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 …

Condition monitoring plays a vital role in ensuring the reliability and optimal performance of
various engineering systems. Traditional methods for condition monitoring rely on physics …

The numerical solution of partial differential equations (PDEs) is challenging because of the
need to resolve spatiotemporal features over wide length-and timescales. Often, it is …

The integration of data and scientific computation is driving a paradigm shift across the
engineering, natural, and physical sciences. Indeed, there exists an unprecedented …

Multiscale modeling is an effective approach for investigating multiphysics systems with
largely disparate size features, where models with different resolutions or heterogeneous …

In this work we present a data-driven method for the discovery of parametric partial
differential equations (PDEs), thus allowing one to disambiguate between the underlying …

With the rapid increase of available data for complex systems, there is great interest in the
extraction of physically relevant information from massive datasets. Recently, a framework …

There have been many techniques developed in recent years to in silico model a variety of
cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling …

The objective of molecular dynamics computations is to infer macroscopic properties of
matter from atomistic models via averages with respect to probability measures dictated by …

Over the past century, the work of chemical engineers has helped transform societies and
the lives of individuals, from the synthetic fertilizers that helped feed the world to the …