Optimization of SMR process for syngas production through a solar-assisted thermo-chemical reactor with a multi-layered porous core

Abstract

A two-dimensional steady-state axisymmetric model is developed to analyze the performance of a thermo-chemical porous reactor used for syngas and subsequently hydrogen generation through the steam methane reforming (SMR) process. The finite volume method coupled with kinetics thermo-chemical reaction and local thermal non-equilibrium (LTNE) model with modified P1 approximation is employed to obtain the temperature distribution for both the fluid and porous zones. First, the effects of inlet mass flow rate, inlet steam to methane ratio, porosity, number of pores per inch (PPI), permeability, and reactor length on reactor performance are scrutinized. Next, to optimize the performance of the reactor, an artificial neural network (ANN) is developed to obtain the maximum hydrogen generation rate concerning the effective parameters. Finally, a two-layer porous foam is utilized as the catalyst zone to further improve the performance. Results show that increasing inlet flow rate leads to temperature decline and causes an incomplete reaction. Also, increasing porosity enhances heat absorption at the inlet and decreases radiative heat transfer through the porous foam. At a specified condition (ṁ= 0.25 kg.h−1, XCH4/XH2O = 1/3, and PPI = 10), increasing the porosity from 0.6 to 0.8 has increased hydrogen production by 27 %, while by a further increase of porosity to 0.9, hydrogen production decreased by 3 %. Results indicate up to 164 % increment in the performance of the optimal case compared to the base case. Furthermore, employing the two-layer porous foam with different PPIs could further increase hydrogen production, up to 20 %, and reduced the pressure drop.