Optimization of hydrogen production by using genetic algorithm

Authors

  • Leonardo Dantas de Souza Netto Universidade Federal de Sergipe http://orcid.org/0000-0001-5936-7841
  • Taline Valéria Góes Reis
  • André da Silva Guimarães
  • Pedro Leite de Santana
  • Antônio Santos Silva
  • Rogério Luz Pagano

DOI:

https://doi.org/10.14808/sci.plena.2016.054205

Keywords:

Steam reforming, CFD, Genetic Algorithm

Abstract

The research for new alternatives and energy generating processes has become crucial to understand the global demand for sustainable and less aggressive energy sources to the environment. Facing these facts, the production of hydrogen becomes a viable alternative, since it is considered a clean and high density energy fuel. The main industrial route for obtaining hydrogen is the steam methane reforming. This is an endothermic process, in which methane reacts with steam at high temperature and pressure conditions to yield hydrogen. Recently, advances in modeling and simulation field, especially applying computational fluid dynamics technique, is aiding in the investigation and optimization of these processes, with low expenses. In this context, this study aimed to simulate a reactor with membrane by applying commercial software, in order to perform the optimization of its operational conditions. The Genetic Algorithm (GA) was applied in order to maximize the productivity of the process. Simulated profiles of the reactor for the conversion of methane and hydrogen recovery were obtained reaching values of 100%, which proves the effectiveness of the methodology presented for optimizing the main process variables.

Author Biography

Leonardo Dantas de Souza Netto, Universidade Federal de Sergipe

Engenheiro Químico pela Universidade Federal de Sergipe, mestre em Ciências e Engenharia de Processos Químicos Industriais, atualmente trabalhando nas áreas de modelagem, simulação e otimização de processos químicos.

Published

2016-05-12

How to Cite

Netto, L. D. de S., Reis, T. V. G., Guimarães, A. da S., Santana, P. L. de, Silva, A. S., & Pagano, R. L. (2016). Optimization of hydrogen production by using genetic algorithm. Scientia Plena, 12(5). https://doi.org/10.14808/sci.plena.2016.054205

Issue

Section

VII Seminário de Pesquisa em Engenharia Química - Edição financiada pela CAPES

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