Abstract

The application of computational fluid dynamics (CFDs) in the area of porous media and adsorption cooling system is becoming more practical due to the significant improvement in computer power. The results from previous studies have shown that CFD can be useful tool for predicting the water vapour flow pattern, temperature, heat transfer and flow velocity and adsorption rate. This paper investigates the effect of silica gel granular size on the water adsorption rate using computational fluid dynamics and gravimetric experimental (TGA) method.

Highlights

  • The adsorption properties of silica gel have been studied for many years as silica gel is used in many industries including adsorption cooling systems

  • The computational fluid dynamics (CFDs) simulation determines the distribution of water vapour molecules in the flow vapour phase and the adsorption of adsorbed vapour molecules on the silica gel surfaces

  • A CFD model was developed for simulating the adsorpitivity of water vapour on silica gel granules and used to study the effect of granule sizes indicating that reducing the granule size increases the adsorpitivity

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Summary

Introduction

The adsorption properties of silica gel have been studied for many years as silica gel is used in many industries including adsorption cooling systems. The purpose of this work was to study the effect of granule size on the adsorption properties of silica gel by using CFD and comparing the simulation results to those obtained experimentally. The effects of silica gel size and properties have been studied using the porous media approaches by application of modified Navier-Stokes equations and the continuity equation. In this set of equations, an additional term is used describing the porosity distribution in order to take into account the porous media packing geometry. Studies of fluid dynamics and heat transfer in adsorber beds date back to the early twentieth century [1] The early investigation of flow in porous media packed beds provided mainly such bulk information as pressure drop correlations. Similar correlations were proposed by Molerus [3]

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