Abstract:
This work presents a comprehensive model of an alkaline water electrolysis cell for hydrogen
production to evaluate its electrochemical and fluid dynamic phenomena simultaneously. For
this, a 2D alkaline water electrolysis model was simulated on COMSOL MULTIPHYSICS
considering both gas and liquid phases. A Multiphysics approach is used in simulations and the
results are validated with the experimental data to ensure model’s accuracy. The CFD model
includes the equations for electric current conservation and the gas and liquid phase.
Polarization curves are generated to evaluate the AWE cell’s performance and electrochemical
response at different operating conditions. The CFD model allows to predict the distribution of
the generated gases, movement of the bubbles, and turbulence within the cell as well as the
impact of current density, electrolyte flow rate, electrode-diaphragm distance, and other
parameters on the gas profiles. While the CFD model provides valuable insights into alkaline
water electrolysis, combining it with a neural network model further enhances its potential for
better cell design and performance. The trained ANN accurately predicted the complex
relationships between input and output parameters with an R² value of 0.99922. The combined
CFD-ANN approach provides comprehensive understanding of the AWE cell’s behavior,
further optimizing its design for efficient hydrogen production.
