Multiscale design of microwave absorbing sandwich structures via surrogate assisted topology optimization

Abstract

This paper proposes a multiscale design framework for microwave absorbing sandwich structures (MASSs) that simultaneously optimizes macroscopic structural variables and microscopic unit cell geometry. The framework incorporates topology optimization to generate free-form microstructures within the sandwich core. To reduce computational cost and enable rapid exploration of diverse unit cell designs, a surrogate model using an artificial neural network (ANN) is employed. The multiscale optimization problem is formulated with the objective functions of minimizing the total mass and beam deflection of the MASSs. A constraint is imposed on the reflection loss to ensure sufficient microwave absorption at the target frequency. The formulated optimization problem is then solved using three metaheuristic optimization algorithms. To validate the performance of the optimal designs, high-fidelity finite element re-analyses are conducted. Structural validation is performed through 3-point bending and shear deformation analyses, while electromagnetic performance is evaluated using full-wave simulations. The re-analysis results confirm the effectiveness of the proposed multiscale design approach in achieving high-performance MASSs with tailored mechanical and electromagnetic characteristics. © 2025 Elsevier Ltd