Experimental And Numerical Investigation Of A New Silica-Gel/Water Packed Bed For Adsorption Cooling Applications

Keywords

Adsorption kinetics; Experimental; LTE; Novel bed; Numerical; SCP

Abstract

A novel packed bed is designed for application in adsorption cooling systems. The bed is modular in nature and thus can be scaled for a given cooling load. An experimental setup is built to measure the adsorption kinetics of the proposed bed under typical operating conditions. In addition, a transient three-dimensional local thermal equilibrium (LTE) model is developed to study heat and mass transfer inside the bed. The Darcy equation and linear driving force (LDF) model are solved simultaneously to account for inter-particle and intra-particle mass diffusion, respectively. Silica gel RD-2060/water is chosen as the working pair. The influence of the bed porosity, bed thickness, bed height and convective heat transfer coefficient on the specific cooling power (SCP) is investigated. Good agreement between the experimental measurements and the numerical results is obtained. The results show that a reduction in the bed porosity increases the adsorbent density and leads to a lower SCP. Additionally, a decrease in the bed thickness results in a pronounced increase in the SCP. However, a small bed thickness means a small module size, which leads to a high parasitic penalty in the metal-to-adsorbent mass ratio. The SCP is found to be insensitive to the convective heat transfer coefficient when it is over 400 W/m2·K, because the dominant thermal resistance is due to the low thermal conductivity of the adsorbent. The results show that the proposed bed produces a SCP of 350 W/kg of silica-gel after 500 s of adsorption.

Publication Date

1-1-2018

Publication Title

Proceedings of the Thermal and Fluids Engineering Summer Conference

Volume

2018-March

Number of Pages

1535-1546

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1615/TFEC2018.prm.021615

Socpus ID

85049963244 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85049963244

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