ABSTRACT
Thermal management of data centers remains a challenge because of their everincreasing power densities and decreasing server footprints. Current lack of dynamic control over global provisioning and local distribution of cooling resources often result in wasteful overcooling. These trends motivate this thesis research, which focuses on the development of a reliable and energy-efficient framework for allocating cooling resources to meet thermal management requirements, while minimizing energy consumption and adverse environmental impacts. A key component of energy-efficient thermal management is real-time accurate prediction of temperature distribution in data centers. This first section of this dissertation focuses on development and comparison of four Data Driven Modeling (DDM) methods, namely Artificial Neural Networks (ANN), Support Vector Regression (SVR), Gaussian Process Regression (GPR) and Proper Orthogonal Decomposition (POD). These DDM methods were trained on datasets generated from offline Computational Fluid Dynamics/Heat Transfer (CFD/HT) simulations for real-time prediction of temperature and airflow distributions in a data center. Using CFD simulation results to train DDMs transfers computational complexity from model execution (in CFD) to model setup and development. To generate the training data, a physics-based and experimentally validated room-level CFD/HT model was developed using the commercial software Future Facilities 6Sigma Room.
ABSTRACT
This work is focused on finding the impact of conflict on agricultural output in Guma Local Government Area...
Chapter One: Introduction
1.1 Background of the Study
The National Policy on Women, introduced by the Nigerian government, aims...
Chapter One: Introduction
1.1 Background of the Study...
ABSTRACT
Network Security is essential to any organization. This has been previously done by manual method. But this project is aimed at...
Abstract
Creating a good tax system implies that taxes should be collected regularly, consistently, conveniently and aff...
Background of the Study
Agriculture is the backbone of Nigeria's economy, employing over 70% of the population and c...
ABSTRACT
This study was carried out to examine the influence of class size on teaching and learni...
Background of the Study:
Government policies on infectious disease control are fundamental to safeguarding public health an...
Background of the Study
Parental attitudes have a profound influence on the educational choices made by students, particularly in communi...
BACKGROUND OF THE STUDY
Regardless of its natural endowment, no country can thrive unless it prioritizes human capital d...