Experimental and Computational Investigations of the Thermal Environment in a Small Operational Data Center for Potential Energy Efficiency Improvements

The share of equipment and power use in smaller data centers (DCs) is comparable with that of more massive counterparts. However, they grabbed less attention in the literature despite being less energy-efficient. This study highlights the challenges of setting up a computational fluid dynamics (CFD)...

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Veröffentlicht in:Journal of electronic packaging 2020-09, Vol.142 (3)
Hauptverfasser: Turkmen, Ismail, Mercan, Cem Ahmet, Erden, Hamza Salih
Format: Artikel
Sprache:eng
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Zusammenfassung:The share of equipment and power use in smaller data centers (DCs) is comparable with that of more massive counterparts. However, they grabbed less attention in the literature despite being less energy-efficient. This study highlights the challenges of setting up a computational fluid dynamics (CFD) model of a 180-m2 small-size high-performance computing (HPC) DC and the validation procedure leading to a reasonably accurate model for the investigation of the thermal environment and potential energy efficiency improvements. Leaky floors, uneven placement of computing equipment and perforated tiles preventing separation of hot and cold air, low-temperature operation, and excessive cooling capacity and fan power were identified sources of energy inefficiency in the DC. Computational fluid dynamics model predictions were gradually improved by using experimental measurements for various boundary conditions (BCs) and detailed geometrical representation of large leakage openings. Eventually, the model led to predictions with an error of less than 1 °C at the rack inlet and less than 5 °C at the rack outlet. The ultimate objective was to use the validated CFD model to test various energy efficiency measures in the form of operational or design changes in line with the best practices. Impact of leakage between the raised floor and the room, reduced airflow rate, cold-aisle and hot-aisle separation, workload consolidation, and higher temperature operation were among the phenomena tested by using the validated CFD model. The estimated power usage effectiveness (PUE) value reduced from 1.95 to 1.40 with the proposed energy efficiency measures.
ISSN:1043-7398
1528-9044
DOI:10.1115/1.4047845