R Pang, Y Zhou, G Chen, M Jing… - Journal of Engineering …, 2023 - ascelibrary.org
A novel approach for nonlinear stochastic dynamic analysis is proposed and illustrated with nonlinear building structures subjected to mainshock–aftershock sequences. First, a …
In Stochastic Dynamics of Structures, Li and Chen present a unified view of the theory and techniques for stochastic dynamics analysis, prediction of reliability, and system control of …
In the stochastic dynamic analysis of nonlinear structures, the strategy of point selection plays a critical role in achieving the tradeoffs between the accuracy and efficiency. To this …
T Zhou, Y Peng - Reliability Engineering & System Safety, 2022 - Elsevier
An efficient reliability method that combines adaptive Polynomial-Chaos Kriging (PC- Kriging) and probability density evolution method (PDEM) is developed, which is …
MZ Lyu, DC Feng, JB Chen, J Li - Computer Methods in Applied Mechanics …, 2024 - Elsevier
The joint probability density function (PDF) of multiple response processes of a system is a crucial topic in the fields of science and engineering. It is adopted to describe the dependent …
New advances of the probability density evolution method for nonlinear stochastic systems are presented. The principle of preservation of probability, as a fundamental law of …
This paper presents a novel approach for modeling the tensile failure of quasi-brittle materials by incorporating a multivariate random field to represent material parameters in …
DY Liu, MZ Lyu - Computers and Geotechnics, 2023 - Elsevier
Significant uncertainty exists in granular materials, as demonstrated by experimental and simulation studies. Quantifying this uncertainty by integrating refined discrete element …
J Li, D Wang - Probabilistic Engineering Mechanics, 2023 - Elsevier
The accuracy and efficiency of two methods for stochastic analysis, the probability density evolution method (PDEM) and the Monte Carlo simulation (MCS) method, are compared in …