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March 15, 2026Engineering Structures0 citationsOpen Access

Topology optimization using the Material Field Series Expansion method and the Covariance Matrix Adaptation-Evolution Strategy: A potential tool for crashworthiness applications

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MDMarcelo Rubens Galdiano DuartePMPablo Andrés Muñoz-RojasFDFabian Duddeck

Key Points

  • This research aims to enhance topology optimization techniques for structures subjected to crash loads, addressing design limitations in conventional methods.
  • Introduced the Material Field Series Expansion (MFSE) method in topology optimization.
  • Applied the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) to optimize structural designs.
  • Examined performance under crash loading scenarios using preliminary data with low impact velocities.
  • Achieved reductions in design variables from thousands to fewer than 100.
  • Obtained optimized topologies within 7% of traditional gradient-based solutions.
  • Demonstrated the feasibility of applying topology optimization in crashworthiness applications.

Abstract

Topology optimization represents a cutting-edge optimization method that facilitates the design of structures beyond the capabilities of conventional human design approaches. Topology Optimization (TO) identifies highly efficient structures capable of carrying significant loads with minimal material usage. However, most TO studies do not account for impact problems or non-linear plastic constitutive material relationships. This paper introduces the application of the Material Field Series Expansion method in conjunction with the Covariance Matrix Adaptation Evolution Strategy with the potential to optimize structures subject to crash loadings and permanent deformation. Although the results of this work are still preliminary using low impact velocities, the method shows great possibilities to address the crashworthiness problem considerably reducing the computational cost. • Combines MFSE and CMA–ES for crash topology optimization. • Reduces design variables from thousands to fewer than 100. • Obtains topologies within 7% of gradient-based solutions. • Allows the use of topology optimization in crash problems. • Enables crash optimization on standard personal computers.

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Cite This Study

Duarte et al. (2026) studied this question.

synapsesocial.com/papers/69b64ccdb42794e3e660df15https://doi.org/10.1016/j.engstruct.2026.122557
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