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This work presents a complete model for simulating and controlling the final particles distribution in the manufactured part through the resin transfer molding (RTM) process. This model combines: (i) a numerical model simulating the injection of particle-filled resin through a fibrous medium, and (ii) a genetic optimization algorithm to control the final particle distribution in the elaborated composite. A global sensitivity analysis has been applied to identify the parameters (material and process) that have the greatest impact on the particles’ distribution. The results show that the injected particle concentration has the greatest influence, while injection pressure and the initial volume fraction of the preform have negligible effects. Finally, optimization tests have been carried out to evaluate this new approach, targeting specific particle distribution profiles. The results of the optimization show that, in all applications, the optimized initial concentration leads to the closest possible particle distribution to the desired profile.

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Optimization and Simulation of Particle Distribution in Functional Composites Manufactured by the RTM Process

  • 会议论文

  • 发表日期：

    2025年

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  • M. Mtibaa,
  • A. Saouab,
  • A. El Moumen,
  • S. Bouaziz,
  • A. El Hami,
  • M. Haddar

摘要

This work presents a complete model for simulating and controlling the final particles distribution in the manufactured part through the resin transfer molding (RTM) process. This model combines: (i) a numerical model simulating the injection of particle-filled resin through a fibrous medium, and (ii) a genetic optimization algorithm to control the final particle distribution in the elaborated composite. A global sensitivity analysis has been applied to identify the parameters (material and process) that have the greatest impact on the particles’ distribution. The results show that the injected particle concentration has the greatest influence, while injection pressure and the initial volume fraction of the preform have negligible effects. Finally, optimization tests have been carried out to evaluate this new approach, targeting specific particle distribution profiles. The results of the optimization show that, in all applications, the optimized initial concentration leads to the closest possible particle distribution to the desired profile.