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CPOTE2020 logo
6th International Conference on
Contemporary Problems of Thermal Engineering
Online | 21-24 September 2020

Abstract CPOTE2020-1055-A

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Numerical analysis of the catalyst distribution optimization in a steam reforming reactor using genetic algorithm

Marcin PAJĄK, AGH University of Science and Technology, Poland
Grzegorz BRUS, AGH University of Science and Technology, Poland
Janusz SZMYD, AGH University of Science and Technology, Poland

The steam reforming reaction is widely used for obtaining syngas, a mixture of hydrogen and carbon monoxide. The process consist of two reactions - the reforming and water-gas-shift reaction. The reforming reaction has a strong endothermic character, what means it requires huge and continuous heat supply to proceed. Due to the process character, a highly non-uniform temperature field develops inside the reactor. It has a consequence in large temperature gradients, leading to the catalyst degradation and reduced lifetime of the reforming unit. The aim of the presented research is to unify the temperature field developing in the reactor, for easier control of the process and extension of the reformer's life expectancy. A conventional plug-flow reactor consist of a cylindrical pipe body, filled with catalyst. The presented methodology included optimization of the catalyst distribution in the reactor, as to acquire the most uniform temperature field possible. A genetic algorithm was chosen to be the mean of finding the most advantageous alignment of the catalyst. It is an example of evolutionary algorithms, basing on rules similar to natural selection. The algorithm generates a random, initial population of reactors and calls the reforming simulation over each of them. The computation results are then evaluated and ranked using predefined fitness functions. The ranked reactors parameters' are further recombined with selection probability based on the fitness values, until a whole new population is created and the algorithm's loop restarts. The higher the fitness value of a specific reactor, the higher are the chances of passing its segments composition to the proceeding generation. The fitness computation leaves a vast space for improvements, as it may be computed basing on many different process' parameters. This work focuses on distinguishing differences in the algorithm performance, depending on the formula for fitness calculation. The algorithm's converging speed, overall fitness values of specimens and optimization results were investigated and compared.

Keywords: Hydrogen, Design optimization, Genetic algorithm, Steam reforming, Numerical analysis
Acknowledgment: Special thanks to the PL-Grid Infrastructure, as this research made use of the computational resources provided by them. The present study was financially supported by AGH University of Science and Technology (Grant AGH No. The presented research is a part of the "Easy-to-Assemble Stack Type (EAST): Development of solid oxide fuel cell stack for the innovation in Polish energy sector" project, carried out within the FIRST TEAM program (project number First TEAM/2016-1/3) of the Foundation for the Polish Science, co-financed by the European Union under the European Regional Development Fund.