The concept of multiscale modelling has emerged over the last few decades to describe
procedures that seek to simulate continuum-scale behaviour using information gleaned from …

We consider multiphysics applications from algorithmic and architectural perspectives,
where “algorithmic” includes both mathematical analysis and computational complexity, and …

We present a numerical framework for approximating unknown governing equations using
observation data and deep neural networks (DNN). In particular, we propose to use residual …

Simulating cancer behavior across multiple biological scales in space and time, ie,
multiscale cancer modeling, is increasingly being recognized as a powerful tool to refine …

This paper is a continuation of our work on the development of multiscale numerical scheme
from low-speed isothermal flow to compressible flows at high Mach numbers. In our earlier …

We review and provide a perspective on multiscale modeling of catalytic reactions with
emphasis on mechanism development and application to complex and emergent systems …

Practical Multiscaling covers fundamental modelling techniques aimed at bridging diverse
temporal and spatial scales ranging from the atomic level to a full-scale product level. It …

This review focuses on the role of physical theory and computational electrochemistry for
fundamental understanding, diagnostics and design of new electrochemical materials and …

This review attempts to summarize the physical models and advanced methods used in
computational studies of gas–liquid two-phase jet flows encountered in atomization and …

Most modeling approaches lie in either of the two categories: physics‐based or data‐driven.
Recently, a third approach which is a combination of these deterministic and statistical …