The question of how methods from the field of artificial intelligence can help improve the
conventional frameworks for topology optimisation has received increasing attention over …

Automated design synthesis has the potential to revolutionize the modern engineering
design process and improve access to highly optimized and customized products across …

Abstract Physics-Informed Neural Networks (PINNs) have recently attracted exponentially
increasing attention in the field of computational mechanics. This paper proposes a novel …

The rapid development of deep learning has opened a new door to the exploration of
topology optimization methods. The combination of deep learning and topology optimization …

Abstract Physics-Informed Neural Networks (PINNs) have recently gained increasing
attention in the field of topology optimization. The fusion of deep learning and topology …

Abstract Machine Learning (ML) techniques have been used in an extensive range of
applications in the field of structural and multidisciplinary optimization over the last few …

Hybrid additive–subtractive manufacturing (HASM) is a revolutionary technique that
fabricates complex-shaped parts in high precision. One setup to finish complicated …

Generative models have significantly influenced both vision and language domains,
ushering in innovative multimodal applications. Although these achievements have …

A number of machine learning methods have been recently proposed to circumvent the high
computational cost of the gradient-based topology optimization solvers. By and large, these …

Simple Summary Breast cancer is the most common cancer, which resulted in the death of
700,000 people around the world in 2020. Various imaging modalities have been utilized to …