Machine learning-based methods in structural reliability analysis: A review

SS Afshari, F Enayatollahi, X Xu, X Liang - Reliability Engineering & System …, 2022 - Elsevier
Structural Reliability analysis (SRA) is one of the prominent fields in civil and mechanical
engineering. However, an accurate SRA in most cases deals with complex and costly …

A practical Bayesian framework for structural model updating and prediction

T Yin - ASCE-ASME Journal of Risk and Uncertainty in …, 2022 - ascelibrary.org
Due to the influence of various uncertain factors, there will inevitably be certain errors
between the prediction of finite-element (FE) model and observed data for a target structure …

Bayesian updating of failure probability curves with multiple performance functions of nonlinear structural dynamic systems

C Hao, SH Cheung - Computer Methods in Applied Mechanics and …, 2022 - Elsevier
Abstract System failure often involves multiple failure modes which require considering
multiple performance functions. Based on measured system response data, Bayesian …

Bayesian optimal experimental design involving multiple setups for dynamic structural testing

S Bansal - International Journal for Uncertainty Quantification, 2019 - dl.begellhouse.com
In an experimental design for dynamic structural testing, it is a common practice to obtain
data from a structure using multiple setups, with each setup covering a different part of the …

[PDF][PDF] Efficient methodology and algorithms for resilience analysis of critical infrastructure systems subjected to natural hazards

C Hao - Nanyang Technologica l University, 2021 - scholar.archive.org
Critical infrastructure systems (CIS) are highly connected to human life and industrial
productions. Well protected and resilient critical infrastructure systems are the key …