Numerical simulation for expansion of preform and optimization of preform in thermoset composites

The expansion of preform and the optimization of preform have become important steps in the molding process. At present, there are some questions in the expansion of thermoset composite material preform and precompression, for example, the inaccurate dimensions, cracks, and wrinkles. For the expansi...

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Bibliographic Details
Published in:Advances in mechanical engineering 2021-05, Vol.13 (5)
Main Authors: Hou, Jiatong, You, Bo, Xu, Jiazhong, Hu, Qiaomu
Format: Article
Language:English
Subjects:
Algorithms
Composite materials
Computer simulation
Cracks
Finite element method
Genetic algorithms
Iterative methods
Molding (process)
Optimization
Polymer matrix composites
Thermosetting resins
Thickening
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Summary:The expansion of preform and the optimization of preform have become important steps in the molding process. At present, there are some questions in the expansion of thermoset composite material preform and precompression, for example, the inaccurate dimensions, cracks, and wrinkles. For the expansion of preform, the finite element inverse algorithm is used as the expansion algorithm, and then the initial solution is optimized by the arc length mapping method, the expansion of preform is realized by the iterative equation which is solved by the ABAQUS solver. The effectiveness of the expansion of preform is verified through the comparison between the finite element inverse algorithm with DYNAFORM. The optimization of the precompression process is researched in order to solved the problems of cracks and wrinkles in the integral precompression method of preform. Firstly, the precompression sequence is adjusted by the precompression method, and then the precompression direction is optimized by the genetic algorithm. Through numerical simulation, the maximum thinning rate is reduced to 13%, and the maximum thickening rate is reduced to 6%, which improve the problems of cracks and wrinkles of preform, and the effectiveness of the optimization method is verified.
ISSN:1687-8132
1687-8140
DOI:10.1177/16878140211017002