基于遗传算法的钢筋混凝土剪力墙Bouc-Wen模型参数识别

Parametric Identification of RC-shearwall Based on Bouc-Wen Model Using Genetic Algorithm

对钢筋混凝土剪力墙构件层次的滞回行为的合理模拟有着重要的应用及研究价值,但目前剪力墙在反复荷载作用下的非线性模拟仍然存在困难。Bouc-Wen模型是一种平滑模型,以解析公式描述滞回行为,在结构和机械领域有着广泛的应用。本文将剪力墙构件在往复荷载作用下的恢复力-位移关系简化为单自由度Bouc-Wen滞回模型。通过分析Bouc-Wen模型特征,给出其参数取值限制,运用遗传算法在已有试验数据基础上完成模型的参数识别。定参后的单自由度Bouc-Wen滞回模型能较好反映构件在往复荷载作用下的强度刚度退化和恢复力峰值特点,模型可作用宏观单元用于结构模型数值模拟。识别过程对类似模型的参数识别具有参考价值。

Appropriate prediction of hysteretic behavior of reinforced concrete shear wall structural componentis of great importance in both engineering applications and research, but it still has difficulties so far. The Bouc-Wen model, widely used in structural and mechanical engineering, gives an analytical description of a smooth hysteretic behavior. This paper simplified the restoring force-displacement relation of RC shear wall component into a single-degree-of-freedom Bouc-Wen hysteretic model. The parameters of the model is identified using genetic algorithm based on experimental data with suitable parameter limits which introduced by analyzing characters of the Bouc-Wen model. This SDOF Bouc-Wen model can capture the deteriorating characters such as strength and stiffness degradation of the RC shearwall component under reversed cyclic loading and therefore can be used as a macro-element ina structural analysis. The identification process may be a reference to Parameter Identification to similar models. The Bouc-Wen model, widely used in structural and mechanical engineering, gives an analytical description of a smooth hysteretic behavior.