Optimization of a Novel Configuration for an Autothermal Reformer to Produce Hydrogen from Natural Gas

Hydrogen production by natural gas reforming is a mature and well-established method. The process uses methane (CH4), which is present in natural gas, to make hydrogen via thermal processes such as methane steam reforming, partial oxidation, and autothermal reforming. For a wide range of chemical processes, radial flow tubular reactors (RFTRs) offer several advantages over conventional axial flow tubular reactors (AFTRs). Their ability to improve catalyst efficiency, reduce pressure drop, and enable efficient heat transfer makes them a valuable tool for a variety of catalytic chemical processes. This paper presents a study on the modeling and optimization of an autothermal reactor with a radial flow configuration. The reactor is designed to operate under specific conditions, and its performance is optimized by developing a mathematical model that accurately describes the behavior of the system. A combination of experimental data and theoretical calculations is used to develop the model. Genetic algorithm is employed to optimize the reformer’s performance by varying various parameters, such as the feed temperature and the ratio of feed components. The optimization increases the hydrogen production rate by 11% and the methane conversion by 5%, and the optimal temperature profile along the catalyst bed is studied by changing feed specifications.