In many situations across computational science and engineering, multiple computational
models are available that describe a system of interest. These different models have varying …

In the present work, a multi-fidelity surrogate-based optimization framework is proposed, and
then applied to the robust optimizations for airfoil and wing under uncertainty of Mach …

Global sensitivity analysis (GSA), particularly for Sobol index, is a powerful tool to quantify
the variation of model response sourced from the uncertainty of input variables over the …

This work presents multi-fidelity multi-objective infill-sampling surrogate-assisted
optimization for airfoil shape optimization. The optimization problem is posed to maximize …

Resided at the intersection of multi-fidelity optimization (MFO) and Bayesian optimization
(BO), MF BO has found a niche in solving expensive engineering design optimization …

The accuracy of the computational fluid dynamics (CFD) to model the airflow around the
buildings in the atmospheric boundary layer (ABL) is directly linked to the utilized turbulence …

In this paper we present a multi-fidelity (MF) extension of non-intrusive polynomial chaos
based on regression (point collocation) for uncertainty quantification purposes. The …

The presence of uncertainties is inevitable in engineering design and analysis, where failure
in understanding their effects might lead to the structural or functional failure of the systems …

Multi-fidelity approaches combine different models built on a scarce but accurate dataset
(high-fidelity dataset), and a large but approximate one (low-fidelity dataset) in order to …

The ever-increasing demands for risk-free, resource-efficient and environment-friendly air
vehicles motivate the development of advanced design methodology. As a particularly …