Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been e... more Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been enhanced to predict batch operations behavior, including simultaneous chemical reactions. This program has been implemented for personal (80486 based) microcomputers in a package called (ctive istillation namic imulator). Results obtained with the original model applied to multicomponent continuous distillation, startup, shutdown and multiple columns arrangements (distillation trains) were published in several recent papers, demonstrating its good performance. Due to the actual revival in batch operations interest the model has been adapted to handle batch reactive distillation operations. Simulated results for two examples considering both startup and production periods, are presented.
−− This work presents a computational tool, useful in risk assessment of hazardous material relea... more −− This work presents a computational tool, useful in risk assessment of hazardous material releases. It is based on a methodology that takes into account the stochastic uncertainty of atmospheric parameters. This is relevant for calculating risk of hazardous gases, particulate matter or bioaerosols diffusion when an accidental release or continuous emission occurs. This methodology can be applied to risk analysis of static sources (a stack or a fixed tank in a facility) or transportation accidents (road, train, maritime and pipeline transport) involving different scenarios. After carrying out a stochastic simulation based on well-known diffusion models (heavy and light gases or particulate matter), downwind concentrations are obtained so that individual and societal risks can be computed. This work contributes mainly to the formal presentation of the procedure, and the real application of the stochastic simulation avoiding large (prohibitive) computational effort, by introducing a ...
A methodology and a powerful computational tool (Stochastic Toxic Release Risk Assessment Package... more A methodology and a powerful computational tool (Stochastic Toxic Release Risk Assessment Package, STRRAP) useful in risk assessment and emergency planning (safe distance calculation) is presented. This tool is based on a method which lets the handling of stochastic uncertainty of atmospheric parameters, critical when calculating risk, especially when hazardous gases or particulate matter diffusions occur as a result of an accidental release or emission. In fact, the random behaviour of wind intensity, wind direction, atmospheric stability and temperature given a time horizon (seasonal or a complete year), is considered. So, distributions of the meteorological parameters to be used must be specific for the place under study. This methodology can be used for both releases and emissions from static sources (a stack or a fixed tank in a facility) as well as from transportation accidents (road, train, maritime and pipeline transport). After a stochastic simulation which is based on well...
Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (Dycord'95), 1995
Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been e... more Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been enhanced to predict batch operations behavior, including simultaneous chemical reactions. This program has been implemented for personal (80486 based) microcomputers in a package called (ctive istillation namic imulator). Results obtained with the original model applied to multicomponent continuous distillation, startup, shutdown and multiple columns arrangements (distillation trains) were published in several recent papers, demonstrating its good performance. Due to the actual revival in batch operations interest the model has been adapted to handle batch reactive distillation operations. Simulated results for two examples considering both startup and production periods, are presented.
Industrial & Engineering Chemistry Research, Jun 1, 1989
This paper presents a set of heuristics useful for optimal design of heat-exchange networks and i... more This paper presents a set of heuristics useful for optimal design of heat-exchange networks and integrated heat and power systems. These heuristics consolidate other approaches reported in the literature in a formalism useful for design purposes.
This paper presents a mixed integer nonlinear programming (MINLP) mathematical model to simultane... more This paper presents a mixed integer nonlinear programming (MINLP) mathematical model to simultaneously optimize the configuration of a combined cycle power plant (CCPP), the geometric design and operating conditions as well. The whole process is modelled by considering detailed energy and mass balances. Physical and chemical properties of air, flue gases and water (working fluid for power cycle), overall heat transfer coefficients are computed using nonlinear correlations. On the other hand, discrete decisions (integer variables) are employed to model the tube number, diameters and widths of tubes in each equipment section as well as the number of fins per unit length of tube among others. Continuous variables are related to the pressures, temperatures and flow-rates of gases and working fluid streams. GAMS (General Algebraic Modelling System) is used to implement and to solve the mathematical model. Once the proposed MINLP model was successfully validated with literature, it was solved for three objective functions. The obtained results are presented and discussed in detail.
