Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review
C Song, R Kawai - Probabilistic Engineering Mechanics, 2023 - Elsevier
Monte Carlo methods have attracted constant and even increasing attention in structural
reliability analysis with a wide variety of developments seamlessly presented over decades …
reliability analysis with a wide variety of developments seamlessly presented over decades …
A multi-fidelity surrogate model based on extreme support vector regression: Fusing different fidelity data for engineering design
Purpose Extreme support vector regression (ESVR) has been widely used in the design,
analysis and optimization of engineering systems of its fast training speed and good …
analysis and optimization of engineering systems of its fast training speed and good …
Enhanced Kriging leave-one-out cross-validation in improving model estimation and optimization
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 …
and selection of the Kriging surrogate model for engineering problems, such as structural …
Adaptive reliability analysis for multi-fidelity models using a collective learning strategy
In many fields of science and engineering, models with different fidelities are available.
Physical experiments or detailed simulations that accurately capture the behavior of the …
Physical experiments or detailed simulations that accurately capture the behavior of the …
Uncertainty quantification in low-probability response estimation using sliced inverse regression and polynomial chaos expansion
For wave energy converters (WECs), wind turbines, etc., estimation of response extremes
over a selected exposure time is important during design. Sources of uncertainty arising …
over a selected exposure time is important during design. Sources of uncertainty arising …
A novel sampling method for adaptive gradient-enhanced Kriging
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 …
(AGEK) that delivers superior results on a limited budget. The primary innovation of this …
Reliability based design optimization of bridges considering bridge-vehicle interaction by Kriging surrogate model
This paper presents a reliability-based design optimization method for bridge structures,
considering the uncertainties of the material parameters and the effect of bridge-vehicle …
considering the uncertainties of the material parameters and the effect of bridge-vehicle …
Multi-output Gaussian process prediction for computationally expensive problems with multiple levels of fidelity
The multi-output Gaussian process (MOGP) modeling approach is a promising way to deal
with multiple correlated outputs since it can capture useful information across outputs to …
with multiple correlated outputs since it can capture useful information across outputs to …
A novel fidelity selection strategy-guided multifidelity kriging algorithm for structural reliability analysis
J Yi, Y Cheng, J Liu - Reliability Engineering & System Safety, 2022 - Elsevier
Multifidelity (MF) surrogate models have recently attracted intensive attention due to their
advantage of reducing computational demand by fusing multiple sources of data. However …
advantage of reducing computational demand by fusing multiple sources of data. However …
Active learning with multifidelity modeling for efficient rare event simulation
While multifidelity modeling provides a cost-effective way to conduct uncertainty
quantification with computationally expensive models, much greater efficiency can be …
quantification with computationally expensive models, much greater efficiency can be …