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Bayesian parameter identification of hysteretic behavior of composite walls

机译:复合墙体滞回性能的贝叶斯参数辨识

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摘要

A Bayesian probabilistic approach is applied for parameter identification of a hysteretic model using laboratory test data in this paper. A hysteretic model for multi-grid composite walls is proposed to model the behavior of multi-grid composite wall specimens under lateral cyclic loading. Effects of stiffness degradation, strength degradation and pinching are considered. The test data consists of observed hysteretic curves of precast composite wall specimen, composite wall specimen reinforced by light steel, retrofitted composite wall specimen and cast-in-place composite wall specimen. Using the Bayesian approach, the identification results are presented in terms of the most probable value and posterior covariance matrix of model parameters. The implied hysteretic and backbone curves with their uncertainties identified based on the test data are compared with their observed counterparts.
机译:本文采用贝叶斯概率方法,利用实验室测试数据对滞后模型进行参数辨识。提出了一种多层网格复合墙的滞回模型,以模拟多层网格复合墙在横向循环荷载作用下的行为。考虑了刚度降低,强度降低和收缩的影响。试验数据包括预制复合墙试样,轻钢增强的复合墙试样,改型复合墙试样和现浇复合墙试样的观测滞后曲线。使用贝叶斯方法,以最可能的值和模型参数的后协方差矩阵表示识别结果。将隐含的磁滞曲线和主干曲线以及根据测试数据确定的不确定性与观察到的对应曲线进行比较。

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