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Santiago de Querétaro, Mexico

Exxerpro Solutions

Santiago de Querétaro, Mexico

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Miranda-Galindo E.Y.,University of Guanajuato | Segovia-Hernandez J.G.,University of Guanajuato | Hernandez S.,University of Guanajuato | Gutierrez-Antonio C.,CIATEQ | Briones-Ramirez A.,Exxerpro Solutions
Industrial and Engineering Chemistry Research | Year: 2011

Design of reactive distillation sequences is a major computer-aided design challenge. The optimal design of reactive complex distillation systems is a highly nonlinear and multivariable problem, and the objective function used as optimization criterion is generally nonconvex with several local optimums and subject to several constraints. In addition, several attributes for the design of these separation schemes are often conflicting objectives, and the design problem should be represented from a multiple objective perspective. As a result, solving with traditional optimization methods is not reliable because they generally converge to local optimums and often fail to capture the full Pareto optimal front. In this work, we have studied the design of reactive distillation with thermal coupling (using as study case the production of fatty esters), generalizing the use of a multiobjective genetic algorithm with restrictions coupled to Aspen ONE Aspen Plus, previously used in the design and optimization of intensified distillation systems. The results obtained in the Pareto front indicate that the energy consumption of the complex distillation sequence can be reduced significantly by varying operational conditions. Trends in the energy consumption, total annual cost, and greenhouse gas emissions of the thermally coupled reactive distillation sequences can be obtained. © 2010 American Chemical Society.


Cortez-Gonzalez J.,University of Guanajuato | Segovia-Hernandez J.G.,University of Guanajuato | Hernandez S.,University of Guanajuato | Gutierrez-Antonio C.,CIATEQ | And 2 more authors.
Chemical Engineering Research and Design | Year: 2012

The optimal design of complex distillation systems is a highly non-linear and multivariable problem, with several local optimums and subject to different constraints. In addition, some attributes for the design of these separation schemes are often conflicting objectives, and the design problem should be represented from a multiple objective perspective. As a result, solving with traditional optimization methods is not reliable because they generally converge to local optimums, and often fail to capture the full Pareto optimal front. In this paper, a method for the multiobjective optimization of distillation systems, conventional and thermally coupled, with less than N- 1 columns is presented. We use a multiobjective genetic algorithm with restrictions coupled to AspenONE Aspen Plus; so, the complete MESH equations and rigorous phase equilibrium calculations are used. Results show some tendencies in the design of intensified sequences, according to the nature of the mixture and feed compositions. © 2012 The Institution of Chemical Engineers.


Gomez-Castro F.I.,University of Guanajuato | Rodriguez-Angeles M.A.,University of Guanajuato | Rodriguez-Angeles M.A.,Instituto Tecnologico Sanmiguelense | Segovia-Hernandez J.G.,University of Guanajuato | And 4 more authors.
Industrial and Engineering Chemistry Research | Year: 2013

Dividing wall columns are intensified process equipment with the capacity of reducing both capital and operational costs for a given vapor-liquid separation, when compared with conventional distillation sequences. For some kinds of mixtures, distillation systems with two dividing walls have been theoretically proved to present lower energy requirements and lower total annual costs than systems with a single dividing wall. Nevertheless, the use of an additional wall may lead to operational issues on the column, because of the more complex arrangement of the walls on the trays of the columns, where additional split of the vapor and liquid streams is expected. Thus, in this work the open-loop properties (minimum singular value and condition number) for the double dividing wall column are studied and compared with those of the dividing wall column for a wide range of frequencies, in order to determinate if the use of additional dividing walls may lead to potential control problems. It has been found that both systems show similar dynamic performance, with advantages for the double dividing wall column for mixtures with low composition of the middle-boiling component. © 2013 American Chemical Society.


Bravo-Bravo C.,University of Guanajuato | Segovia-Hernandez J.G.,University of Guanajuato | Hernandez S.,University of Guanajuato | Gomez-Castro F.I.,University of Guanajuato | And 2 more authors.
Chemical Engineering and Processing: Process Intensification | Year: 2013

Innovative hybrid processes offer significant cost savings, particularly for azeotropic or close-boiling mixtures. Hybrid separation processes are characterized by the combination of two or more different unit operations, which contribute to the separation task by different physical separation principles. Despite of the inherent advantages of hybrid separation processes, they are not systematically exploited in industrial applications due to the complexity of the design and optimization of these highly integrated processes. In this work we study a hybrid distillation/melt crystallization process, using conventional and thermally coupled distillation sequences. The design and optimization were carried out using, as a design tool, a multi-objective genetic algorithm with restrictions coupled with the process simulator Aspen Plus™, for the evaluation of the objective function. The results show that this hybrid configuration with thermally coupled arrangements is a feasible option in terms of energy savings, capital investment and control properties. © 2012 Elsevier B.V.


Gutierrez-Antonio C.,Autonomous University of Queretaro | Romero-Izquierdo A.G.,University of Guanajuato | Gomez-Castro F.I.,University of Guanajuato | Hernandez S.,University of Guanajuato | Briones-Ramirez A.,Exxerpro Solutions
Chemical Engineering and Processing: Process Intensification | Year: 2016

The sustainable development of aviation sector relies on four strategies, being the use of biojet fuel as the most promising. There are different processes to produce biojet fuel; however, the hydrotreating process is certified by ASTM for its use in commercial and passenger flights. This process has several opportunity areas to decrease energy consumption and environmental impact. In this work, we propose the simultaneous energy integration and intensification of the hydrotreating process to produce biojet fuel from jatropha curcas oil. The released energy by the hydrodeoxygenation reactor is used to perform the energy integration of the process. Moreover, the separation zone of the process is intensified through thermally coupled distillation sequences, which are optimized with a multiobjective stochastic strategy. Results show that it is possible to reduce significantly the energy requirements of the process when energy integration is performed; however, the decreasing in the service costs is accompanied by an increasing in the equipment costs. On the other hand, the intensification of the separation zone does not lead to a decreasing in energy consumption. Therefore, net effect of both strategies on the total annual cost and biojet fuel prices is small, but significant decreasing in CO2 emissions is achieved. © 2016 Elsevier B.V.


