Digital Engineering

Digital Engineering is a dynamic field that includes a diverse array of simulation and modelling techniques. These techniques find applications not only within digital engineering but also in our other three key research areas. The adaptability of digital engineering lies in its ability to incorporate technologies that enhance and optimise processes within these domains.

Artificial intelligence (AI) and machine learning have emerged in digital engineering as powerful tools for improving engineering practices. These technologies excel at analysing complex data, identifying patterns, and making predictions, contributing to the development and optimisation of a wide range of systems and processes.

Our research focuses on the development of advanced AI techniques and the application of advanced modelling and simulation tools across broad engineering areas, including energy and biotechnology, and the digital transformation and optimisation of continuous manufacturing of pharmaceutical products.

One frontier research area includes the development of digital twins particularly in electrochemical systems like fuel cells. A digital twin is a digital replica of a living or non-living physical entity that mirrors real-world changes in real-time.

In the context of fuel cells, these digital twins prove invaluable for research and development. They simulate and monitor fuel cell behaviour with precision, offering crucial insights into performance, maintenance, and optimisation. Our advanced full-range scale fuel cell simulation platform plays a pivotal role in advancing the commercial development of fuel cell vehicles, thereby contributing to zero-emission transportation solutions.