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钢筋混凝土结构的模型更新混合试验方法
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  • 英文篇名:Model Updating Hybrid Simulation of Reinforced Concrete Structures
  • 作者:梅竹 ; 吴斌 ; 杨格 ; 刘洋
  • 英文作者:MEI Zhu;WU Bin;YANG Ge;LIU Yang;College of Architecture & Environment,Sichuan Univ.;School of Civil Eng.and Architecture,Wuhan Univ.of Technol.;School of Civil Eng.Harbin Inst.of Technol.;
  • 关键词:混合试验 ; 参数在线识别 ; 隐性卡尔曼滤波器(UKF) ; OpenSEES ; 混凝土框架
  • 英文关键词:hybrid simulation;;online parameter identification;;unscented Kalman filter;;OpenSEES;;RC frame
  • 中文刊名:SCLH
  • 英文刊名:Advanced Engineering Sciences
  • 机构:四川大学建筑与环境学院;武汉理工大学土木工程与建筑学院;哈尔滨工业大学土木工程学院;
  • 出版日期:2018-10-30 09:00
  • 出版单位:工程科学与技术
  • 年:2018
  • 期:v.50
  • 基金:国家重点研发计划资助项目(2016YFC0701106);; 国家自然科学基金重大国际(地区)合作研究资助项目(51161120360)
  • 语种:中文;
  • 页:SCLH201806009
  • 页数:6
  • CN:06
  • ISSN:51-1773/TB
  • 分类号:69-74
摘要
当结构在极端荷载作用下进入强非线性时,混合试验数值子结构是否能够准确模拟结构的强非线性成为关注焦点。模型更新从本构模型参数准确性的角度出发,提出了在线更新数值子结构本构模型参数的概念。由于构件本构模型与截面本构模型具有一定局限性,现有构件、截面本构模型更新的混合试验很难满足大型复杂结构的需求。作者从材料层次出发,采用混凝土本构模型参数的识别方法,并将其应用于钢筋混凝土结构的在线更新混合试验中。通过完成平面混凝土框架3种工况的混合试验,对混凝土材料本构参数识别方法和在线模型更新混合试验进行了验证。试验结果表明该参数识别方法具有较好的收敛速度和稳定性;混凝土本构模型参数的在线更新提高了数值子结构的准确性,进而提高了混合试验的可靠性。
        The accuracy of numerical substructures in structural hybrid simulation attracts more and more attention, especially when structures experience strong nonlinearity under extreme loadings. Model updating technique concerning on the accuracy of the parameters for the constitutive model is proposed to online update these parameters of numerical substructures. Due to their certain limitation, the component and sectional constitutive model for parameter updating in hybrid simulations cannot satisfy the requirements of large, complicated structures. To this end, the parameter identification of material constitutive model is proposed and applied to the hybrid simulation of RC frame structures. The identification of the parameters for concrete constitutive law and the hybrid simulation with model updating were validated through three cases of RC frame hybrid simulation. Results show that the convergence speed and stability of the parameter identification are quite good; the credibility of the hybrid simulation is highly enhanced by improving the accuracy of numerical substructures.
引文
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