![]() The detailed two-dimensional electrochemical and flow/transport simulations further reveal that in the presence of hydrogen dilution in the fuel stream, hydrogen is depleted at the reaction surface resulting in substantial kinetic polarization and hence a lower current density that is limited by hydrogen transport from the fuel stream to the reaction = separation. Our approach opens the door to applying machine learning to large-scale physical modeling tasks like airplane design and climate prediction. ![]() The predicted polarization cubes under hydrogen dilution conditions are found to be in qualitative agreement with recent experiments reported in the literature. Here we show that using machine learning inside traditional fluid simulations can improve both accuracy and speed, even on examples very different from the training data. Subsequently, the model is applied to explore hydrogen dilution effects in the anode feed. The numerical model is validated against published experimental data with good agreement. Optimize Engineering Design with CFD Modeling Services Computational Fluid Dynamics Simulation & Numerical Analysis Call 81822236 For Free Consultation. A single set of conservation equations valid for flow channels, gas-diffusion electrodes, catalyst layers and the membrane region are developed and numerically solved using a finite-volume-based computational fluid dynamics (CFD) technique. The model accounts simultaneously for electrochemical kinetics, current distribution, hydrodynamics and multi-component transport. ![]() A transient, multi-dimensional model has been developed to simulate proton exchange membrane (PEM) fuel cells. The comparison of computational costs gives a recommendation for modeling thermal radiation in packed beds: the S2S model is to be preferred over the DOM radiation model, which need 7.5 and 35 additional calculation time in comparison to the model neglecting radiation, respectively. ![]()
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