Modern Monte Carlo methods for efficient uncertainty quantification and propagation: A survey

J Zhang - Wiley Interdisciplinary Reviews: Computational …, 2021 - Wiley Online Library
Uncertainty quantification (UQ) includes the characterization, integration, and propagation of
uncertainties that result from stochastic variations and a lack of knowledge or data in the …

Recent developments in mechanical and uncertainty modelling of concrete

J Chen, X Ren, DC Feng, J Kohler, JD Sørensen… - Structural Safety, 2025 - Elsevier
Concrete is one of the most widely used materials in civil and infrastructure engineering in
the world, just following water. Therefore, the serviceability and safety of concrete structures …

A nonparametric seismic reliability analysis method based on Bayesian compressive sensing–stochastic harmonic function method and probability density evolution …

J He, R Gao, H Zhou - Mechanical Systems and Signal Processing, 2023 - Elsevier
In engineering practice, the evaluation of seismic reliability of high-rise reinforced concrete
structure relies on the probabilistic modelling of material properties. However, the measured …

Investigations on the restrictions of stochastic collocation methods for high dimensional and nonlinear engineering applications

MM Dannert, F Bensel, A Fau, RMN Fleury… - Probabilistic …, 2022 - Elsevier
Sophisticated sampling techniques used for solving stochastic partial differential equations
efficiently and robustly are still in a state of development. It is known in the scientific …

Karhunen-Loève expansion based on an analytical solution over a bounding box domain

AA Basmaji, MM Dannert, F Bensel, RMN Fleury… - Probabilistic …, 2023 - Elsevier
This paper explores the accuracy and the efficiency of analytical solution of Fredholm
integral equation to represent a random field on complex geometry. Because no analytical …

Interval and fuzzy physics-informed neural networks for uncertain fields

JN Fuhg, I Kalogeris, A Fau, N Bouklas - Probabilistic Engineering …, 2022 - Elsevier
Temporally and spatially dependent uncertain parameters are regularly encountered in
engineering applications. Commonly these uncertainties are accounted for using random …

[HTML][HTML] Soft-constrained interval predictor models and epistemic reliability intervals: A new tool for uncertainty quantification with limited experimental data

R Rocchetta, Q Gao, M Petkovic - Mechanical Systems and Signal …, 2021 - Elsevier
Abstract Interval Predictor Models (IPMs) offer a non-probabilistic, interval-valued,
characterization of the uncertainty affecting random data generating processes. IPMs are …

The effect of fastener clip fatigue for high-speed railway on vehicle-track dynamic interaction: Numerical analysis and probabilistic evaluation

Z Li, H Liu, W Wang, L Xu - Applied Mathematical Modelling, 2024 - Elsevier
To investigate the vehicle-induced fatigue damage evolution of fastener clips and their
impact on the vehicle-track (VT) system, a numerical dynamic model is established to …

[HTML][HTML] Polymorphic uncertainty field quantification in structural analysis with machine learning assistance

Q Wang, Z Luo, M Zhang, D Wu, G Li, W Gao - Mechanical Systems and …, 2025 - Elsevier
This research proposes and evaluates a generalised uncertainty model, the Polymorphic
Uncertainty Field, which simultaneously considers two challenges in engineering practices …

Damage evaluation of ballastless track concrete under high frequency flexural fatigue loading based on surface resistivity

J Wen, H Li, Z Yang, Z Yang, H Dong - Construction and Building Materials, 2024 - Elsevier
A fatigue loading system with 20 Hz was established to simulate loading characteristics of
ballastless track concrete. The surface resistivity (SR) method was utilized to evaluate …