In this paper, a new strategy involving an evolutionary algorithmic procedure for the optimizatio... more In this paper, a new strategy involving an evolutionary algorithmic procedure for the optimization of Multiple Stage Flash (MSF-M) Systems is presented. A "detailed model" of an MSF-M System is developed according to rigorous material, momentum and energy balances for each stage. The model of the MSF-M System is represented as a complex NLP, which incorporates a high number of nonlinear constraints that difficult the global optimum determination. Here we present a hybrid methodology that uses optimal solutions obtained from a "thermodynamic method" to find the "economic global optimal solution". A pre-processing stage (solving successive NLPs) is used to initialize the final NLP problem. A Case Study and a discussion of the results are presented.
Journal of Food Science and Technology, Dec 1, 2016
Water consumption required during the leaching stage in the surimi manufacturing process strongly... more Water consumption required during the leaching stage in the surimi manufacturing process strongly depends on the design and the number and size of stages connected in series for the soluble protein extraction target, and it is considered as the main contributor to the operating costs. Therefore, the optimal synthesis and design of the leaching stage is essential to minimize the total annual cost. In this study, a mathematical optimization model for the optimal design of the leaching operation is presented. Precisely, a detailed Mixed Integer Nonlinear Programming (MINLP) model including operating and geometric constraints was developed based on our previous optimization model (NLP model). Aspects about quality, water consumption and main operating parameters were considered. The minimization of total annual costs, which considered a trade-off between investment and operating costs, led to an optimal solution with lesser number of stages (2 instead of 3 stages) and higher volumes of the leaching tanks comparing with previous results. An analysis was performed in order to investigate how the optimal solution was influenced by the variations of the unitary cost of fresh water, waste treatment and capital investment. Keywords Surimi manufacturing process Á Optimal configuration and design Á MINLP model Á Mathematical programming model Á GAMS List of symbols A Area (m 2) c Concentration (mg/ml
ABSTRACT To guarantee acceptable hard candy quality during the cooling stage, the distribution of... more ABSTRACT To guarantee acceptable hard candy quality during the cooling stage, the distribution of the product’s temperature throughout the cooling tunnel must be controlled. Hence, the product’s quality depends on the operating conditions of the cooling process and the air conditioning system. In this paper, hard candy quality, operating policies and production planning are integrated in an NLP optimization mathematical model to obtain optimal operating polices under different operating modes, minimizing the annual cost. The resulting model is applied in different case studies in which the production of one, and then six products, is analyzed considering different levels of production, demand and conveyor belt capacities. The study also considers different operating conditions for the air conditioning system under three possible operating modes during the year.
In this paper, a new procedure for the design and analysis of Heat and Power Plants is presented.... more In this paper, a new procedure for the design and analysis of Heat and Power Plants is presented. In this formulation, thermodynamic solutions obtained by maximizing the plant efficiency are used to find the economic design of the plant. In fact, by applying the Karush-Kuhn-Tucker conditions it is possible to relate thermodynamic and economic solutions. A formal context for the use of thermodynamic models in solving complex optimization problems that arise in the area of synthesis and design of chemical processes is introduced. The proposed methodology has been successfully applied for two plant arrangements. Rigorous models have been used to model the plant equipments. The obtained results are presented in order to illustrate the proposed procedure. Keywords−− Thermodynamic solutions, optimal design of combined power and heat plants, optimization.
A new deterministic algorithm [1] to solve a nonconvex, nonlinear optimization problem (a desalin... more A new deterministic algorithm [1] to solve a nonconvex, nonlinear optimization problem (a desalination process model) to global optimality is presented. The algorithm optimization was applied to the simplified model developed previously by Mussati et al. [2,3]. The objective was to determine the optimal process design and operating conditions for a given water production. Although the model for the desaltor was derived from a simplified hypothesis, it considers all the most important aspects of the process. The model takes into account the evaporator geometric design (height, length and width of stages), number of tubes in the pre-heater, boiling point elevation, among others. The resulting mathematical model contains inherently nonlinear and nonconvex constraints. The proposed iterative algorithm is deterministic, and it attains finite g-convergence to the global optimum through the successive subdivision of the original region and the subsequent solution of nonconvex optimization problems. A bound reduction technique is performed in order to accelerate the algorithm convergence. The global optimal solutions obtained by the algorithm provide preliminary designs for the process. Moreover, these solutions are used as a starting point to solve more complex models efficiently [3]. Different case studies are presented and discussed in order to illustrate the methodology and computational performance.
