Surrogate models are popular tool to approximate the functional relationship of expensive
simulation models in multiple scientific and engineering disciplines. Successful use of …

A variable-fidelity method can remarkably improve the efficiency of a design optimization
based on a high-fidelity and expensive numerical simulation, with assistance of lower-fidelity …

In design optimization of complex systems, the surrogate model approach relying on
progressively enriched Design of Experiments (DOE) avoids efficiency problems …

The efficient global optimization method (EGO) based on kriging surrogate model and
expected improvement (EI) has received much attention for optimization of high-fidelity …

By fusing aerodynamic data from multiple sources, multi-fidelity methods can well balance
model accuracy and computational cost. To extend multi-fidelity models for predicting …

To reduce the computational burden of aerodynamic design optimization, a multi-fidelity
expected improvement (MFEI) method is developed, based on the error analysis of a multi …

The polynomial chaos expansion (PCE) approaches have drawn much attention in the field
of simulation-based uncertainty quantification (UQ) of stochastic problem. In this paper, we …

Sampling efficiency is important for simulation-based design optimization. While Bayesian
optimization (BO) has been successfully applied in engineering problems, the cost …

Computational fluid dynamics (CFD) simulations are nowadays been intensively used in
aeronautical industries to analyse the aerodynamic performance of different aircraft …

In the current paper efficient uncertainty quantification (UQ) of high dimensional stochastic
fields is performed via a bi-fidelity surrogate model. The method is based on combination of …