With the technology being developed to manufacture metallic parts using increasingly
advanced additive manufacturing processes, a new era has opened up for designing novel …

A timely review is presented on artificial intelligence (AI) and, more specifically, deep
learning, which is a subfield of machine learning (ML), applied to the design and behaviour …

Designing materials for targeted performance requirements as required in Integrated
Computational Materials Engineering (ICME) demands a combined strategy of bottom–up …

Data-driven methods are attracting growing attention in the field of materials science. In
particular, it is now becoming clear that machine learning approaches offer a unique avenue …

Research trends in metal plasticity over the past 25years are briefly reviewed. The myriad of
length scales at which phenomena involving microstructure rearrangement during plastic …

Practical multiscale materials design is contingent on the availability of robust and reliable
reduced-order linkages (ie, surrogate models) between the material internal structure and its …

A unified variational theory is proposed for a general class of multiscale models based on
the concept of Representative Volume Element. The entire theory lies on three fundamental …

This paper develops an approach to model the deformation and fracture of heterogeneous
materials at different scales (including multiscale modeling) within a discrete representation …

Although already suggested in the middle of the 19th century, have material models that
include higher gradients of the kinematical variables become a blossoming field of research …

Проблема построения конститутивных моделей, позволяющих описывать поведение
материалов в широких диапазонах изменения параметров воздействия (температур …