Application of computational fluid dynamics for modeling of Fischer-Tropsch synthesis as a sustainable energy resource in different reactor configurations: A review

Increasing the global energy demand motivates the search for renewable and clean energy resources. Fischer-Tropsch synthesis (FTS) is one of these sources, which converts syngas (a mixture of CO and H2) to a wide range of hydrocarbons . Liquid transportation fuels produced via FTS from biomass-derived syngas introduce an attractive, clean, carbon-neutral, and sustainable energy source. Reactor and catalyst designs play a significant role in the improvement of FTS efficiency. Flow hydrodynamics coupled with reaction kinetics makes this process challenging. Numerical methods such as computational fluid dynamics (CFD) can help us effectively understand the fluid dynamics within FT reactor. The main objective of CFD simulation for FTS can be summarized in three points (1) to analyze the conservation laws (mass, heat, and momentum transport) coupled with the catalytic reactions in the reactor, (2) to optimize the operating conditions to maximize the catalytic activity and selectivity to desired products, and (3) to support the reactor design and engineering. A CFD code consists of four steps: geometry generation, meshing, solver, and post-processing. Emerging data-driven techniques were also reviewed in this work to analyze the fluid dynamics of FTS. FTS is mainly operated in fixed bed, slurry bubble column, fluidized bed, micro-structured, and membrane reactors. This review aims to analyze the capability of CFD simulation in predicting the FTS performance in different reactor types and address the present challenges. •FTS process is investigated as a sustainable energy resource.•Hydrodynamics, reaction kinetics, and reactor modeling of FTS are discussed using CFD.•Different methods are investigated for the simulation of multiphase and turbulent flows.•CFD simulation results of FTS in different reactor categories are critically analyzed.•The application of data-driven methods is presented for analysis of the fluid dynamics.