dc.contributor.advisor | Agonafer, Dereje | |
dc.creator | Karmokar, Pritam | |
dc.date.accessioned | 2016-01-26T23:49:18Z | |
dc.date.available | 2016-01-26T23:49:18Z | |
dc.date.created | 2015-12 | |
dc.date.issued | 2015-12-07 | |
dc.date.submitted | December 2015 | |
dc.identifier.uri | http://hdl.handle.net/10106/25466 | |
dc.description.abstract | This 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.mimetype | application/pdf | |
dc.language.iso | en_US | |
dc.subject | Evaporative cooling | |
dc.subject | Artificial neural networks | |
dc.title | A Study on Evaporative Cooling for data centers & Artificial Neural Network Modeling | |
dc.title.alternative | A Study on Evaporative Cooling for data centers and Artificial Neural Network Modeling | |
dc.type | Thesis | |
dc.date.updated | 2016-01-26T23:50:21Z | |
thesis.degree.department | Mechanical and Aerospace Engineering | |
thesis.degree.grantor | The University of Texas at Arlington | |
thesis.degree.level | Masters | |
thesis.degree.name | Master of Science in Mechanical Engineering | |
dc.type.material | text | |