Fatigue performance of existing coastal slender bridges under multiple stochastic dynamic loads
Coastal slender bridges could interact with complicated dynamic loadings from traffic,wind,and waves,facing with potential fatigue damage threats especially in weldments with complicated geometries of the orthotropic steel deck(OSD).Nevertheless,the fatigue damage accumulation is a stochastic process,attributed to uncertainties from the ambient environmental loads,making it difficult and questionable for using fatigue stress spectrum simulation and fatigue performance assessment.Hence,a reliability-based fatigue assessment approach is appropriate and necessary to analyze the performance of OSD considering multiple stochastic characteristics of the dynamic loadings.In this paper,a numerical framework is developed by integrating deterministic multi-scale finite-element(FE)model with stochastic traffic,wind and wave loads,to enable probabilistic modeling of fatigue damage and reliability assessment of welded details in OSD.The stochastic load models are first established based on field measurements,which are utilized as dynamic loads input for the multi-scale FE model to further extract the stress time-histories at the critical bridge weldment.The extracted stress responses are further transformed to daily equivalent fatigue damage accumulations using the rain-flow counting method and Miners rule.To improve the computational efficiency,the uniform design sampling method and machine-learning algorithm are adopted to substitute the conventional Monte Carlo simulations.After the daily equivalent fatigue accumulation is predicted with the proposed probabilistic numerical framework,the fatigue life of the critical welded details of the OSD can be rationally estimated with an appropriate limit-state function.A prototype cable-stayed orthotropic steel deck bridge is presented as a demonstration to illustrate the feasibility of the proposed numerical framework.
vehicle-bridge-wind-wave dynamics machine learning fatigue reliability copula
J.Zhu W.Zhang
Ph.D.Candidate,Dept.of Civil & Environmental Engineering,University of Connecticut,Storrs,United Sta Assistant Professor,Dept.of Civil & Environmental Engineering,University of Connecticut,Storrs,Unite
国际会议
The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)
青岛
英文
2464-2473
2018-07-22（万方平台首次上网日期，不代表论文的发表时间）