Structural dynamic reliability analysis: review and prospects
D Teng, YW Feng, JY Chen, C Lu - International Journal of Structural …, 2022 - emerald.com
Purpose The purpose of this paper is to briefly summarize and review the theories and
methods of complex structures' dynamic reliability. Complex structures are usually …
methods of complex structures' dynamic reliability. Complex structures are usually …
Monte Carlo and variance reduction methods for structural reliability analysis: A comprehensive review
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 …
[HTML][HTML] Machine learning and materials informatics approaches for predicting transverse mechanical properties of unidirectional CFRP composites with microvoids
The mechanical properties of composites are traditionally measured using numerical and
experimental approaches, which impede the innovation of materials due to the cost, time, or …
experimental approaches, which impede the innovation of materials due to the cost, time, or …
An adaptive surrogate model to structural reliability analysis using deep neural network
This article introduces a simple and effective adaptive surrogate model to structural reliability
analysis using deep neural network (DNN). In this paradigm, initial design of experiments …
analysis using deep neural network (DNN). In this paradigm, initial design of experiments …
Review and application of artificial neural networks models in reliability analysis of steel structures
This paper presents a survey on the development and use of Artificial Neural Network (ANN)
models in structural reliability analysis. The survey identifies the different types of ANNs, the …
models in structural reliability analysis. The survey identifies the different types of ANNs, the …
Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence
Monte Carlo analysis has become nearly ubiquitous since its introduction, now over 65
years ago. It is an important tool in many assessments of the reliability and robustness of …
years ago. It is an important tool in many assessments of the reliability and robustness of …
The interactive effects of online reviews on the determinants of Swiss hotel performance: A neural network analysis
From a strategy perspective, the growth of social media accelerates the need for tourism
organisations to constantly re-appraise their competitive strategies. This study contributes …
organisations to constantly re-appraise their competitive strategies. This study contributes …
Optimal sizing of a grid independent hybrid renewable energy system incorporating resource uncertainty, and load uncertainty
Wind speed (WS) and solar radiation (SR) are innately uncertain and bring about more
uncertainties in the power system. Therefore, due to the nonlinear nature of photovoltaic …
uncertainties in the power system. Therefore, due to the nonlinear nature of photovoltaic …
Deep learning for accelerated seismic reliability analysis of transportation networks
To optimize mitigation, preparedness, response, and recovery procedures for infrastructure
systems, it is essential to use accurate and efficient means to evaluate system reliability …
systems, it is essential to use accurate and efficient means to evaluate system reliability …
Adaptive surrogate model with active refinement combining Kriging and a trust region method
The reliability analysis of engineering structural systems with limit state functions defined
implicitly by time-consuming numerical models (eg finite element analysis structural models) …
implicitly by time-consuming numerical models (eg finite element analysis structural models) …