Title:
An Approach for the Robust Design of Data Center Server Cabinets

dc.contributor.advisor Allen, Janet K.
dc.contributor.advisor Joshi, Yogendra
dc.contributor.author Rolander, Nathan Wayne en_US
dc.contributor.committeeMember Mistree, Farrokh
dc.contributor.committeeMember Garimella, Srinivas
dc.contributor.department Mechanical Engineering en_US
dc.date.accessioned 2006-01-18T22:27:06Z
dc.date.available 2006-01-18T22:27:06Z
dc.date.issued 2005-11-29 en_US
dc.description.abstract The complex turbulent flow regimes encountered in many thermal-fluid engineering applications have proven resistant to the effective application of systematic design because of the computational expense of model evaluation and the inherent variability of turbulent systems. In this thesis the integration of the Proper Orthogonal Decomposition (POD) for reduced order modeling of turbulent convection with the application of robust design principles is proposed as a practical design approach. The POD has been used successfully to create low dimensional steady state flow models within a prescribed range of parameters. The underlying foundation of robust design is to determine superior solutions to design problems by minimizing the effects of variation on system performance, without eliminating their causes. The integration of these constructs utilizing the compromise Decision Support Problem (DSP) results in an efficient, effective robust design approach for complex turbulent convective systems. The efficacy of the approach is illustrated through application to the configuration of data center server cabinets. Data centers are computing infrastructures that house large quantities of data processing equipment. The data processing equipment is stored in 2 m high enclosures known as cabinets. The demand for increased computational performance has led to very high power density cabinet design, with a single cabinet dissipating up to 20 kW. The computer servers are cooled by turbulent convection and have unsteady heat generation and cooling air flows, yielding substantial inherent variability, yet require some of the most stringent operational requirements of any engineering system. Through variation of the power load distribution and flow parameters, such as the rate of cooling air supplied, thermally efficient configurations that are insensitive to variations in operating conditions are determined. This robust design approach is applied to three common data center server cabinet designs, in increasing levels of modeling detail and complexity. Results of the application of this approach to the example problems studied show that the resulting thermally efficient configurations are capable of dissipating up to a 50% greater heat load and 15% decrease in the temperature variability using the same cooling infrastructure. These results are validated rigorously, including comparison of detailed CFD simulations with experimentally gathered temperature data of a mock server cabinet. Finally, with the approach validated, augmentations to the approach are considered for multi-scale design, extending approaches domain of applicability. en_US
dc.description.degree M.S. en_US
dc.format.extent 6364738 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/7592
dc.language.iso en_US
dc.publisher Georgia Institute of Technology en_US
dc.subject POD en_US
dc.subject Data center
dc.subject Optimization
dc.subject Robust design
dc.subject.lcsh Heat Convection Mathematical models en_US
dc.subject.lcsh Turbulence en_US
dc.subject.lcsh Decision support systems en_US
dc.subject.lcsh Electronic equipment enclosures Design en_US
dc.subject.lcsh Fluid dynamics en_US
dc.subject.lcsh Heat engineering Design en_US
dc.title An Approach for the Robust Design of Data Center Server Cabinets en_US
dc.type Text
dc.type.genre Thesis
dspace.entity.type Publication
local.contributor.advisor Joshi, Yogendra
local.contributor.corporatename George W. Woodruff School of Mechanical Engineering
local.contributor.corporatename College of Engineering
relation.isAdvisorOfPublication 63ef328b-076b-44b7-92a9-0f7dd03fa1fa
relation.isOrgUnitOfPublication c01ff908-c25f-439b-bf10-a074ed886bb7
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
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