product purity level. Second, the minimization of the total power demand and the minimization of the total membrane area were performed for H2 recovery of 90% and H2 product purity of 0.90. The TAC values obtained in the fi...
This paper fits into the process system engineering field by addressing the optimization of a two... more This paper fits into the process system engineering field by addressing the optimization of a two-stage membrane system for H2 separation in refinery processes. To this end, a nonlinear mathematical programming (NLP) model is developed to simultaneously optimize the size of each membrane stage (membrane area, heat transfer area, and installed power for compressors and vacuum pumps) and operating conditions (flow rates, pressures, temperatures, and compositions) to achieve desired target levels of H2 product purity and H2 recovery at a minimum total annual cost. Optimal configuration and process design are obtained from a model which embeds different operating modes and process configurations. For instance, the following candidate ways to create the driving force across the membrane are embedded: (a) compression of both feed and/or permeate streams, or (b) vacuum application in permeate streams, or (c) a combination of (a) and (b). In addition, the potential selection of an expansion...
Uploads
Papers by Jose Caballero