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 …

Surrogate modeling, also called metamodeling, has evolved and been extensively used
over the past decades. A wide variety of methods and tools have been introduced for …

This paper presents a novel bio-inspired algorithm inspired by starlings' behaviors during
their stunning murmuration named starling murmuration optimizer (SMO) to solve complex …

Architectured materials on length scales from nanometers to meters are desirable for diverse
applications. Recent advances in additive manufacturing have made mass production of …

The field of optimal design of linear elastic structures has seen many exciting successes that
resulted in new architected materials and structural designs. With the availability of cloud …

In this work, a decoupled computational homogenization method for nonlinear elastic
materials is proposed using neural networks. In this method, the effective potential is …

Computation-intensive design problems are becoming increasingly common in
manufacturing industries. The computation burden is often caused by expensive analysis …

The present paper describes a method to enhance the capability of, or to broaden the scope
of computational mechanics by using deep learning, which is one of the machine learning …

Large-scale structural topology optimization has always suffered from prohibitively high
computational costs that have till date hindered its widespread use in industrial design. The …

Evolutionary algorithms (EAs) have received increasing interests both in the academy and
industry. One main difficulty in applying EAs to real-world applications is that EAs usually …