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Abstract

The change of the transient indoor temperature is crucial to evaluate electrical power consumption of a heat pump and thermal comfort of the room. Computational Fluid Dynamics (CFD) model can provide the most comprehensive information in transient indoor temperature simulations. In CFD models, the transient flow and temperature fields are fully coupled. This coupling leads to high computation cost and time, which limits the CFD application in practice. A segregated CFD model was then proposed to speed up the computation. However, such model is not very accurate during the transient analysis. In this paper, a semi-coupled CFD model combining advantages of the fully-coupled CFD model and the segregated CFD model was proposed. In this CFD model, the flow and the temperature fields are firstly solved by fully coupled simulation during the transient start up period and then the segregated CFD is used for the transient temperature rising simulation. This method can reduce the computation time without losing the simulation accuracy. The transient indoor temperature is studied using the proposed method and the results are compared with those obtained from both fully-coupled and segregated CFD models. The hot air temperature is first calculated using a lumped-parameter method, and then it is applied as an initial boundary condition in the CFD models. The comparison results show that the proposed semi-coupled CFD model shows a promising capability of capturing the critical transient thermal responses for the air-conditioning room, and it can effectively reduce the computing time with an acceptable accuracy.

Item Type:	Conference Publication
Authors/Creators:	Zhang, L and Yu, X and Lv, Q and Cao, F and Wang, X
Keywords:	Heat pump, energy consumption, HVAC room, computational fluid dynamics
Journal or Publication Title:	Energy Procedia
Publisher:	Elsevier
ISSN:	1876-6102
DOI / ID Number:	https://doi.org/10.1016/j.egypro.2019.02.145
Copyright Information:	Copyright 2019 the AuthorsCC BY-NC-ND license
Related URLs:	Google Scholar: Wang, X UTAS Profile: Wang, X
Item Statistics:	View statistics for this item

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