Optimization of chemical engineering problems with EMSO software

EMSO software, a free tool for teaching and academic research, presents a favorable environment for simulation and optimization of chemical engineering problems. Although its use in research activities have been demonstrated in the literature, its application as a supporting tool for educational purposes in process systems engineering courses has not been evaluated. The objective of this paper is to demonstrate that this software is suitable as a tool for educational purposes in process systems engineering courses at undergraduate (complementary elective subject) and graduate levels. To accomplish this task, different cases studies, encompassing different sort of programming formulations, are proposed and solved with different solvers in EMSO.

[1]  Argimiro R. Secchi,et al.  Teaching chemical reaction engineering using EMSO simulator , 2010, Comput. Appl. Eng. Educ..

[2]  Ignacio E. Grossmann,et al.  An outer-approximation algorithm for a class of mixed-integer nonlinear programs , 1987, Math. Program..

[3]  Andreas Wächter,et al.  Short Tutorial: Getting Started With Ipopt in 90 Minutes , 2009, Combinatorial Scientific Computing.

[4]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[5]  Christodoulos A. Floudas,et al.  Nonlinear and Mixed-Integer Optimization , 1995 .

[6]  Omprakash K. Gupta Branch and bound experiments in nonlinear integer programming , 1980 .

[7]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[8]  Argimiro Resende Secchi,et al.  EMSO: A new environment for modelling, simulation and optimisation , 2003 .

[9]  Argimiro Resende Secchi,et al.  Implementation of a block-oriented model library for undergraduate process control courses in EMSO simulator , 2017 .

[10]  Caliane Bastos Borba Costa,et al.  Implementation of Pareto Multi-objective Particle Swarm Optimization Algorithm in EMSO , 2012 .

[11]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[12]  I. Grossmann,et al.  An LP/NLP based branch and bound algorithm for convex MINLP optimization problems , 1992 .

[13]  José Antonio Caballero,et al.  Logic hybrid simulation-optimization algorithm for distillation design , 2015, Comput. Chem. Eng..

[14]  Alexandre C. Dimian,et al.  Integrated design and simulation of chemical processes , 2003 .

[15]  Antonio José Gonçalves Cruz,et al.  Multiobjective optimization of a sugarcane biorefinery involving process and environmental aspects , 2016 .

[16]  Gerard Olivar,et al.  Bifurcation analysis of dynamic process models using Aspen Dynamics® and Aspen Custom Modeler® , 2014, Comput. Chem. Eng..

[17]  Felipe C. Cunha,et al.  Dynamic Simulation of a Compressor Located in a Natural Gas Processing Unit Using EMSO Simulator , 2009 .

[18]  Juan Gabriel Segovia-Hernández,et al.  The importance of the sequential synthesis methodology in the optimal distillation sequences design , 2014, Computers and Chemical Engineering.

[19]  Argimiro R. Secchi,et al.  Assessing the production of first and second generation bioethanol from sugarcane through the integration of global optimization and process detailed modeling , 2012, Comput. Chem. Eng..

[20]  William R. Paterson,et al.  A replacement for the logarithmic mean , 1984 .

[21]  Ignacio E. Grossmann,et al.  Disjunctive Programming Techniques for the Optimization of Process Systems with Discontinuous Investment Costs−Multiple Size Regions , 1996 .

[22]  Emeli Borges,et al.  CAMPUS - SÃO JOSÉ DO RIO PRETO , 2009 .

[23]  R. M. Filho,et al.  Production of bioethanol and other bio-based materials from sugarcane bagasse: Integration to conventional bioethanol production process , 2009 .

[24]  Argimiro Resende Secchi,et al.  Reduced Rigorous Models for Efficient Dynamic Simulation and Optimization of Distillation Columns , 2012 .

[25]  Argimiro R. Secchi,et al.  A simple approach to improve the robustness of equation-oriented simulators: Multilinear look-up table interpolators , 2016, Comput. Chem. Eng..

[26]  Gérard Cornuéjols,et al.  An algorithmic framework for convex mixed integer nonlinear programs , 2008, Discret. Optim..

[27]  Prospero C. Naval,et al.  An effective use of crowding distance in multiobjective particle swarm optimization , 2005, GECCO '05.

[28]  Michael N. Vrahatis,et al.  Particle swarm optimization for integer programming , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).