Hybrid enhanced Monte Carlo simulation coupled with advanced machine learning approach for accurate and efficient structural reliability analysis
The accurate estimations of the failure probability with low-computational burden play a vital
role in structural reliability analyses. Due to high-calculation cost and time-consuming Monte …
role in structural reliability analyses. Due to high-calculation cost and time-consuming Monte …
An advanced mixed-degree cubature formula for reliability analysis
Efficient assessment of mechanical system reliability subject to arbitrary probability
distributions and dependent input parameters signifies an important yet challenging task. To …
distributions and dependent input parameters signifies an important yet challenging task. To …
An efficient and versatile Kriging-based active learning method for structural reliability analysis
In structural reliability analysis, the development of an efficient and versatile active learning
method applicable to problems of varying complexities remains a challenging task. The …
method applicable to problems of varying complexities remains a challenging task. The …
An accelerated active learning Kriging model with the distance-based subdomain and a new stopping criterion for reliability analysis
Reliability analysis for computationally expensive models is a challenging problem. Monte
Carlo simulation is commonly employed in conjunction with the active learning assisted …
Carlo simulation is commonly employed in conjunction with the active learning assisted …
Polynomial chaos expansion approximation for dimension-reduction model-based reliability analysis method and application to industrial robots
J Wu, Y Tao, X Han - Reliability Engineering & System Safety, 2023 - Elsevier
Polynomial chaos expansion (PCE) is considered an excellent method for accurately and
efficiently reliability analysis in various engineering problems. However, it becomes …
efficiently reliability analysis in various engineering problems. However, it becomes …
Dimensional decomposition-aided metamodels for uncertainty quantification and optimization in engineering: A review
Quantitative analysis and optimal design under uncertainty are active research areas in
modern engineering structures and systems. A metamodel, as an effective mathematical …
modern engineering structures and systems. A metamodel, as an effective mathematical …
高置信水平结构逆可靠度分析与优化方法研究进展
郝鹏， 杨浩， 冯少军， 王博 - 力学学报, 2023 - lxxb.cstam.org.cn
不确定性客观存在于工程结构生产制造以及服役等各环节之中并对结构的承载性能影响显著.
特别是对于服役条件苛刻的航空航天承载装备, 在设计阶段考虑多源不确定性的影响对于结构 …
特别是对于服役条件苛刻的航空航天承载装备, 在设计阶段考虑多源不确定性的影响对于结构 …
Deep adaptive arbitrary polynomial chaos expansion: A mini-data-driven semi-supervised method for uncertainty quantification
W Yao, X Zheng, J Zhang, N Wang, G Tang - Reliability Engineering & …, 2023 - Elsevier
All kinds of uncertainties influence the reliability of the engineering system. Thus, uncertainty
quantification is significant to the system reliability analysis. Polynomial chaos expansion …
quantification is significant to the system reliability analysis. Polynomial chaos expansion …
Prediction and global sensitivity analysis of long-term deflections in reinforced concrete flexural structures using surrogate models
W Dan, X Yue, M Yu, T Li, J Zhang - Materials, 2023 - mdpi.com
Reinforced concrete (RC) is the result of a combination of steel reinforcing rods (which have
high tensile) and concrete (which has high compressive strength). Additionally, the …
high tensile) and concrete (which has high compressive strength). Additionally, the …
Generalized distribution reconstruction based on the inversion of characteristic function curve for structural reliability analysis
Recovering the probability distribution of the performance function with an arbitrary shape is
still a difficult task for structural reliability analysis. Since working with the characteristic …
still a difficult task for structural reliability analysis. Since working with the characteristic …