This article presents the transport input properties necessary for alkaline water electrolyzer multiphysic modeling (CFD). This article provides experimental data and the needed correlations of the parameter (electrical conductivity, density, viscosity, heat capacity, heat and mass transfer diffusion coefficients used in multiphysical modeling depending on temperature and mass fraction for two classical alkaline electrolytes (KOH, NaOH) over a wide range of temperature and mass fraction. Thus, the different involved electrodes boundary layers can be calculated with precision. First of all, 6 usual inputs liquid electrolyte parameters (density, specific heat, electric and thermal conductivity, viscosity, mass diffusivity) are given as a function of temperature and electrolyte mass fraction (for KOH and NaOH). Different interpolation models from various authors and also original are compared to experimental rough data. The goal of this article is to give to the modeler the needed correlations to allow the simulation of the alkaline water electrolysis.

Hydrogen storage is a promising technology for storage of renewable energy resources. Despite its high energy density potential, the development of hydrogen storage has been impeded, mainly due to its significant cost. Although its cost is governed mainly by electrical energy expense, especially for hydrogen produced with alkaline water electrolysis, it is also driven by the value of the cell tension. The most common means of electrolyzer improvement is the use of an electrocatalyst, which reduces the energy required for electrochemical reaction to take place. Another efficient means of electrolyzer improvement is to use the Computational Fluid Dynamics (CFD)-assisted design that allows the comprehension of the phenomena occurring in the electrolyzer and also the improvement in the electrolyzer’s efficiency. The designed two-phase hydrodynamics model of this study has been compared with the experimental results of velocity profiles measured using Laser Doppler Velocimetry (LDV) method. The simulated results were in good agreement with the experimental data in the literature. Under the good fit with experimental values, it is efficient to introduce a new physical bubble transfer phenomenon description called “bubble diffusion”.