A critical review of surrogate assisted robust design optimization
Robust design optimization (RDO) has been eminent, ascertaining optimal configuration of
engineering systems in presence of uncertainties. However, computational aspect of …
engineering systems in presence of uncertainties. However, computational aspect of …
Progress and prospects of artificial intelligence development and applications in supersonic flow and combustion
J Le, M Yang, M Guo, Y Tian, H Zhang - Progress in Aerospace Sciences, 2024 - Elsevier
Due to the significant improvement in computing power and the rapid advancement of data
processing technologies, artificial intelligence (AI) has introduced new tools and …
processing technologies, artificial intelligence (AI) has introduced new tools and …
Uncertainty quantification of turbulence model closure coefficients for transonic wall-bounded flows
The goal of this work is to quantify the uncertainty and sensitivity of commonly used
turbulence models in Reynolds-averaged Navier–Stokes codes due to uncertainty in the …
turbulence models in Reynolds-averaged Navier–Stokes codes due to uncertainty in the …
Constructing least-squares polynomial approximations
Polynomial approximations constructed using a least-squares approach form a ubiquitous
technique in numerical computation. One of the simplest ways to generate data for least …
technique in numerical computation. One of the simplest ways to generate data for least …
Uncertainty and sensitivity analysis of heat transfer in hypersonic three-dimensional shock waves/turbulent boundary layer interaction flows
J Lu, J Li, Z Song, W Zhang, C Yan - Aerospace Science and Technology, 2022 - Elsevier
Hypersonic shock waves/turbulent boundary layer interaction flow can cause severe
localized thermal loads, while the fluctuations in freestream conditions and inevitable …
localized thermal loads, while the fluctuations in freestream conditions and inevitable …
Stochastic multi-scale modeling of carbon fiber reinforced composites with polynomial chaos
A stochastic multi-scale modeling framework for uncertainty quantification of carbon fiber
reinforced composites with a non-intrusive method called Polynomial Chaos Decomposition …
reinforced composites with a non-intrusive method called Polynomial Chaos Decomposition …
Propagation of parameter uncertainty in SWAT: A probabilistic forecasting method based on polynomial chaos expansion and machine learning
Abstract Soil and Water Assessment Tool (SWAT) is one of the most widely used semi-
distributed hydrological models. Assessment of the uncertainties in SWAT outputs is a …
distributed hydrological models. Assessment of the uncertainties in SWAT outputs is a …
Analysis of Discrete Projection on Polynomial Spaces with Random Evaluations
We analyze the problem of approximating a multivariate function by discrete least-squares
projection on a polynomial space starting from random, noise-free observations. An area of …
projection on a polynomial space starting from random, noise-free observations. An area of …
[HTML][HTML] Bayesian uncertainty analysis of SA turbulence model for supersonic jet interaction simulations
LI ****, C Shusheng, CAI Fangjie, W Sheng… - Chinese Journal of …, 2022 - Elsevier
Abstract The Reynolds Averaged Navier-Stokes (RANS) models are still the workhorse in
current engineering applications due to its high efficiency and robustness. However, the …
current engineering applications due to its high efficiency and robustness. However, the …
Adaptive weighted least-squares polynomial chaos expansion with basis adaptivity and sequential adaptive sampling
An efficient framework to obtain stochastic models of responses with polynomial chaos
expansion (PCE) using an adaptive least-squares approach is presented in this paper. PCE …
expansion (PCE) using an adaptive least-squares approach is presented in this paper. PCE …