(372e) Two-Fluid Model–Based Computational Fluid Dynamics (CFD-TFM) Study of Chemical Looping Combustion

Fossil fuel-based energy production is the primary source of greenhouse gas emissions [1], particularly carbon dioxide (CO₂). Therefore, effective strategies are urgently needed to reduce CO₂ emissions [2]. While several techniques exist for CO₂ separation from combustion exhaust gas streams, many are energy-intensive [3]. Chemical looping combustion (CLC) has emerged as one of the most economical combustion technologies, offering low energy penalty, inherent CO₂separation, NO_x pollution control, and a high efficiency of up to 100% [4]. In CLC, oxygen needed for fuel combustion is transferred between two fluidized-bed reactors via metal oxide particles known as oxygen carriers (OCs), preventing direct contact between air and fuel. This results in efficiently separable exhausts that contain only water vapor and CO₂. The rapid expansion and effective commercialization of this process require robust first-principles models to understand better the fluid dynamics, transport mechanisms, and thermodynamics of CLC. Such models are also necessary for determining the optimal operating conditions and developing control systems for efficient and safe operation. However, because of the underlying physics of gas-solid multiphase flows, considering the catalytic behavior of solids in CLC increases the complexity of models and renders the models numerically stiff.

In this work, we model the reduction of NiO as the OC in the CLC process. We consider a complete chemistry scheme of the process, including non-catalytic reactions of partial and complete combustion, along with seven potential paths for catalytic reactions such as water gas shift, steam reforming, and dry reforming, to name a few. To deal with the complexity and excessively time-consuming computations, we use the open-source code Multiphase Flow with Interphase eXchanges (MFiX) [5,6], which has been developed specifically for modeling reacting multiphase systems. This provides a robust, generic, and ready-to-use model that takes care of the hydrodynamics of the process. To integrate the inclusive chemistry scheme of the reduction phase into MFiX, we use the Levenspiel approach to account for solid conversion. The model is then evaluated using experimental data extracted from the literature [7,8]. The results show a successful integration of a well-detailed and realistic chemistry scheme of the CLC process into backend CFD-coded software. This allows investigation of the process by modeling in MFiX as a robust and time-efficient medium for the CLC process optimization.

References:

[1] Al-Absi, A.A., Domin, A., Mohamedali, M., Benneker, A.M. and Mahinpey, N., 2023. CO2 capture using in-situ polymerized amines into pore-expanded-SBA-15: Performance evaluation, kinetics, and adsorption isotherms. Fuel, 333, p.126401.

[2] Akram, W., Sanjay and Hassan, M.A., 2021. Chemical looping combustion with nanosize oxygen carrier: a review. International Journal of Environmental Science and Technology, 18(3), pp.787-798.

[3] Kheirinik, M., Ahmed, S. and Rahmanian, N., 2021. Comparative techno-economic analysis of carbon capture processes: Pre-combustion, post-combustion, and oxy-fuel combustion operations. Sustainability, 13(24), p.13567.

[4] Zhao, Y.J., Zhang, Y.K., Cui, Y., Duan, Y.Y., Huang, Y., Wei, G.Q., Mohamed, U., Shi, L.J., Yi, Q. and Nimmo, W., 2022. Pinch combined with exergy analysis for heat exchange network and techno-economic evaluation of coal chemical looping combustion power plant with CO2 capture. Energy, 238, p.121720.

[5] Syamlal, M., Rogers, W. and OBrien, T.J., 1993. MFIX documentation theory guide (No. DOE/METC-94/1004). USDOE Morgantown Energy Technology Center (METC), WV (United States).

[6] Syamlal, M., 1998. MFIX documentation: Numerical technique. Rep. DOE/MC/31346, 5824, p.80.

[7] Iliuta, I., Tahoces, R., Patience, G.S., Rifflart, S. and Luck, F., 2010. Chemical‐looping combustion process: Kinetics and mathematical modeling. AIChE journal, 56(4), pp.1063-1079.

[8] Zhou, Z., Han, L. and Bollas, G.M., 2015. Model-assisted analysis of fluidized bed chemical-looping reactors. Chemical Engineering Science, 134, pp.619-631.