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Reference Number EP/R006768/1
Title Digital twins for improved dynamic design
Status Started
Energy Categories NUCLEAR FISSION and FUSION(Nuclear Fission, Nuclear supporting technologies) 20%;
RENEWABLE ENERGY SOURCES(Wind Energy) 20%;
NOT ENERGY RELATED 60%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 50%;
ENGINEERING AND TECHNOLOGY (Mechanical, Aeronautical and Manufacturing Engineering) 50%;
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Professor DJ Wagg
No email address given
Mechanical Engineering
University of Bristol
Award Type Standard
Funding Source EPSRC
Start Date 01 February 2018
End Date 30 June 2023
Duration 65 months
Total Grant Value £5,112,624
Industrial Sectors Aerospace; Defence and Marine; Energy
Region South West
Programme Manufacturing : Manufacturing, NC : Engineering
 
Investigators Principal Investigator Professor DJ Wagg , Mechanical Engineering, University of Bristol (99.993%)
  Other Investigator Professor MI Friswell , Engineering, Swansea University (0.001%)
Professor J Clarkson , Engineering, University of Cambridge (0.001%)
Professor RS Langley , Engineering, University of Cambridge (0.001%)
Professor S Elliott , School of Engineering Sciences, University of Southampton (0.001%)
Dr SA Neild , Mechanical Engineering, University of Bristol (0.001%)
Professor K Worden , Mechanical Engineering, University of Sheffield (0.001%)
Professor S Au , Engineering (Level 1), University of Liverpool (0.001%)
  Industrial Collaborator Project Contact , EDF Energy (0.000%)
Project Contact , Schlumberger Cambridge Research Ltd (0.000%)
Project Contact , Airbus UK Ltd (0.000%)
Project Contact , Romax Technology (0.000%)
Project Contact , Siemens AG, Germany (0.000%)
Project Contact , Stirling Dynamics Ltd (0.000%)
Project Contact , LOC Group (London Offshore Consultants) (0.000%)
Project Contact , Leonardo (UK) (0.000%)
Project Contact , Ultra Electronics Limited (0.000%)
Web Site
Objectives
Abstract The aim of this proposal is to create a robustly-validated virtual prediction tool called a "digital twin". This is urgently needed to overcome limitations in current industrial practice that increasingly rely on large computer-based models to make critical design and operational decisions for systems such as wind farms, nuclear power stations and aircraft. 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. In this project, 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 results from the 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
Publications (none)
Final Report (none)
Added to Database 14/09/18