DigiTwin is a £5M EPSRC funded programme grant, running from February 2018 – January 2023, led by the University of Sheffield in collaboration with the Universities of Bristol, Cambridge, Liverpool, Southampton & Swansea and ten industrial partners: Airbus, EDF energy, Leonardo Helicopters, LOC engineering, Romax Technology, Schlumberger, Siemens Gamesa, Siemens Turbomachinery, Stirling Dynamics and Ultra Electronics.
The aim of the project is to create a robustly-validated virtual prediction tool called a “digital twin”.
The digital twin is much more than just a numerical model: It is a “virtualised” proxy version of the physical system built from a fusion of data with models of differing fidelity, using novel techniques in uncertainty analysis, model reduction, and experimental validation.
We will deliver the transformative new science required to generate digital twin technology for key sectors of UK industry: specifically power generation, automotive and aerospace.
The objectives of the project are:
- Design: specifically to create new design methodologies that can be applied to dynamic systems that lead to significant improvements in confidence based on digital twin concepts.
- Uncertainty management: to fully integrate quantification, propagation and management of uncertainty into the digital twin framework to radically improve the levels of trust available .
- Validation: to ensure that the digital twin framework can be robustly verified and validated.
This project will empower industry with the ability to create digital twins as predictive tools for real-world problems that (i) radically improve design methodology leading to significant cost savings, and (ii) transform uncertainty management of key industrial assets, enabling a step change reduction in the associated operation and management costs. Ultimately, we envisage that the scientific advancements proposed here will revolutionise the engineering design-to-decommission cycle for a wide range of engineering applications of value to the UK.