期刊
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
卷 46, 期 38, 页码 20183-20197出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ijhydene.2020.02.228
关键词
Evolutionary computation; Genetic algorithms; Numerical simulation; Design optimization; Hydrogen production
资金
- Foundation for the Polish Science [First TEAM/2016-1/3]
- European Union under the European Regional Development Fund
The research focused on optimizing the distribution of catalyst inside a small-scale methane/steam reforming reactor using a genetic algorithm for multiobjective optimization. The study found that the optimized catalyst distribution resulted in the best performance under the working conditions of the system.
The presented research focuses on an optimization design of a catalyst distribution inside a small-scale methane/steam reforming reactor. A genetic algorithm was used for the multiobjective optimization, which included the search for an optimum of methane conversion rate and a minimum of the difference between highest and lowest temperatures in the reactor. For the sake of computational time, the maximal number of the segment with different catalyst densities was set to be thirty in this study. During the entire optimization process, every part of the reactor could be filled, either with a catalyst material or non catalytic metallic foam. In both cases, the porosity and pore size was also specified. The impact of the porosity and pore size on the active reaction surface and permeability was incorporated using graph theory and three-dimensional digital material representation. Calculations start with the generation of a random set of possible reactors, each with a different catalyst distribution. The algorithm calls reforming simulation over each of the reactors, and after obtaining concentration and temperature fields, the algorithms calcu-lated fitness function. The properties of the best reactors are combined to generate a new population of solutions. The procedure is repeated, and after meeting the coverage criteria, the optimal catalyst distribution was proposed. The paper is summarized with the optimal catalyst distribution for the given size and working conditions of the system. (c) 2020 The Authors. Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
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