考虑长期监测应力时序的钢箱梁桥疲劳评估方法研究

项目名称： 考虑长期监测应力时序的钢箱梁桥疲劳评估方法研究

项目编号： No.51308186

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 建筑科学

项目作者： 周广东

作者单位： 河海大学

项目金额： 25万元

中文摘要： 针对忽略长期监测应力时序可能造成钢箱梁桥疲劳评估结果偏离实际情况的不足，本项目对"考虑长期监测应力时序的钢箱梁桥疲劳评估方法"的关键科学问题开展系统性研究，主要包括：（1）基于长期监测应力数据揭示疲劳荷载效应的时变规律并建立疲劳荷载效应的时变函数，给出疲劳荷载效应的统计模型，进而提出面向可靠度评估的时变疲劳荷载效应随机模拟方法；（2）形成钢箱梁桥疲劳评估的全空间S-N曲线，建立考虑长期监测应力时序的非线性疲劳损伤累积模式，在此基础上提出非线性疲劳累积损伤计算的高效时序损伤模型；（3）建立基于高效时序损伤模型的钢箱梁桥疲劳可靠度评估极限状态方程，确定极限状态方程参数的概率表述，从而形成考虑长期监测应力时序的钢箱梁桥疲劳可靠度评估方法；（4）集成考虑长期监测应力时序的钢箱梁桥疲劳评估软件，开展考虑长期监测应力时序的疲劳评估方法典型工程应用。研究结果可为钢箱梁桥的疲劳性能评估提供新的途径。

中文关键词： 应力时序；疲劳损伤；钢箱梁桥；疲劳可靠度评估；结构健康监测

英文摘要： To cover the shortages that the steel box-girder bridge fatigue assessment results may deviate from the actual situation when neglecting long-term monitoring stress sequence, the key scientific problems about the fatigue assessment methodology for steel box-girder bridges considering long-term monitoring stress sequence will be researched systemically. The main contents are as following: (1) The time-dependent law of fatigue load effect will be revealed based on long-term monitoring stress, and the time-dependent function will be proposed. Then, the statistic model of fatigue load effect will be established. After that, the numerical simulation method of time-dependent fatigue load effect considering random and time-varying characteristics of fatigue stress will be suggested. (2) The fully known S-N curves for fatigue assessment of steel box-girder bridge will be provided. Then the non-linear fatigue damage accumulation model considering long-term monitoring stress sequence will be developed. Based on this, the efficiency stress-sequence damage model used for non-linear accumulation fatigue damage calculation will be proposed. (3) The limit state function used for fatigue reliability assessment of steel box-girder bridge will be established based on the efficiency stress-sequence damage model. The statistical mo

英文关键词： stress sequence；fatigue damage；steel box-girder birdge；fatigue reliability assessment；structural health monitoring