Neural networks, and more broadly, machine learning techniques, have been recently
exploited to accelerate topology optimization through data-driven training and image …

There is significant interest today in integrating additive manufacturing (AM) and topology
optimization (TO). However, TO often leads to designs that are not AM friendly. For example …

With the design freedoms afforded by additive manufacturing (AM) processes, an increasing
interest in shape synthesis methods has led to a variety of advances in topology optimisation …

Additive manufacturing (AM) is emerging as a promising technology to fabricate cost-
effective, customized functional parts. Designing such functional, ie, load bearing, parts can …

Additive manufacturing still suffers from redundant support material usage when printing
parts with overhanging features. All the supports will be removed after fabrication, resulting …

Topology optimization has evidenced its capacity to provide new optimal designs in many
different disciplines. However, most novel methods are difficult to apply in commercial …

The focus of this paper is on multi-material topology optimization (MMTO), where the
objective is to not only compute the optimal topology, but also the distribution of two or more …

Temperature-constrained topology optimization for thermo-mechanical coupled problems
under a design-dependent temperature field considering the thermal expansion effect …

Microstructural topology optimization (MTO) is the simultaneous optimization of macroscale
topology and microscale structure. MTO holds the promise of enhancing product …

This work presents a finite element analysis-based, topology optimization (TO) methodology
for the combined magnetostatic and structural design of electrical machine cores. Our …