Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/91791
DC FieldValueLanguage
dc.contributorDepartment of Mechanical Engineeringen_US
dc.creatorLee, YTen_US
dc.creatorWen, CYen_US
dc.creatorShih, YCen_US
dc.creatorLi, Zen_US
dc.creatorYang, ASen_US
dc.date.accessioned2021-12-13T04:03:09Z-
dc.date.available2021-12-13T04:03:09Z-
dc.identifier.issn0306-2619en_US
dc.identifier.urihttp://hdl.handle.net/10397/91791-
dc.language.isoenen_US
dc.publisherPergamon Pressen_US
dc.subjectAirflow managementen_US
dc.subjectCFD simulationen_US
dc.subjectData centeren_US
dc.subjectRack cooling indexen_US
dc.subjectReturn temperature indexen_US
dc.subjectSupply heat indexen_US
dc.titleNumerical and experimental investigations on thermal management for data center with cold aisle containment configurationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1016/j.apenergy.2021.118213en_US
dcterms.abstractThis study proposes the container data center with the featured cold aisle containment (CAC) as effective thermal control strategy. In design, the overhead downward flow system is implemented with a heat exchanger arranged right above the data center on the air side and an evaporative water chiller on the water side to form the cooling approach. The cold airflows and hot exhausts of racks are separately transported by the contained cold and hot aisles to alleviate the problem of cold and hot air mixing. The measurements of air temperature and velocity of racks are used to validate the prediction accuracy of the computational fluid dynamics (CFD) model. The performance metrics in terms of the rack cooling index (RCI), return temperature index (RTI), supply heat index (SHI) are used to examine the design effectiveness of the proposed test data center. The simulations are then extended to assess the air distribution and thermal management at varied supply air temperatures and velocities for a large-scale data center to be built in the green energy technology demonstration site of the Shalun smart green energy science city. Overall, the calculated average PUE of 1.38 for the large-scale data center is notably less than the average PUE of 1.59 from the results of 2020 data center industry survey, indicating the potential savings of cooling energy and cost. This paper demonstrates a generalized approach as an easily adaptable, cost-effective solution for data centers to be deployed in tropical and subtropical areas.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationApplied energy, 2021, In Press, 118213, https://doi.org/10.1016/j.apenergy.2021.118213en_US
dcterms.isPartOfApplied energyen_US
dcterms.issued2021-
dc.identifier.scopus2-s2.0-85119611252-
dc.identifier.eissn1872-9118en_US
dc.identifier.artn118213en_US
dc.description.validate202112 bcvcen_US
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera1098-n01-
dc.identifier.SubFormID43934-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextMinistry of Science and Technology, Taiwan, ROC (Contract No. MOST109-3116-F-027-001-CC1 and 110-2622-E-027-028)en_US
dc.description.pubStatusEarly releaseen_US
dc.date.embargo0000-00-00 (to be updated)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 0000-00-00 (to be updated)
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