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Numerical Simulation and Multi-objective Optimization for Curing Process of Thermosetting Prepreg

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Abstract

In order to improve the curing quality of thermosetting prepreg, reduce the unevenness of the temperature field and the curing degree field during curing process, and improve the curing efficiency, a multi-objective optimization method is used to optimize the cure cycle. In this paper, the coupling of heat conduction, cure kinetics, are used to analyze curing process of thermosetting prepreg. Firstly, a quarter finite element analysis model of the 4-layer unidirectional laminate is established in ABAQUS, the change of the cure cycle is considered, the temperature field and the curing degree field are analyzed. After comparison, the results of numerical simulation are basically consistent with the data in the reference paper. Secondly, surrogate model was established by Genetic Algorithm- Back Propagation (GA-BP) neural network, and the target value is predicted accurately under the given process parameters. The GA-BP surrogate model is used as the fitness function, and the Non-dominated sorting genetic algorithm II (NSGA-II) algorithm is used to select the maximum value of temperature overshoot and the curing time as the objectives to perform multi-objective optimization of process parameters. Finally, the research results show that the optimization method can reduce the maximum value of temperature overshoot, improve the uniformity of curing, and reduce curing time. The optimization strategy of “finite element numerical simulation-GA-BP neural network-NSGA-II optimization algorithm” is proposed, which has positive significance for the optimization of composites molding process.

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Data Availability

The data presented in this study are available on request from the corresponding author.

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Acknowledgements

This work was supported by Heilongjiang Province Applied Technology Research and Development Plan, grant number GA20A401.

Funding

This research was funded by Heilongjiang Province Applied Technology Research and Development Plan, grant number GA20A401.

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Authors and Affiliations

  1. School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China

    Jiatong Hou & Tianyu Fu

  2. School of Automation, Harbin University of Science and Technology, Harbin, 150080, China

    Bo You, Jiazhong Xu & Tao Wang

  3. Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration, Harbin University of Science and Technology, Harbin, 150080, China

    Jiatong Hou, Bo You, Jiazhong Xu, Tianyu Fu & Tao Wang

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  1. Jiatong Hou
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  2. Bo You
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  5. Tao Wang
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Contributions

Conceptualization, J.H.; methodology, J.H.; software, J.H.; validation, J.H., T.F., and T.W.; formal analysis, J.H.; investigation, J.H.; resources, J.H.; data curation, J.H.; writing–original draft preparation, J.H.; writing–review and editing, B.Y. and J.X.; visualization, J.H.; supervision, B.Y. and J.X.; project administration, B.Y. and J.X.; funding acquisition, B.Y. and J.X. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Bo You.

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Hou, J., You, B., Xu, J. et al. Numerical Simulation and Multi-objective Optimization for Curing Process of Thermosetting Prepreg. Appl Compos Mater 29, 1409–1429 (2022). https://doi.org/10.1007/s10443-022-10022-7

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