Micromechanical Progressive Failure Analysis of Fiber-Reinforced Composite Using Refined Beam Models

被引:0
作者
Kaleel, I. [1 ]
Petrolo, M. [1 ]
Waas, A.M. [2 ,3 ]
Carrera, E. [1 ]
机构
[1] Department of Mechanical and Aerospace Engineering, Politecnico di Torino Turin, Turin,10129, Italy
[2] Department of Aeronautics and Astronautics, University of Washington Seattle, Seattle,WA,9819, United States
[3] Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin,10129, Italy
来源
Journal of Applied Mechanics, Transactions ASME | 2018年 / 85卷 / 02期
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摘要
An efficient and novel micromechanical computational platform for progressive failure analysis of fiber-reinforced composites is presented. The numerical framework is based on a recently developed micromechanical platform built using a class of refined beam models called Carrera unified formulation (CUF), a generalized hierarchical formulation which yields a refined structural theory via variable kinematic description. The crack band theory is implemented in the framework to capture the damage propagation within the constituents of composite materials. The initiation and orientation of the crack band in the matrix are determined using the maximum principal stress state and the tractionseparation law governing the crack band growth is related to the fracture toughness of the matrix. A representative volume element (RVE) containing randomly distributed fibers is modeled using the component-wise (CW) approach, an extension of CUF beam model based on Lagrange type polynomials. The efficiency of the proposed numerical framework is achieved through the ability of the CUF models to provide accurate threedimensional (3D) displacement and stress fields at a reduced computational cost. The numerical results are compared against experimental data available in the literature and an analogous 3D finite element model with the same constitutive crack band model. The applicability of CUF beam models as a novel micromechanical platform for progressive failure analysis as well as the multifold efficiency of CUF models in terms of CPU time are highlighted. © 2018 by ASME.
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