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Using Experimental Data to Improve Crash Modeling for Composite Materials

  • Morteza Kiani
  • Hirotaka Shiozaki
  • Keiichi Motoyama
Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Accurate simulation of the composite material crash tubes subjected to axial impact is a challenging field of study in automotive or aerospace industry; however, analytical prediction of the crashworthiness behavior in composite materials is limited. In this paper, three different analytical approaches are presented which have been used to study the crashworthiness of a pultruded glass-polyester tube. The first model is established based on the single shell elements. This approach is very effective, when composite part is assembled in the full structure. However, this technique can be used when the experimental result is available. In the second approach, the crash tube is modeled by using multi-layered shell element (delamination model). Relying on coupon test information of the composite material, this modeling technique can provide reasonable result for the energy absorption of the tube. The third modeling approach is looking for crashworthiness prediction of the discussed tube by using the first model which its parameters are tuned based on the result of the second model. Finally, the sensitivity of the result is studied by changing the major parameters in the first model. This paper is looking for finding a method to reasonably estimate the crashworthiness behavior in the composite materials.

Keywords

Energy Absorption Carbon Fiber Reinforce Plastic Coupon Test Contact Algorithm Composite Tube 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Society for Experimental Mechanics, Inc. 2013

Authors and Affiliations

  • Morteza Kiani
    • 1
  • Hirotaka Shiozaki
    • 2
  • Keiichi Motoyama
    • 3
  1. 1.Center for Advanced Vehicular System, Computational Engineering ProgramMississippi State UniversityStarkvilleUSA
  2. 2.Mitsubishi Motors CorporationOkazakiJapan
  3. 3.Center for Advanced Vehicular SystemMississippi State UniversityStarkvilleUSA

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