Enhanced Kriging leave-one-out cross-validation in improving model estimation and optimization

Y Pang, Y Wang, X Lai, S Zhang, P Liang… - Computer Methods in …, 2023 - Elsevier
Leave-one-out cross-validation (LOOCV) is a widely used technique in model estimation
and selection of the Kriging surrogate model for engineering problems, such as structural …

AK-SEUR: An adaptive Kriging-based learning function for structural reliability analysis through sample-based expected uncertainty reduction

C Peng, C Chen, T Guo, W Xu - Structural Safety, 2024 - Elsevier
Reliability Analysis (RA) is a critical aspect of structural design and performance evaluation
aiming to determine the probability of structural failure under given random input …

A novel sampling method for adaptive gradient-enhanced Kriging

M Lee, Y Noh, I Lee - Computer Methods in Applied Mechanics and …, 2024 - Elsevier
This paper presents a novel infill-sampling strategy for adaptive gradient-enhanced Kriging
(AGEK) that delivers superior results on a limited budget. The primary innovation of this …

Failure probability function estimation in augmented sample space combined active learning Kriging and adaptive sampling by Voronoi cells

H Hu, P Wang, F Xin, L Li - Mechanical Systems and Signal Processing, 2024 - Elsevier
Due to the epistemic uncertainty in engineering practice, both the random variables and
their distribution parameters should be simultaneously considered uncertain. Therefore, the …

Surrogate-based sequential Bayesian experimental design using non-stationary Gaussian Processes

P Pandita, P Tsilifis, NM Awalgaonkar, I Bilionis… - Computer Methods in …, 2021 - Elsevier
Inferring arbitrary quantities of interest (QoI) using limited computational or, in realistic
scenarios, financial budgets, is a challenging problem that requires sophisticated strategies …

A novel adaptive Kriging method: Time-dependent reliability-based robust design optimization and case study

Z Jiang, J Wu, F Huang, Y Lv, L Wan - Computers & Industrial Engineering, 2021 - Elsevier
The computational efficiency and accuracy of the time-dependent reliability-based robust
design optimization (TRBRDO) directly rely on the capability to handle the time-dependent …

Large-scale sandwich structures optimization using Bayesian method

H Liu, J Guo, J Wang, C Wang - International Journal of Mechanical …, 2024 - Elsevier
Benefiting from advanced features like high stiffness-to-weight ratios, sandwich structures
are widely used in aerospace for primary and secondary structures. As tasks grow more …

Gradient and uncertainty enhanced sequential sampling for global fit

S Lämmle, C Bogoclu, K Cremanns, D Roos - Computer Methods in …, 2023 - Elsevier
Surrogate models based on machine learning methods have become an important part of
modern engineering to replace costly computer simulations. The data used for creating a …

Local non‐intrusive reduced order modeling based on soft clustering and classification algorithm

YE Kang, S Shon, K Yee - International Journal for Numerical …, 2022 - Wiley Online Library
The use of non‐intrusive reduced order modeling (NIROM) to approximate high‐fidelity
computer models has been steadily increased over the past decade. Recently, local NIROM …

Adaptive virtual modelling enhanced dynamic and reliability analysis of SGPLRP-MEE plates

L Bo, J Zhang, K Gao, H Wang - International Journal of Mechanical …, 2025 - Elsevier
This paper proposes the novel multi-physical nonlinear dynamic biaxial buckling and
reliability analysis for sandwich graphene platelets reinforced porous plates with magneto …