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Reduced-order modeling framework for improving spatial resolution of data center transient air temperatures

  • Georgia Institute of Technology
  • IBM

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

A proper orthogonal decomposition (POD)-based modeling framework is developed for improving the spatial resolution of transient rack air temperature data collected in a heterogeneous data center (DC) facility. Blocking cooling air inflow into racks periodically, three sets of transient temperature data are collected at the outlets of electronic equipment residing in three different racks. Using various combinations of initial discrete data as ensembles, the capability of the proposed POD/ interpolation framework for predicting new temperature data is demonstrated. The accuracy of POD-based temperature predictions is validated by comparing it to corresponding experimental data. The root mean square deviations between experimental data and POD-based predictions are found to be on the order of 5%.

Original languageEnglish
Title of host publication29th Annual IEEE Semiconductor Thermal Measurement and Management Symposium, SEMI-THERM 2013 - Proceedings
Pages216-222
Number of pages7
DOIs
StatePublished - 2013
Event29th Annual IEEE Semiconductor Thermal Measurement and Management Symposium, SEMI-THERM 2013 - San Jose, CA, United States
Duration: Mar 17 2013Mar 21 2013

Publication series

NameAnnual IEEE Semiconductor Thermal Measurement and Management Symposium
ISSN (Print)1065-2221

Conference

Conference29th Annual IEEE Semiconductor Thermal Measurement and Management Symposium, SEMI-THERM 2013
Country/TerritoryUnited States
CitySan Jose, CA
Period03/17/1303/21/13

Keywords

  • Data center
  • dynamic events
  • proper orthogonal decomposition
  • transient temperature measurement

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