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dc.contributor.advisorAgonafer, Dereje
dc.creatorKarmokar, Pritam
dc.date.accessioned2016-01-26T23:49:18Z
dc.date.available2016-01-26T23:49:18Z
dc.date.created2015-12
dc.date.issued2015-12-07
dc.date.submittedDecember 2015
dc.identifier.urihttp://hdl.handle.net/10106/25466
dc.description.abstractThis study mainly aims at exploring how, one of the best “Green” solutions for IT equipment cooling aka Evaporative Cooling, can be optimized for better future deployment. Also, this study focuses on ways to deploy Artificial Neural Network models to Dynamic Systems. Today, SERVERS are one of most important devices that our technology driven world cannot do without. Efficiently cooling these delicate yet highly power dense beasts, while being environment friendly is one of our prime concerns. This study is a combination of two deceptively divergent works. First, on exploring the workings of this technique by investigating one such Evaporative Cooling unit for optimization purposes; and second, an exhaustive study and analysis on Artificial Neural Networks Modeling.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectEvaporative cooling
dc.subjectArtificial neural networks
dc.titleA Study on Evaporative Cooling for data centers & Artificial Neural Network Modeling
dc.title.alternativeA Study on Evaporative Cooling for data centers and Artificial Neural Network Modeling
dc.typeThesis
dc.date.updated2016-01-26T23:50:21Z
thesis.degree.departmentMechanical and Aerospace Engineering
thesis.degree.grantorThe University of Texas at Arlington
thesis.degree.levelMasters
thesis.degree.nameMaster of Science in Mechanical Engineering
dc.type.materialtext


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