Optimization of Honeycomb Geometry for Bumper Beam Using Response Surface Methodology

Authors

  • Fauzi Ibrahim Lampung State Polytechnic , Department Automotive Engineering Technology Author
  • Teuku Marjuni Universitas Malahayati image/svg+xml , Mechanical Engineering Author
  • Rina Febrina Universitas Malahayati image/svg+xml , Civil Engineering Author
  • Agus Apriyanto Lampung State Polytechnic , Department Automotive Engineering Technology Author
  • Novia Utami Putri Lampung State Polytechnic , Department Automotive Engineering Technology Author
  • Retno Wahyudi Author
  • Alexander Sembiring Lampung State Polytechnic , Department Automotive Engineering Technology Author
  • Adam Wisnu Murti Lampung State Polytechnic , Department Automotive Engineering Technology Author

DOI:

https://doi.org/10.47355/32hg6e19

Keywords:

Bumper beam, Honeycomb structure, Response Surface Methodology (RSM), Finite Element Analysis (FEA), Crashworthiness, Energy absorption

Abstract

The bumper beam serves as a vital element in a vehicle’s safety system because it absorbs impact energy and reduces structural damage during a collision. The shape and configuration of its inner structure especially the honeycomb pattern greatly affect how efficiently the energy is absorbed and how light the component can be made. In this research, the geometric parameters of a hexagonal honeycomb used in an automotive bumper beam were optimized through the Response Surface Methodology (RSM). Finite Element Analysis (FEA) using ABAQUS/Explicit was carried out to examine how the cell wall thickness, cell size, and honeycomb depth influence several crash performance indicators, including specific energy absorption (SEA), peak impact force, and deformation behavior. The Central Composite Design (CCD) was applied to build the RSM model and determine the best parameter combination. The results revealed that variations in honeycomb geometry strongly affect both the load path and energy absorption capacity. The developed RSM model showed a strong predictive accuracy with an R² value above 0.95. The optimized configuration successfully lowered the peak impact force by about 18.7% while increasing SEA by 22.3% in comparison to the baseline model. Overall, this approach confirms that RSM can be used effectively to optimize multiple parameters in lightweight automotive component design, leading to better crashworthiness and more efficient material utilization.

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Published

2025-05-18