Multiscale Concurrent Topology Optimization and Mechanical Property Analysis of Sandwich Structures

Area of Science:

• Materials Science
• Mechanical Engineering
• Computational Mechanics

Background:

• Traditional topology optimization methods often overlook microstructural details.
• Sandwich structures offer excellent stiffness-to-weight ratios but require precise design.
• Concurrent optimization at multiple scales is crucial for advanced material design.

Purpose of the Study:

• To develop and present a novel multiscale topology optimization method for sandwich structures.
• To concurrently optimize both the macro-scale structure and the micro-scale core.
• To validate the proposed method through numerical simulations and experimental testing.

Main Methods:

• Integration of Bi-directional Evolutionary Structural Optimization (BESO) and Solid Isotropic Material with Penalization (SIMP) methods.
• Development of three concurrent optimization strategies: MM, MMG, and MMLG.
• Numerical analysis of a sandwich simply supported beam, followed by micro-nano 3D printing and experimental validation.

Main Results:

• The multiscale topology optimization method demonstrated superior performance compared to traditional macroscopic methods.
• Optimized structures exhibited enhanced deformation modes, load-bearing capacity, and energy absorption.
• Experimental results closely matched numerical simulations, confirming the method's efficacy.

Conclusions:

• The proposed multiscale topology optimization effectively enhances the mechanical properties of sandwich structures.
• The method is versatile and applicable to various sandwich beam designs (2D and 3D).
• This research paves the way for designing high-performance sandwich materials with tailored microstructures.