Biological H2(g) Production and Modelling with Computational Fluid Dynamics (CFD)

Abstract

In this study, bio-hydrogen gas [bio-H2(g)] production and modeling with a three-phase computational fluid dynamics (CFD) model, heat and mass transfer of bio-hydrogen production, reaction kinetics, and fluid dynamics; It was investigated by dark fermentation process in an anaerobic continuous plug flow reactor (ACPFR). The three-phase CFD model was used to determine the bio-H2(g) production in an ACPFR. The effect of different operating parameters, increasing hydrolic retention times (HRTs) (1, 2, 4, 8, and 12 days), different pH values (4.0, 5.0, 6.0, 7.0, and 8.0), and increasing feed rate as organic loading rates (OLRs) (0.5, 1.0, 2.0, 4.0, 8.0 and 10.0 g COD/l.d) on the bio-H2(g) production rates were operated in municipal sludge wastes (MSW) with Thermoanaerobacterium thermosaccharolyticum SP-H2 methane bacteria during dark fermentation for bio-H2(g) production. The effect of HRT, pH, and feed rate on the bioH2(g) efficiencies and H2(g) production rates were examined in the simulation stage. Production of volatile fatty acids (VFAs) namely, acetic acids, butyric acids, and propionic acids were important points influencing the bio-H2(g) production yields. The artificial neural network (ANN) model substrate inhibition on bio-H2(g) production to the methane (CH4) bacteria was also investigated. The reaction kinetics model used Thermotoga neapolitana microorganisms with the Andrews model of substrate inhibition. Furthermore, the ANN model was well-fitted to the experimental data to simulate the bio-H2(g) production from chemical oxygen demand (COD).