TL;DR
A model selection algorithm using pilot samples to choose a combination of models which minimizes the theoretical error bound and total cost, based on the theoretically derived optimal sample size for each model in the multifidelity ensemble is proposed.
This work proposes and compares several approaches to solve the Boltzmann equation with uncertain parameters, including multilevel Monte Carlo and multifidelity methods that employ an asymptotic-preserving-hybrid scheme for the deterministic Boltzmann model and provides practical guidelines for selection between APH-ba...
We develop a multifidelity method for fusing low-resolution simulations with computationally expensive high-resolution simulations, which are run infrequently and are therefore prone to bias. We formulate this fusion as a constrained optimization under missing-not-at-random (MNAR) selection bias. This formulation searc...
This paper proposes ASTRO-BFDF, an adaptive sampling trust-region method specifically designed for unconstrained bi-fidelity stochastic derivative-free optimization problems and proves that the iterates generated by ASTRO-BFDF converge to a first-order stationary point almost surely.
Quasi-Monte Carlo sampling is a numerical integration method that uses points with a space-filling property in $[0,1]^s$ designed to give better estimates than plain Monte Carlo methods do. For integrands of bounded variation in the sense of Hardy and Krause, errors of $O(n^{-1+\epsilon})$ for any $\epsilon>0$ are obta...
Floor response spectra (FRS) are essential tools for the design of non-structural elements (such as equipment or components). Given the various physical phenomena influencing FRS, high-fidelity (HF) mechanical models of the primary structure may be required to estimate them. Since numerical simulations based on such mo...
Risk-averse design optimization with conditional value-at-risk (CVaR) constraints requires accurate tail estimates, but repeated high-fidelity (HF) evaluations are costly. We propose a multifidelity (MF) tail-region correction method that uses dimensionally decomposed generalized polynomial chaos expansion (DD-GPCE) as...
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