Sharif Rahman

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This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal(More)
To my family and friends ii If you can't explain it simply, you don't understand it well enough. Albert Einstein iii ABSTRACT The objective of this study is to develop a new modified Bayesian Kriging (MBKG) surrogate modeling method that can be used to carry out confidence-based reliability-based design optimization (RBDO) for problems in which simulation(More)
ACKNOWLEDGEMENTS I would first and foremost like to thank my PH.D. supervisor, Dr. Jia Lu. He is brilliant as a teacher, mentor, and research collaborator, and provided incredible support to my research. I owe a lot to my wife Rong. Without her tremendous love, support, encouragement and sacrifice on her own career, I'd never be able to finish this work. I(More)
This article advocates factorized and hybrid dimensional decompositions (FDD/HDD), as alternatives to analysis-of-variance dimensional decomposition (ADD), for second-moment statistical analysis of multivariate functions. New formulas revealing the relationships between component functions of FDD and ADD are proposed. While ADD or FDD is relevant when a(More)
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