Ha-Rok Bae (Advisor), Ramana Grandhi (Committee Member), Joseph Slater (Committee Member)
Master of Science in Engineering (MSEgr)
In this thesis, the Locally-Optimized Covariance (LOC) Kriging method is developed. This method represents a flexible surrogate modeling approach for approximating a non-stationary Kriging covariance structures for deterministic responses. The non-stationary covariance structure is approximated by aggregating multiple stationary localities. The aforementioned localities are determined to be statistically significant utilizing the Non-Stationary Identification Test. This methodology is applied to various demonstration problems including simple one and two-dimensional analytical cases, a deterministic fatigue and creep life model, and a five-dimensional fluid-structural interaction problem. The practical significance of LOC-Kriging is discussed in detail and is directly compared to stationary Kriging considering computational cost and accuracy.
Department or Program
Department of Mechanical and Materials Engineering
Year Degree Awarded
Copyright 2016, all rights reserved. My ETD will be available under the "Fair Use" terms of copyright law.