In this paper, glass transition temperature (Tg) and microstructure of hard candy honey flavored ... more In this paper, glass transition temperature (Tg) and microstructure of hard candy honey flavored have been investigated using differential scanning calorimetry (DSC) data and scanning electron microscopy images (SEM) respectively. Precisely, the glass transition temperature can be used as reference temperature to determine the operating mode of processing stages. In fact, the temperature at which hard candies may leave the
In this paper, a new formulation based on disjunctive programming to model the superstructure of ... more In this paper, a new formulation based on disjunctive programming to model the superstructure of alternative configurations for the synthesis, design and analysis of combined cycle power and desalination plant recently developed in Mussati et al. [Desalination, 182 (2005) 123-129] is presented. In this new formulation, boolean variables model discrete decisions while continuous variables represent the operation conditions of the process, e.g., flow rates, energy demand. Optimal unit configuration and operating conditions are computed by solving the proposed model in order to satisfy electricity generation and freshwater productions demands. Rigorous, non-convex and highly non-linear constraints are involved in the formulation, therefore, robust and efficient solution algorithms have to be used. The Logic-Based Outer Approximation (LOA) algorithm developed by Turkay and Grossmann [Comp. Chem. Eng., 20 (8) (1996) 959] with the modifications introduced by Yeomans and Grossmann [Ind. Eng. Chem. Res., 39 (6) (2000) 1637] are used as part of the solution procedure. The model is implemented and solved in the General Algebraic Modeling System (GAMS). Several study cases for different required power to water ratios are presented and analyzed in order to illustrate the robustness and computational performance of the proposed model.
Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been e... more Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been enhanced to predict batch operations behavior, including simultaneous chemical reactions. This program has been implemented for personal (80486 based) microcomputers in a package called (ctive istillation namic imulator). Results obtained with the original model applied to multicomponent continuous distillation, startup, shutdown and multiple columns arrangements (distillation trains) were published in several recent papers, demonstrating its good performance. Due to the actual revival in batch operations interest the model has been adapted to handle batch reactive distillation operations. Simulated results for two examples considering both startup and production periods, are presented.
−− This work presents a computational tool, useful in risk assessment of hazardous material relea... more −− This work presents a computational tool, useful in risk assessment of hazardous material releases. It is based on a methodology that takes into account the stochastic uncertainty of atmospheric parameters. This is relevant for calculating risk of hazardous gases, particulate matter or bioaerosols diffusion when an accidental release or continuous emission occurs. This methodology can be applied to risk analysis of static sources (a stack or a fixed tank in a facility) or transportation accidents (road, train, maritime and pipeline transport) involving different scenarios. After carrying out a stochastic simulation based on well-known diffusion models (heavy and light gases or particulate matter), downwind concentrations are obtained so that individual and societal risks can be computed. This work contributes mainly to the formal presentation of the procedure, and the real application of the stochastic simulation avoiding large (prohibitive) computational effort, by introducing a ...
A methodology and a powerful computational tool (Stochastic Toxic Release Risk Assessment Package... more A methodology and a powerful computational tool (Stochastic Toxic Release Risk Assessment Package, STRRAP) useful in risk assessment and emergency planning (safe distance calculation) is presented. This tool is based on a method which lets the handling of stochastic uncertainty of atmospheric parameters, critical when calculating risk, especially when hazardous gases or particulate matter diffusions occur as a result of an accidental release or emission. In fact, the random behaviour of wind intensity, wind direction, atmospheric stability and temperature given a time horizon (seasonal or a complete year), is considered. So, distributions of the meteorological parameters to be used must be specific for the place under study. This methodology can be used for both releases and emissions from static sources (a stack or a fixed tank in a facility) as well as from transportation accidents (road, train, maritime and pipeline transport). After a stochastic simulation which is based on well...