Gomez-Castro F.I.,Celaya Institute of Technology | Gomez-Castro F.I.,University of Guanajuato | Rodriguez-Angeles M.A.,University of Guanajuato | Segovia-Hernandez J.G.,University of Guanajuato | And 2 more authors.
Chemical Engineering and Technology | Year: 2011

Since the optimal design of dividing wall columns (DWC) is a highly nonlinear and multivariable problem, an appropriate solving tool is required. In this paper a multi-objective genetic algorithm with restrictions is considered to design columns with dividing walls. Also, a methodology is proposed for sizing the DWC. The proposed design methodology allows achieving appropriate designs for columns with two dividing walls. As expected, the physical structures that allow the use of one or two dividing walls are not so different from each other and, as a consequence, the difference in the total annual costs for both systems depends mainly on the energy requirements. For the optimal design of dividing wall columns (DWC), a multi-objective genetic algorithm with restrictions is considered. Additionally, a methodology is proposed for sizing the DWC. The proposed design methodology shows robustness and it allows obtaining an adequate set of optimal designs for complex distillation sequences. © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


Gutierrez-Antonio C.,CIATEQ | Briones-Ramirez A.,Exxerpro Solutions | Briones-Ramirez A.,Aguascalientes Institute of Technology
Computer Aided Chemical Engineering | Year: 2010

Evolutionary algorithms have been recognized to be well suited for multiobjective optimization [1]; their principal disadvantage is the large number of evaluations of objective function required [2], which is accentuated when those are computationally expensive. In this work, we propose the use of artificial neuronal networks, ANN, to speed up a multiobjective genetic algorithm with constraints, with base on the work of Gaspar-Cunha [3]. The neuronal network generates an approximated function of the original objective function, which are switched during the optimization; so, we reduce the evaluations of the original objective function and the computational time. The use of approximated functions created by the ANN allows reaching the optimal zone rapidly. Results show a significant reduction in the number of evaluations of the objective function, as well as in computational time, required to reaching the Pareto front. © 2010 Elsevier B.V.


Bravo-Bravo C.,University of Guanajuato | Segovia-Hernandez J.G.,University of Guanajuato | Gutierrez-Antonio C.,CIATEQ | Duran A.L.,Aguascalientes Institute of Technology | And 2 more authors.
Industrial and Engineering Chemistry Research | Year: 2010

This paper proposes a novel extractive dividing wall distillation column, which has been designed using a constrained stochastic multiobjective optimization technique. The approach is based on the use of genetic algorithms to determine the design that minimizes energy consumption and total annualized cost. Several case studies are used to show the feasibility of performing extractive separations in dividing wall distillation columns. The simulation results show the effect of the main variables on the complex extractive distillation process. © 2010 American Chemical Society.


Gutierrez-Antonio C.,Autonomous University of Queretaro | Ojeda-Gasca A.,University of Guanajuato | Bonilla-Petriciolet A.,Aguascalientes Institute of Technology | Segovia-Hernandez J.G.,University of Guanajuato | Briones-Ramirez A.,Exxerpro Solutions
Industrial and Engineering Chemistry Research | Year: 2014

We analyze the effect of using adjusted parameters, corresponding to local and global optimums, in the NRTL thermodynamic model on the complete process synthesis (design, optimization and control) of homogeneous azeotropic distillation columns. The adjusted parameters that correspond to a global optimum were obtained with simulated annealing technique, while the adjusted parameters that correspond to a local optimum were taken from the Dechema Collection. Both sets of parameters were used to design a conventional sequence, a side-stream column, and a Petlyuk sequence. These designs were used as the initial solution to a multiobjective genetic algorithm with constraints handling, coupled to a processes simulator, where the number of stages and heat duty of each column were considered as objectives; as a result, a set of optimal designs, called the Pareto front, was obtained. Then, we chose some designs to analyze their theoretical control properties and the dynamic performance. Results show remarkable differences in structure, energy consumption, control properties, and dynamic performance of these schemes, depending on the use of adjusted parameters. The results show the importance of using the best adjusted parameters available, which in our case correspond to global optimums obtained with the simulated annealing technique. © 2013 American Chemical Society.


Gutierrez-Antonio C.,Autonomous University of Queretaro | Gomez-Castro F.I.,University of Guanajuato | Hernandez S.,University of Guanajuato | Briones-Ramirez A.,Exxerpro Solutions
Chemical Engineering and Processing: Process Intensification | Year: 2015

Aviation sector contributes with 2% of the total CO2 emissions, and predictions estimate that air traffic will duplicate in the next 20 years. The development of aviation fuel from renewable feedstocks has been identified as the most promissory strategy to reduce CO2 emissions. Recently, a process to produce aviation fuel from renewable feedstock has been proposed, which converts vegetable oil through hydrogenating, deoxygenating, isomerization and selective hydrocracking to renewable fuels, which are purified later.In this work, we propose the intensification of the hydrotreating production process through the use of thermally coupled distillation for the purification stage; moreover, we incorporate a turbine in order to generate electricity with the energy contained in the outlet stream of the reactor. Also, the purification stage is optimized through a multiobjective genetic algorithm, coupled to a process simulator. Results show that the use of thermally coupled distillation reduces the energy requirements in the separation stage. Also, energy can be generated as a result of the conditioning of the stream that is fed to the distillation train. © 2014 Elsevier B.V.

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