Graduation Semester and Year

2015

Language

English

Document Type

Thesis

Degree Name

Master of Science in Mechanical Engineering

Department

Mechanical and Aerospace Engineering

First Advisor

Dereje Agonafer

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.

Keywords

Evaporative cooling, Artificial neural networks

Disciplines

Aerospace Engineering | Engineering | Mechanical Engineering

Comments

Degree granted by The University of Texas at Arlington

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