Modeling, analysis, and optimization under uncertainties: a review

E Acar, G Bayrak, Y Jung, I Lee, P Ramu… - Structural and …, 2021‏ - Springer
Abstract Design optimization of structural and multidisciplinary systems under uncertainty
has been an active area of research due to its evident advantages over deterministic design …

Evidence-theory-based structural reliability analysis with epistemic uncertainty: a review

Z Zhang, C Jiang - Structural and Multidisciplinary Optimization, 2021‏ - Springer
Epistemic uncertainty widely exists in the early design stage of complex engineering
structures or throughout the full-life cycle of innovative structure design, which should be …

Mixed efficient global optimization for time-dependent reliability analysis

Z Hu, X Du - Journal of Mechanical Design, 2015‏ - asmedigitalcollection.asme.org
Time-dependent reliability analysis requires the use of the extreme value of a response. The
extreme value function is usually highly nonlinear, and traditional reliability methods, such …

A general failure-pursuing sampling framework for surrogate-based reliability analysis

C Jiang, H Qiu, Z Yang, L Chen, L Gao, P Li - Reliability Engineering & …, 2019‏ - Elsevier
Abstract Design of experiment and active learning strategy are vital for the surrogate-based
reliability analysis. However, the existing sampling and modeling methods usually ignore …

Global sensitivity analysis-enhanced surrogate (GSAS) modeling for reliability analysis

Z Hu, S Mahadevan - Structural and Multidisciplinary Optimization, 2016‏ - Springer
An essential issue in surrogate model-based reliability analysis is the selection of training
points. Approaches such as efficient global reliability analysis (EGRA) and adaptive Kriging …

A nested extreme response surface approach for time-dependent reliability-based design optimization

Z Wang, P Wang - Journal of Mechanical Design, 2012‏ - asmedigitalcollection.asme.org
A primary concern in practical engineering design is ensuring high system reliability
throughout a product's lifecycle, which is subject to time-variant operating conditions and …

Limit state Kriging modeling for reliability-based design optimization through classification uncertainty quantification

X Li, H Zhu, Z Chen, W Ming, Y Cao, W He… - Reliability engineering & …, 2022‏ - Elsevier
Reliability-based design optimization (RBDO) plays a vital role in considering the effect of
uncertainties in the optimal design variables on the production reliability. Kriging-assisted …

System reliability analysis with autocorrelated kriging predictions

H Wu, Z Zhu, X Du - Journal of Mechanical Design, 2020‏ - asmedigitalcollection.asme.org
When limit-state functions are highly nonlinear, traditional reliability methods, such as the
first-order and second-order reliability methods, are not accurate. Monte Carlo simulation …

Deep learning for high-dimensional reliability analysis

M Li, Z Wang - Mechanical Systems and Signal Processing, 2020‏ - Elsevier
High-dimensional reliability analysis remains a grand challenge since most of the existing
methods suffer from the curse of dimensionality. This paper introduces a novel high …

Reliability analysis with Monte Carlo simulation and dependent Kriging predictions

Z Zhu, X Du - Journal of Mechanical Design, 2016‏ - asmedigitalcollection.asme.org
Reliability analysis is time consuming, and high efficiency could be maintained through the
integration of the Kriging method and Monte Carlo simulation (MCS). This Kriging-based …