多级变幅疲劳荷载下预应力混凝土梁刚度退化

基于材料疲劳损伤和损伤累积的非线性模型,将混凝土损伤弹模和钢筋损伤剩余面积引入到截面刚度计算中,推导了预应力混凝土梁在多级变幅疲劳荷载下的刚度退化模型。结合遗传算法进行了参数拟合,提出了疲劳刚度损伤退化预测的神经网络方法,编制了相应的Matlab计算程序。通过预应力混凝土梁多级变幅疲劳试验对模型参数和结果进行了拟合、修正和验证。结果表明:多级变幅疲劳荷载下预应力混凝土梁刚度退化存在类似混凝土损伤发展的三阶段规律,混凝土材料应采用能体现损伤发展三阶段规律的损伤模型;刚度退化模型各参数物理意义明确,理论分析结果与试验结果偏差普遍在5%以下;基于遗传算法进行参数拟合方法和基于神经网络预测方法的结果具有较高精度,可以为预应力混凝土梁的疲劳耐久性评估提供一定的参考。

Fatigue stiffness degradation of prestressed concrete beam under multilevel amplitude cycle loading

Based on the nonlinear fatigue damage model and damage accumulative model of materials,the damage elastic modulus of concrete and the damage residual area of steel reinforcement bars and prestressed tendons were introduced into the section stiffness calculation.The stiffness degradation model of the prestressed concrete beam under multilevel amplitude cycle loading was deduced,and genetic algorithm was applied in parameter determination.Then,the neural network method for forecasting the fatigue stiffness degradation was proposed and Matlab program code of the calculation model was generated.Experiment of prestressed concrete beam under multilevel amplitude cycle loading was carried out to establish the parameters,improve the calculation accuracy and verify the calculation results.It is suggested that the stiffness degradation of the prestressed concrete beam under multilevel amplitude cycle loading could be divided into three stages.The model calculation results agree well with experiment results,with a deviation within 5%.The genetic algorithm based model parameter fitting method and the neural network based forecasting method can give accurate results,thus providing useful reference for the estimation of fatigue resistance of prestressed concrete beam.