Failure prediction for fiber reinforced polymer composites based on virtual experimental tests

被引:7
|
作者
Zhang, Binbin [1 ]
Ge, Jingran [1 ]
Cheng, Feng [3 ]
Huang, Jian [4 ]
Liu, Shuo [1 ]
Liang, Jun [1 ,2 ]
机构
[1] Beijing Inst Technol, Inst Adv Struct Technol, Beijing 100081, Peoples R China
[2] Beijing Key Lab Lightweight Multifunct Composite M, Beijing 100081, Peoples R China
[3] China Acad Launch Vehicle Technol, Beijing 100076, Peoples R China
[4] Nanjing Fiberglass Res & Design Inst, Nanjing 211101, Peoples R China
基金
中国国家自然科学基金;
关键词
Carbon fiber reinforced polymer; composites; Matrix nonlinear behavior; Virtual testing method; Failure envelope; TRANSVERSE COMPRESSION; COMPUTATIONAL MICROMECHANICS; STRESS/STRAIN BEHAVIOR; INTERFACIAL PROPERTIES; MECHANICAL-PROPERTIES; SHEAR BEHAVIOR; PART II; CRITERIA; MATRIX; MODELS;
D O I
10.1016/j.jmrt.2023.05.123
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A novel virtual experimental testing methodology that utilizes virtual microstructures representative of genuine fiber distribution, is devised to micromechanically simulate and scrutinize the inter-fiber failure of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The experimentally identified nonlinear behavior of the matrix is incorporated by utilizing the Drucker-Prager plasticity model. The interaction behavior between fiber-matrix interfaces, including delamination and friction, is represented by means of a cohesive interaction approach. The results of virtual testing demonstrate that interfacial parameters and the epoxy properties exert considerable influences on the predicted macroscopic responses under individual loading cases. Additionally, the interface and epoxy material properties are inversely determined through virtual testing analysis assisted by experimental results. Furthermore, the validated virtual testing method is utilized to obtain the inter-fiber failure envelope of the composites. The predictions are then compared with those theoretically derived from classical failure criteria. The current comparative studies indicate that the existing classical failure criterion exhibits limited predictive ability with computational data. & COPY; 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:8924 / 8939
页数:16
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