Abstract
Thermoplastic fiber reinforced composites (TPFRCs) are becoming more important due to the potential of short part cycle times and recyclability. One major problem of these materials is process stability. During processing, unwanted distortions appear due to residual stresses on different scales. The prediction of these distortions and stresses would reduce the cost of TPFRCs and would assist in achieving a higher market share. For the prediction of the residual stresses, a new multi-scale simulation approach is required. The research presented in this paper is a contribution to the micro-scale model. A method for the representation of the thermoplastic matrix in a 2D micro-scale model is developed. With this, the a solid as well as a semi-liquid state of the polymer which appear during thermoforming can be represented.
Highlights
The demand for lightweight materials is rising due to resource scarcity and environmental awareness
During processing, unwanted distortions appear due to residual stresses on different scales
The prediction of these distortions and stresses would reduce the cost of Thermoplastic fiber reinforced composites (TPFRCs) and would assist in achieving a higher market share
Summary
The demand for lightweight materials is rising due to resource scarcity and environmental awareness. Springs representing the matrix are implemented in the DEM model shown in [5]. These springs are dependent on geometrical and material property factors. The basic rules for the implementation of the matrix springs in the DEM model are explained in the following chapters. 2. Model description The matrix model is based on springs with a stiffness dependent on the material properties and geometry factors. The model calculates the forces for each fiber solely based on the matrix springs. Neighbor search The connections must be established between appropriate fibers and must be attached to appropriate regions of the matrix. After finding the neighboring fibers the stiffness of the matrix portions need to be calculated, which is done in the following
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