Topology optimization (TO) is a method of deriving an optimal design that satisfies a given
load and boundary conditions within a design domain. This method enables effective design …

In this paper, a deep learning-based model is proposed which is capable of automatically
generating the structural topology configurations with the minimum structural compliance …

Abstract Machine learning (ML) is reshaping additive manufacturing (AM) with its potent
capability of data analysis, antonomous learning and intelligent decision-making. ML …

This research develops a highly effective deep-learning-based surrogate model that can
provide the optimum topologies of 2D and 3D structures. In general, structural topology …

This paper investigates the potential of Deep Learning (DL) for data-driven topology
optimization (TO). Unlike the rest of the literature that mainly applies DL to TO from a …

Despite the freedom Additive Manufacturing (AM) offers when manufacturing organic
shapes, it still requires some geometrical criteria to avoid a part's collapse during printing …

Recent developments in Deep Learning (DL) suggest a vast potential for Topology
Optimization (TO). However, while there are some promising attempts, the subfield still lacks …

This paper improves on the performance of the Deep Learning Additive Manufacturing
driven Topology Optimization (DL-AM-TO) approach that was proposed in [4]. DL-AM-TO is …

Artificial intelligence (AI) has progressed significantly during the last several decades, along
with the rapid advancements in computational power. This advanced technology is currently …