基于修正Burgers模型的浇筑式沥青混合料黏弹性参数确定方法

Viscoelastic parameters determination method of pouring type asphalt mixture based on modified Burgers model

黏弹性是浇筑式沥青混合料的重要特性之一。首先利用Laplace变换,将修正Burgers模型的黏弹性参数转化为剪切松弛模量的Prony级数形式,以满足ANSYS等有限元软件的黏弹性材料参数输入要求,并通过ANSYS模拟验证了公式的正确性;对浇筑式沥青混合料进行了单轴贯入蠕变试验;利用Matlab软件对蠕变柔量进行拟合,获得了修正Burgers模型表征的黏弹性参数;基于推导的Prony级数公式,对单轴贯入蠕变试验进行有限元模拟,并进行了实际试验的模型应力修正。结果表明:有限元模拟结果与理论计算结果的相对误差小于1%,验证了本研究推导的Prony级数公式的可靠性;应力修正后,有限元模拟结果与试验数据的相对误差能控制在6%以内,显著提高了模型参数识别精度。

Viscoelasticity is one of the important characteristics for gussasphalt. The objective of this study is to find the correct viscoelastic material parameters for the novel gussasphalt applied in the 4th Changjiang （Yangtze） River Bridge based on the modified Burgers model. In this study, we first converted the viscoelastic parameters of modified Burgers model into the explicit Prony series form of the shear relaxation modulus using the Laplace transform. Thus they could be transformed into the required material parameters that were used to input into the finite element software such as ANSYS, and the correctness of the formula was verified by ANSYS simulation. At the same time, the uniaxi- al penetration creep experiment of gussasphalt was carried out at constant temperature of 40, 50, and 60℃, respec- tively. The creep compliance was fitted by Matlab program, and the viscoelastic parameters were obtained by modified Burgers model, respectively. Based on the explicit Prony series formulas developed in this study, the uniaxial penetration creep experiment was simulated by finite element software. Based on the analysis of the vertical normal stress in the actual experimental model, the stress correction coefficient α was presented to carry out the stress correction in the model, and the viscoelastic material parameters with higher accuracy were obtained at different temperature. The results indicated that the relative error between the finite element simulation and the theoretical calculation is lower than 1%, which validated the reliability of explicit Prony series formula deduced in this study. After the stress correction, the relative error between the finite element simulation and the experimental data could be controlled within 6%, which significantly improved the accuracy of model parameter identification.