基于纤维模型的钢混框架结构拟静力试验数值模拟  被引量:7

Numerical simulation for pseudo-static test of RC frame structure based on the fiber model

在线阅读下载全文

作  者:张沛洲[1] 欧进萍[1,2] 

机构地区:[1]大连理工大学建设工程学部,大连116024 [2]哈尔滨工业大学土木工程学院,哈尔滨150090

出  处:《建筑结构》2013年第18期64-69,共6页Building Structure

基  金:国家自然科学基金项目(51261120376);“973”国家重点基础研究发展计划基金项目(2007CB714202)

摘  要:为分析汶川地震中钢混框架结构的震害机理,清华大学和中国建筑学会建筑结构防倒塌专业委员会开展了一系列拟静力试验,以此为背景,基于纤维模型提出了考虑节点宏观模型的建模方法,并采用此方法在试验前后分别模拟了该系列试验。基于结构整体和局部信息对比了框架试验与模拟的结果,初步探讨了柱构件试验边界条件的合理性。研究表明,与其他模型相比,使用纤维模型能够更好地预测框架结构及构件的受力行为,尤其在考虑了节点区建模后可更准确地模拟结构的滞回行为;对于"强节点弱构件"类结构,分析中可不考虑节点区建模,若梁柱节点区配箍不足,则要考虑节点区的影响,建议针对特定的问题需选取合适的建模方法。In order to analyze the seismic damage mechanism of reinforced concrete (RC) frame structures damaged during the Wenchuan Earthquake, a series of pseudo-static tests of RC frame structure were carried out by Tsinghua University and Professional Committee of Collapse-prevention of Building Structure, Architectural Society of China. Based on these experiments, a structural modeling method based on fiber model and joint macro model was developed to predict mechanical behaviors of the frame before and after the experiments. Then the simulation results were compared with the test results from the global and local levels. Finally, the reasonability of the boundary conditions of RC column tests was discussed. Research shows that fiber models can predict the mechanical behaviors of the RC structures and their components much better than other models, and it can better illustrate the hysteretic behavior of structures when considering the joint modeling. For structures as "strong connections and weak members", joint modeling isn't necessary except for structures with poor shear capacity in joints. It is proposed to select appropriate modeling methods under the specific condition.

关 键 词:钢筋混凝土框架结构 数值模拟 OPENSEES 纤维模型 梁柱节点 

分 类 号:TU375.4[建筑科学—结构工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象