Academic Journal

Computational Fluid Dynamics Modeling and Validating Experiments of Airflow in a Data Center.

Bibliographic Details
Title: Computational Fluid Dynamics Modeling and Validating Experiments of Airflow in a Data Center.
Authors: Wibron, Emelie, Ljung, Anna-Lena, Lundström, T. Staffan
Source: Energies (19961073); Mar2018, Vol. 11 Issue 3, p644, 15p
Abstract: The worldwide demand on data storage continues to increase and both the number and the size of data centers are expanding rapidly. Energy efficiency is an important factor to consider in data centers since the total energy consumption is huge. The servers must be cooled and the performance of the cooling system depends on the flow field of the air. Computational Fluid Dynamics (CFD) can provide detailed information about the airflow in both existing data centers and proposed data center configurations before they are built. However, the simulations must be carried out with quality and trust. The k--ε model is the most common choice to model the turbulent airflow in data centers. The aim of this study is to examine the performance of more advanced turbulence models, not previously investigated for CFD modeling of data centers. The considered turbulence models are the k--ε model, the Reynolds Stress Model (RSM) and Detached Eddy Simulations (DES). The commercial code ANSYS CFX 16.0 is used to perform the simulations and experimental values are used for validation. It is clarified that the flow field for the different turbulence models deviate at locations that are not in the close proximity of the main components in the data center. The k--ε model fails to predict low velocity regions. RSM and DES produce very similar results and, based on the solution times, it is recommended to use RSM to model the turbulent airflow data centers. [ABSTRACT FROM AUTHOR]
Subject Terms: COMPUTATIONAL fluid dynamics, AIR flow, SERVER farms (Computer network management), COOLING systems, ENERGY consumption
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ISSN: 19961073
DOI: 10.3390/en11030644
Database: Complementary Index