文献类型：期刊文献

英文题名：Fast Mixture Distribution Optimization for Rain-Flow Matrix of a Steel Arch Bridge by REBMIX Algorithm

作者：He, Yuliang[1]; Lou, Weihong[1]; Hang, Da[2]; Su, Youhua[3]

机构：[1] School of Civil Engineering, Shaoxing University, Shaoxing, 312000, China; [2] Department of Civil Engineering, Zhejiang University, Hangzhou, 310058, China; [3] Department of Civil Engineering, Xi’an Jiaotong University, Xi’an, 710049, China

年份：2025

卷号：19

期号：4

起止页码：887

外文期刊名：SDHM Structural Durability and Health Monitoring

收录：EI(收录号：20252818750434)、Scopus(收录号：2-s2.0-105009958945)

语种：英文

外文关键词：Computational efficiency - Fatigue of materials - Matrix algebra - Optimization - Parameter estimation - Reliability analysis - Spectrum analysis

外文摘要：The computational accuracy and efficiency of modeling the stress spectrum derived from bridge monitoring data significantly influence the fatigue life assessment of steel bridges. Therefore, determining the optimal stress spectrum model is crucial for further fatigue reliability analysis. This study investigates the performance of the REBMIX algorithm in modeling both univariate (stress range) and multivariate (stress range and mean stress) distributions of the rain-flow matrix for a steel arch bridge, using Akaike’s Information Criterion (AIC) as a performance metric. Four types of finite mixture distributions—Normal, Lognormal, Weibull, and Gamma—are employed to model the stress range. Additionally, mixed distributions, including Normal-Normal, Lognormal-Normal, Weibull-Normal, and Gamma-Normal, are utilized to model the joint distribution of stress range and mean stress. The REBMIX algorithm estimates the number of components, component weights, and component parameters for each candidate finite mixture distribution. The results demonstrate that the REBMIX algorithm-based mixture parameter estimation approach effectively identifies the optimal distribution based on AIC values. Furthermore, the algorithm exhibits superior computational efficiency compared to traditional methods, making it highly suitable for practical applications. Copyright ? 2025 The Authors.