Multi-Physics CFD Simulation of Heat and Mass Transfer in Solar-Assisted Biogas Upgrading Reactor Systems
Keywords:
Computational Fluid Dynamics, Biogas Upgrading, Heat and Mass Transfer, Solar-Assisted Reactor, Renewable Energy, Methane PurificationAbstract
The upgrading of biogas into high-quality biomethane is essential for improving renewable energy utilization and reducing greenhouse gas emissions in sustainable energy systems. This study presents a multi-physics computational fluid dynamics (CFD) simulation of heat and mass transfer phenomena in solar-assisted biogas upgrading reactor systems. The proposed investigation integrates fluid flow dynamics, thermal energy transfer, gas absorption behavior, and solar energy utilization within a unified numerical modeling framework to evaluate reactor performance under varying operational conditions. A three-dimensional CFD model was developed to simulate gas-liquid interaction, temperature distribution, solar heat absorption, and contaminant separation mechanisms during biogas upgrading processes. Key operational parameters, including solar irradiation intensity, gas flow rate, reactor geometry, absorbent concentration, and operating temperature, were analyzed to determine their influence on methane enrichment efficiency and carbon dioxide removal performance. Simulation results demonstrated that optimized solar-assisted heating significantly enhances mass transfer rates and improves biogas upgrading efficiency by promoting favorable thermodynamic conditions within the reactor system. The study further revealed that controlled thermal distribution and improved flow uniformity contribute to reduced energy consumption and enhanced operational stability. Comparative analysis indicated superior methane purification performance and improved energy efficiency compared to conventional non-solar-assisted upgrading methods. Additionally, the integration of multi-physics CFD modeling enabled accurate prediction of coupled transport phenomena and supported reactor design optimization for large-scale renewable energy applications.