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

Emelie Wibron, Anna-Lena Ljung and T. Staffan Lundström
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Emelie Wibron: Division of Fluid and Experimental Mechanics, Luleå University of Technology, SE-971 87 Luleå, Sweden
Anna-Lena Ljung: Division of Fluid and Experimental Mechanics, Luleå University of Technology, SE-971 87 Luleå, Sweden
T. Staffan Lundström: Division of Fluid and Experimental Mechanics, Luleå University of Technology, SE-971 87 Luleå, Sweden

Energies, 2018, vol. 11, issue 3, 1-15

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 – ? 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 – ? 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 – ? 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.

Keywords: data center; airflow; computational fluid dynamics (CFD); turbulence models (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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