Dynamics and Control of Chemical Reactors, Distillation Columns and Batch Processes (Dycord'95), 1995
Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been e... more Abstract A well proven multicomponent, reactive, continuous distillation dynamic model has been enhanced to predict batch operations behavior, including simultaneous chemical reactions. This program has been implemented for personal (80486 based) microcomputers in a package called (ctive istillation namic imulator). Results obtained with the original model applied to multicomponent continuous distillation, startup, shutdown and multiple columns arrangements (distillation trains) were published in several recent papers, demonstrating its good performance. Due to the actual revival in batch operations interest the model has been adapted to handle batch reactive distillation operations. Simulated results for two examples considering both startup and production periods, are presented.
Industrial & Engineering Chemistry Research, Jun 1, 1989
This paper presents a set of heuristics useful for optimal design of heat-exchange networks and i... more This paper presents a set of heuristics useful for optimal design of heat-exchange networks and integrated heat and power systems. These heuristics consolidate other approaches reported in the literature in a formalism useful for design purposes.
This paper presents a mixed integer nonlinear programming (MINLP) mathematical model to simultane... more This paper presents a mixed integer nonlinear programming (MINLP) mathematical model to simultaneously optimize the configuration of a combined cycle power plant (CCPP), the geometric design and operating conditions as well. The whole process is modelled by considering detailed energy and mass balances. Physical and chemical properties of air, flue gases and water (working fluid for power cycle), overall heat transfer coefficients are computed using nonlinear correlations. On the other hand, discrete decisions (integer variables) are employed to model the tube number, diameters and widths of tubes in each equipment section as well as the number of fins per unit length of tube among others. Continuous variables are related to the pressures, temperatures and flow-rates of gases and working fluid streams. GAMS (General Algebraic Modelling System) is used to implement and to solve the mathematical model. Once the proposed MINLP model was successfully validated with literature, it was solved for three objective functions. The obtained results are presented and discussed in detail.
In this paper, a new strategy involving an evolutionary algorithmic procedure for the optimizatio... more In this paper, a new strategy involving an evolutionary algorithmic procedure for the optimization of Multiple Stage Flash (MSF-M) Systems is presented. A "detailed model" of an MSF-M System is developed according to rigorous material, momentum and energy balances for each stage. The model of the MSF-M System is represented as a complex NLP, which incorporates a high number of nonlinear constraints that difficult the global optimum determination. Here we present a hybrid methodology that uses optimal solutions obtained from a "thermodynamic method" to find the "economic global optimal solution". A pre-processing stage (solving successive NLPs) is used to initialize the final NLP problem. A Case Study and a discussion of the results are presented.
Journal of Food Science and Technology, Dec 1, 2016
Water consumption required during the leaching stage in the surimi manufacturing process strongly... more Water consumption required during the leaching stage in the surimi manufacturing process strongly depends on the design and the number and size of stages connected in series for the soluble protein extraction target, and it is considered as the main contributor to the operating costs. Therefore, the optimal synthesis and design of the leaching stage is essential to minimize the total annual cost. In this study, a mathematical optimization model for the optimal design of the leaching operation is presented. Precisely, a detailed Mixed Integer Nonlinear Programming (MINLP) model including operating and geometric constraints was developed based on our previous optimization model (NLP model). Aspects about quality, water consumption and main operating parameters were considered. The minimization of total annual costs, which considered a trade-off between investment and operating costs, led to an optimal solution with lesser number of stages (2 instead of 3 stages) and higher volumes of the leaching tanks comparing with previous results. An analysis was performed in order to investigate how the optimal solution was influenced by the variations of the unitary cost of fresh water, waste treatment and capital investment. Keywords Surimi manufacturing process Á Optimal configuration and design Á MINLP model Á Mathematical programming model Á GAMS List of symbols A Area (m 2) c Concentration (mg/ml
ABSTRACT To guarantee acceptable hard candy quality during the cooling stage, the distribution of... more ABSTRACT To guarantee acceptable hard candy quality during the cooling stage, the distribution of the product’s temperature throughout the cooling tunnel must be controlled. Hence, the product’s quality depends on the operating conditions of the cooling process and the air conditioning system. In this paper, hard candy quality, operating policies and production planning are integrated in an NLP optimization mathematical model to obtain optimal operating polices under different operating modes, minimizing the annual cost. The resulting model is applied in different case studies in which the production of one, and then six products, is analyzed considering different levels of production, demand and conveyor belt capacities. The study also considers different operating conditions for the air conditioning system under three possible operating modes during the year.
