This paper investigates the feasibility of data-driven methods in automating the engineering
design process, specifically studying inverse design of cellular mechanical metamaterials …

This article comprehensively discusses the relevant research progress in the field of
structural topology optimization and the cross-integration development of deep learning …

The temperature history of an additively-manufactured part plays a critical role in
determining process-structure-property relationships in fusion-based additive manufacturing …

Triply period minimal surface (TPMS)-based porous microchannels with freeform surfaces
are extensively used in various applications, eg, bone scaffold design and thermal …

Anisotropic mechanical metamaterials with controllable properties are crucial for additive
manufacturing design. However, manually regulating microstructural anisotropy remains …

This paper introduces MTO-DNNCLS, a novel multiscale topology optimization (TMO)
framework using dual neural networks and cutting level sets. It designs graded lattice …

Abstract 3D lattice structure is a kind of advanced metamaterial structure with excellent
performance, such as lightweight, high specific strength and stiffness, shock damping, heat …

本文综合论述了近年来结构拓扑优化领域与深度学习技术交叉融合发展的相关研究进展.
围绕结构拓扑优化设计的核心方法与关键环节, 以深度学习赋能的角度系统性梳理了两大类赋能 …

Inspired by natural designs, microstructures exhibit remarkable properties, which drive
interest in creating metamaterials with extraordinary traits. However, imperfections within …

Neural networks have gained popularity for modeling complex non-linear relationships.
Their computational efficiency has led to their growing adoption in optimization methods …