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<p>This study investigates the crashworthiness properties of carbon fiber sheet molding compound (CF-SMC) material, highlighting its potential for applications requiring effective energy absorption. While CF-SMC exhibits promising specific energy absorption values, further optimization of both the material and its geometrical design is necessary to enhance performance. Notably, CF-SMC's manufacturing advantages, including faster production and the capability to integrate recycled fibers, make it a cost-effective and sustainable option for industries prioritizing efficiency and environmental responsibility. The short-fiber material model implemented within the ESI-VPS software was calibrated by means of tensile and compressive test simulations, and it was validated through crash simulations. The results indicate a strong correlation between experimental data and numerical predictions, confirming the effectiveness of the modeling approach.</p>

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Experimental and Numerical Assessment of Sheet Molding Compound Composite Crushing Behavior

  • 期刊论文

  • 发表日期：

    2025年3月3日

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  • Maria Pia Falaschetti,
  • Francesco Semprucci,
  • Luca Raimondi,
  • Davide Serradimigni

摘要

This study investigates the crashworthiness properties of carbon fiber sheet molding compound (CF-SMC) material, highlighting its potential for applications requiring effective energy absorption. While CF-SMC exhibits promising specific energy absorption values, further optimization of both the material and its geometrical design is necessary to enhance performance. Notably, CF-SMC's manufacturing advantages, including faster production and the capability to integrate recycled fibers, make it a cost-effective and sustainable option for industries prioritizing efficiency and environmental responsibility. The short-fiber material model implemented within the ESI-VPS software was calibrated by means of tensile and compressive test simulations, and it was validated through crash simulations. The results indicate a strong correlation between experimental data and numerical predictions, confirming the effectiveness of the modeling approach.