Affiliation:
1. Department of Engineering Systems and Management, Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates
2. Department of Mechanical and Materials Engineering, Masdar Institute of Science and Technology, Abu Dhabi, United Arab Emirates
Abstract
Fiber-reinforced plastics are a cost efficient solution for many structural applications as they offer sufficient stiffness and a large freedom of shapes provided by injection molding. These materials are increasingly being used for making structural components, which are subjected to complex and repeated mechanical loads. Therefore, the need for a method to predict the mechanical behavior of such materials is important. In this work, a through process modeling methodology suitable for coupling the microstructure and the macroscopic response of composites considering plastic injection molding process for different injection modes is presented. The key tasks discussed in this work are (1) simulation of the whole manufacturing process in order to obtain the fiber orientation distribution at each point of the part; (2) estimation of local effective properties using the orientation tensor obtained by performing a two-step homogenization and (3) prediction of the mechanical response as a function of a local anisotropy using a mean-field homogenization technique which is based on assumed relationships between average values of strain and stress fields in each phase. The scheme suggested allows to analyze the influence of processing conditions on elastic properties of composites. By changing these conditions, for example, the injection mode (central or linear), the cavity thickness, the fiber volume fraction, the microstructure and hence the local elastic properties of the material can be tailored. Thus, for desired structural response of composites, the optimum filling parameters can be chosen even at the stage of design.
Subject
Materials Chemistry,Polymers and Plastics,Mechanical Engineering,Mechanics of Materials,Ceramics and Composites
Cited by
8 articles.
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