Entropy generation minimization for the thermal decomposition of methane gas in hydrogen using genetic algorithms

In the present work, we have developed an optimization analysis based on entropy generation minimization for the thermal cracking of methane gas. The CO2-free production of hydrogen derived from the above process is predicted theoretically for a simple model that retains the main physical and geometrical characteristics of a thermochemical solar reactor. In the present case, the mass and energy balance equations together with the global entropy generation were numerically solved taking into account that the prediction of the methane conversion and the temperature field are constrained by the minimization of the entropy generation, which defines the objective function. Since the number of variables and physical properties is considerable, the optimization procedure is based on genetic algorithms, technique particularly attractive to obtain an optimal solution for the thermal design of this simple reactor. Using dimensionless variables, we show the existence of five relevant dimensionless parameters which control the optimization process. In addition, an order of magnitude analysis enables us to identify that the chemical reaction is the main source of internal irreversibility of the suggested chemical process. Therefore, minimum values of the objective function are found for an optimal combination of the above parameters. Finally, we show that when the entropy generation is minimized, then the economical costs associated with the thermal cracking of the methane are reduced also.

► The production of hydrogen is based on an endothermic reaction.
► The methane cracking can be optimized by using genetic algorithms.
► The optimal performance is obtained by using entropy generation minimization.