摘要
为探索框架填充墙在地震作用下开裂模式,提出了墙体高宽比和梁柱线刚度比作为预测参数,基于已收集的试验研究成果,运用了神经网络技术对上述参数不同组合下的填充墙裂缝开展进行了预测研究,通过所定义的评价预测结果的指标,比较了不同预测参数组合时框架填充墙裂缝开展模式,并在此基础上对预测结果进行验证。分析结果表明:在使用墙体高宽比和梁柱线刚度比的双参数组合时,填充墙裂缝预测的开裂模式与实际裂缝发展吻合较好,它能较准确地预测框架填充墙开裂模式,可为设计提供参考。
In order to know the cracking pattern of frame infilled wall,wall＇s aspect ratio and line stiffness ratio of beam and column as prediction parameters are proposed. The appearance of cracking in different parameter combination is evaluated by neural network based on existing experiment results. According to the defined indicators which are used to evaluate crack,the crack patterns in different parameter combination are compared. In the same time,the experimental verification for crack pattern of the infills in RC frame is done. The results show that when wall＇s aspect ratio and line stiffness ratio of beam and column are combined as prediction parameters,the predicted result appears to be the most matched with the actual experiment. It can well predict the cracking pattern of frame infilled wall,which provides a vital reference to project.
出处
《建筑科学》
CSCD
北大核心
2016年第9期69-73,共5页
Building Science
基金
四川省住房及城乡建设厅科技基金项目资助(2014S20025)
国家自然科学基金项目资助(51308473)
关键词
框架结构
填充墙
裂缝
开裂模式
神经网络
frame structure
infilled wall
crack
crack pattern
neural network
