数字图像相关技术在多孔气凝胶基复合材料弹性力学常数识别中的应用

采用数字图像相关技术(digital image correlation,DIC)结合有限元模型修正技术(FEMU),通过2维编织高铝纤维增强多孔气凝胶基复合材料正轴及偏轴拉伸实验,同时识别获得了材料面内多个工程弹性常数.通过力学实验结合有限元数值虚拟实验,研究了识别过程中目标函数构成、优化方法、参数初值、位移场随机误差水平对识别结果和效率的影响.研究表明针对2维编织多孔气凝胶基复合材料,选取DIC实测位移和有限元数值计算位移的方差作为目标函数,通过L-M非线性最小二乘优化方法,计算参数敏感度矩阵,可同时识别获得多个加载面内材料力学性能参数,识别效率高,识别过程对参数初值、位移场随机误差水平不敏感,鲁棒性好.

Identification of a Set of Elastic Parameters in 2D Plain Woven Aerogel-Based Matrix Composites Using Mixed Numerical-Experimental Method

Using digital image correlation technology (DIC) and finite element model correction technique (FEMU), multiple mechanical engineering constants in the two-dimensional woven high aluminum fiber reinforced porous aerogel matrix composites were identified through on-axis and off-axis tensile tests. The effects of objective function construction, optimization method, initial value of parameter and random error in the measured displacement field on the identifying results and efficiency were investigated by mechanical experiments and finite-element-based numerical virtual experiments. The results show that, for two-dimensional woven porous aerogel matrix composites, when the variance of the DIC measured displacement and finite element calculated displacement is chosen as the objective function and the L-M nonlinear least-square optimization method is used to calculate the sensitivity matrix, the multiple mechanical properties in the loading surface can be identified simultaneously with high efficiency. The proposed method is insensitive to the differences in initial values of material constitutive parameters and random error in the DIC displacement measurement and has strong robustness.