Latent diffusion–driven inverse design of damping microstructures with multiaxial nonlinear mechanical targets

Abstract

This study presents an integrated generative framework for the inverse design of damping microstructures in energy-dissipating steel walls (EDSWs) for seismic applications, establishing a seamless pipeline from large-scale pixel-based datasets to latent-space representation, three-dimensional reconstruction, industrial fabrication, and finite element analysis (FEA) verification. Starting from over 140,000 boundary-identical microstructures, a variational autoencoder-based TopoFormer compresses geometric features into latent codes, enabling over 90% reduction in generation complexity while maintaining high reconstruction fidelity. Representative structures are selected via k-means clustering in the latent space and analyzed through nonlinear FEA under shear and compression to construct a performance-labeled dataset. A conditional latent diffusion transformer (DiT) is then trained to map complete nonlinear mechanical performance curves to manufacturable geometries, thus achieving a one-to-many correspondence between target responses and structural configurations. Comparative evaluations show that the proposed DiT framework surpasses multiple CondUNet baselines, achieving the lowest FID (11.367) and the highest SSIM (0.676) with balanced coverage and precision. Experimental validation using laser-cut low-yield-point steel specimens under low-cycle reciprocating loading demonstrates close agreement between generated and target hysteresis curves, confirming both geometric fidelity and mechanical reliability. The results establish a scalable, high-accuracy, and experimentally validated approach for automated, performance-driven microstructure design, providing a practical pathway for incorporating generative artificial intelligence into the engineering development of next-generation seismic energy-dissipation systems. The related codes are available at https://github.com/AshenOneme/DiT-Based-Microstructures-Design.