A unified cohesive zone model for simulating adhesive failure of composite structures and its parameter identification
A unified cohesive zone model for simulating adhesive failure of composite structures and its parameter identification
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模拟复合材料结构粘合破坏的统一内聚区模型及其参数辨识
DOI：
10.1016/j.compstruct.2017.09.012
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发表时间：
2017-09
影响因子：
6.3
通讯作者：
Wang Xiaogui
中科院分区：
文献类型：
--
作者：
Xu Yangjian;Guo Yuanqi;Liang Lihua;Liu Yong;Wang Xiaogui
事实证明，在许多情况下，不同内聚规律的形状效应是不可忽视的。本文进一步研究和阐明了这种效应。为了更准确地模拟复合材料结构的粘结破坏，有必要建立一个统一的粘结区模型（CZM），该模型能够逼近现有的任意粘结规律。为此，一种改进的基于插值的CZM（ICZM）已被开发。这种模型的参数通常通过反分析来获得。然而，反分析的成功与否很大程度上取决于模型参数的初始估计及其分析技术。因此，我们进一步发展了一种与现有ICZM完全匹配的两步反分析方法。基于伪实验和真实的实验数据的验证表明，所提出的模型和方法是稳健的，可以统一描述各种粘结失效，而不需要考虑针对不同类型的断裂问题选择合适的CZM。最后，结合两类实验信息，提出了一种新的反分析方法，以提高解的可靠性和缓解反问题的不适定程度。
It has been proven that the shape effect of different cohesive laws can not be ignored in many cases. Such an effect is further investigated and clarified in the present paper. In order to more accurately simulate the adhesive failures of composite structures, it is necessary to develop a unified cohesive zone model (CZM) capable of approaching an arbitrary existing cohesive law. Toward this end, an improved interpolation-based CZM (ICZM) has been developed. The parameters of such a model were generally obtained by inverse analysis. However, success of the inverse analysis greatly depends on the initial guess of model parameters and its analysis technique. Therefore, a two-step inverse analysis method, perfectly matching the present ICZM, has been further developed in our work. The verifications based on both pseudo-experimental and real experimental data have shown that the present developed model and method are robust and can uniformly describe various adhesive failures without need to consider selection of appropriate CZM for different types of fracture problems. Finally, a novel inverse analysis method in combination with two types of experimental information, has been developed to improve the solution reliability and relieve the ill-posed extent of inverse problems.
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影响因子：
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