Topology optimization of periodic structures for crash and static load cases using the evolutionary level set method

This research-oriented project development support framework addresses the challenges of periodic topology optimization (PTO) under highly non-linear crashworthiness and static loading conditions. Traditional gradient-based optimization techniques often struggle with crash scenarios due to the non-smooth nature of transient dynamic responses and the unavailability of analytical sensitivities. To overcome these limitations, this study provides guidance on implementing a periodic evolutionary level set method (P-EA-LSM). The methodology utilizes a low-dimensional level-set representation driven by moving morphable components (MMC) to parameterize a single representative unit cell. This unit cell is systematically patterned across the global design domain to form a periodic structure. An evolutionary algorithm is employed to optimize the unit cell topology,

while the structural responses under static and dynamic crash loads are evaluated globally. The proposed framework supports the evaluation of energy absorption, structural compliance, and deformation behavior. By decoupling the geometric parameterization from the finite element mesh, this approach mitigates numerical instabilities and ensures manufacturing feasibility. The research direction facilitates the design of high-performance, lightweight lattice-like structures suitable for automotive and aerospace crashworthiness applications.

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