[HTML][HTML] Adaptive approaches in metamodel-based reliability analysis: A review

R Teixeira, M Nogal, A O'Connor - Structural Safety, 2021 - Elsevier
The present work reviews the implementation of adaptive metamodeling for reliability
analysis with emphasis in four main types of metamodels: response surfaces, polynomial …

Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial

V Nemani, L Biggio, X Huan, Z Hu, O Fink… - … Systems and Signal …, 2023 - Elsevier
On top of machine learning (ML) models, uncertainty quantification (UQ) functions as an
essential layer of safety assurance that could lead to more principled decision making by …

[图书][B] Uncertainty quantification: theory, implementation, and applications

RC Smith - 2024 - SIAM
Uncertainty quantification serves a central role for simulation-based analysis of physical,
engineering, and biological applications using mechanistic models. From a broad …

Structure damage identification in dams using sparse polynomial chaos expansion combined with hybrid K-means clustering optimizer and genetic algorithm

L YiFei, HL Minh, S Khatir, T Sang-To, T Cuong-Le… - Engineering …, 2023 - Elsevier
Structural damage identification plays a crucial role in structural health monitoring. In this
study, a novelty method for structural damage identification is developed, which employs an …

Multi-parameter identification of concrete dam using polynomial chaos expansion and slime mould algorithm

L YiFei, C MaoSen, H Tran-Ngoc, S Khatir… - Computers & …, 2023 - Elsevier
This paper presents a novel methodology that combines polynomial chaos expansion and
slime mould algorithm for multi-parameter identification of concrete dams. This methodology …

Enhancing the explainability of regression-based polynomial chaos expansion by Shapley additive explanations

PS Palar, LR Zuhal, K Shimoyama - Reliability Engineering & System Safety, 2023 - Elsevier
Surrogate models are indispensable tools in uncertainty quantification and global sensitivity
analysis. Polynomial chaos expansion (PCE) is one of the most widely used surrogate …

Metamodel-assisted hybrid optimization strategy for model updating using vibration response data

L YiFei, C MaoSen, TN Hoa, S Khatir, HL Minh… - … in Engineering Software, 2023 - Elsevier
In this study, an effective and novel method, termed Metamodel Assisted Hybrid of Particle
Swarm Optimization with Genetic Algorithm (MA-HPSOGA), is developed to identify …

Variance-based adaptive sequential sampling for polynomial chaos expansion

L Novák, M Vořechovský, V Sadílek… - Computer Methods in …, 2021 - Elsevier
This paper presents a novel adaptive sequential sampling method for building Polynomial
Chaos Expansion surrogate models. The technique enables one-by-one extension of an …

Efficient reliability analysis using prediction-oriented active sparse polynomial chaos expansion

J Zhang, W Gong, X Yue, M Shi, L Chen - Reliability Engineering & System …, 2022 - Elsevier
In this paper, a prediction-oriented active sparse polynomial chaos expansion (PAS-PCE) is
proposed for reliability analysis. Instead of leveraging on additional techniques to reduce the …

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems

K Kontolati, D Loukrezis, DG Giovanis… - Journal of …, 2022 - Elsevier
Constructing surrogate models for uncertainty quantification (UQ) on complex partial
differential equations (PDEs) having inherently high-dimensional O (10 n), n≥ 2, stochastic …