Recent advances in surrogate modeling methods for uncertainty quantification and propagation

C Wang, X Qiang, M Xu, T Wu - Symmetry, 2022 - mdpi.com
Surrogate-model-assisted uncertainty treatment practices have been the subject of
increasing attention and investigations in recent decades for many symmetrical engineering …

Static homotopy response analysis of structure with random variables of arbitrary distributions by minimizing stochastic residual error

H Zhang, X Xiang, B Huang, Z Wu, H Chen - Computers & Structures, 2023 - Elsevier
The modelling of realistic engineering structures with uncertainties often involves various
probabilistic distribution types, which bring forward higher requirements for the generality of …

Uncertainty quantification of spatially uncorrelated loads with a reduced-order stochastic isogeometric method

C Ding, KK Tamma, H Lian, Y Ding, TJ Dodwell… - Computational …, 2021 - Springer
This work models spatially uncorrelated (independent) load uncertainty and develops a
reduced-order Monte Carlo stochastic isogeometric method to quantify the effect of the load …

An nth high order perturbation-based stochastic isogeometric method and implementation for quantifying geometric uncertainty in shell structures

C Ding, KK Tamma, X Cui, Y Ding, G Li… - Advances in Engineering …, 2020 - Elsevier
This paper presents an n-th high order perturbation-based stochastic isogeometric Kirchhoff–
Love shell method, formulation and implementation for modeling and quantifying geometric …

Stochastic isogeometric buckling analysis of composite shell considering multiple uncertainties

P Hao, H Tang, Y Wang, T Wu, S Feng… - Reliability Engineering & …, 2023 - Elsevier
An efficient stochastic isogeometric analysis (SIGA) framework considering multiple
uncertainties is proposed for the stochastic buckling analysis of composite shells. The …

A matrix-free isogeometric Galerkin method for Karhunen–Loève approximation of random fields using tensor product splines, tensor contraction and interpolation …

ML Mika, TJR Hughes, D Schillinger, P Wriggers… - Computer Methods in …, 2021 - Elsevier
Abstract The Karhunen–Loève series expansion (KLE) decomposes a stochastic process
into an infinite series of pairwise uncorrelated random variables and pairwise L 2-orthogonal …

Polyphase uncertainty analysis through virtual modelling technique

Q Wang, Y Feng, D Wu, C Yang, Y Yu, G Li… - … Systems and Signal …, 2022 - Elsevier
A virtual model aided non-deterministic static analysis (including linear and nonlinear
analyses) with polyphase uncertainty is presented in this paper. Within an uncertain system …

A new stochastic isogeometric analysis method based on reduced basis vectors for engineering structures with random field uncertainties

Z Liu, M Yang, J Cheng, J Tan - Applied Mathematical Modelling, 2021 - Elsevier
A new stochastic isogeometric analysis method based on reduced basis vectors (SRBIGA) is
proposed for engineering structures with random field material properties and external …

Meta-model based stochastic isogeometric analysis of composite plates

Z Liu, M Yang, J Cheng, D Wu, J Tan - International Journal of Mechanical …, 2021 - Elsevier
A stochastic isogeometric analysis approach (SIGA) is presented for functionally graded
porous plates with graphene platelets reinforcement (FGP-GPLs). Different kinds of random …

Stochastic isogeometric analysis for the linear stability assessment of plate structures using a Kriging enhanced Neural Network

Z Liu, M Yang, J Cheng, D Wu, J Tan - Thin-Walled Structures, 2020 - Elsevier
The stability of functionally graded porous plates with graphene platelets reinforcement
(FGP-GPLs) is investigated in this paper. Combining with a new metamodeling approach …