In this paper, a new procedure for the design and analysis of Heat and Power Plants is presented.... more In this paper, a new procedure for the design and analysis of Heat and Power Plants is presented. In this formulation, thermodynamic solutions obtained by maximizing the plant efficiency are used to find the economic design of the plant. In fact, by applying the Karush-Kuhn-Tucker conditions it is possible to relate thermodynamic and economic solutions. A formal context for the use of thermodynamic models in solving complex optimization problems that arise in the area of synthesis and design of chemical processes is introduced. The proposed methodology has been successfully applied for two plant arrangements. Rigorous models have been used to model the plant equipments. The obtained results are presented in order to illustrate the proposed procedure. Keywords−− Thermodynamic solutions, optimal design of combined power and heat plants, optimization.
A new deterministic algorithm [1] to solve a nonconvex, nonlinear optimization problem (a desalin... more A new deterministic algorithm [1] to solve a nonconvex, nonlinear optimization problem (a desalination process model) to global optimality is presented. The algorithm optimization was applied to the simplified model developed previously by Mussati et al. [2,3]. The objective was to determine the optimal process design and operating conditions for a given water production. Although the model for the desaltor was derived from a simplified hypothesis, it considers all the most important aspects of the process. The model takes into account the evaporator geometric design (height, length and width of stages), number of tubes in the pre-heater, boiling point elevation, among others. The resulting mathematical model contains inherently nonlinear and nonconvex constraints. The proposed iterative algorithm is deterministic, and it attains finite g-convergence to the global optimum through the successive subdivision of the original region and the subsequent solution of nonconvex optimization problems. A bound reduction technique is performed in order to accelerate the algorithm convergence. The global optimal solutions obtained by the algorithm provide preliminary designs for the process. Moreover, these solutions are used as a starting point to solve more complex models efficiently [3]. Different case studies are presented and discussed in order to illustrate the methodology and computational performance.
In this paper, glass transition temperature (Tg) and microstructure of hard candy honey flavored ... more In this paper, glass transition temperature (Tg) and microstructure of hard candy honey flavored have been investigated using differential scanning calorimetry (DSC) data and scanning electron microscopy images (SEM) respectively. Precisely, the glass transition temperature can be used as reference temperature to determine the operating mode of processing stages. In fact, the temperature at which hard candies may leave the
In this paper, a new formulation based on disjunctive programming to model the superstructure of ... more In this paper, a new formulation based on disjunctive programming to model the superstructure of alternative configurations for the synthesis, design and analysis of combined cycle power and desalination plant recently developed in Mussati et al. [Desalination, 182 (2005) 123-129] is presented. In this new formulation, boolean variables model discrete decisions while continuous variables represent the operation conditions of the process, e.g., flow rates, energy demand. Optimal unit configuration and operating conditions are computed by solving the proposed model in order to satisfy electricity generation and freshwater productions demands. Rigorous, non-convex and highly non-linear constraints are involved in the formulation, therefore, robust and efficient solution algorithms have to be used. The Logic-Based Outer Approximation (LOA) algorithm developed by Turkay and Grossmann [Comp. Chem. Eng., 20 (8) (1996) 959] with the modifications introduced by Yeomans and Grossmann [Ind. Eng. Chem. Res., 39 (6) (2000) 1637] are used as part of the solution procedure. The model is implemented and solved in the General Algebraic Modeling System (GAMS). Several study cases for different required power to water ratios are presented and analyzed in order to illustrate the robustness and computational performance of the proposed model.
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