Ammonia decomposition in a porous catalytic reactor to enable hydrogen storage: Numerical simulation, machine learning, and response surface methodology

Abstract

Ammonia decomposition is a promising technique for storing and producing hydrogen without carbon emissions. Herein, the potential of hydrogen production via ammonia decomposition in a porous catalytic shell and tube reactor is studied for the first time. The underlying relationship between eight process variables, including reactor structural and operational ones, and the system performance is developed by the aids of computational fluid dynamics (CFD), artificial neural network (ANN), and response surface methodology (RSM). It is found that the reactor (shell-side) inlet velocity, tube inlet temperature, reactor inlet temperature, and porosity are the most influential parameters in ammonia conversion, system efficiency, hydrogen flow rate, and pressure drop, respectively. Moreover, three optimal designs with minimal pressure drop are proposed, considering different optimization objectives. The suggested designs, that are suitable for constructing experimental prototypes, have a porosity of around 0.8 and pore diameters >1.5 mm.