Projects
Projects: Projects for Investigator |
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| Reference Number | EP/R006768/1 | |
| Title | Digital twins for improved dynamic design | |
| Status | Completed | |
| 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%; |
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| 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 September 2023 | |
| Duration | 68 months | |
| Total Grant Value | £5,112,624 | |
| Industrial Sectors | Mathematical sciences | |
| Region | South West | |
| Programme | NC : Engineering | |
| Investigators | Principal Investigator | Professor DJ Wagg , Mechanical Engineering, University of Bristol |
| Other Investigator | Dr SA Neild , Mechanical Engineering, University of Bristol Professor S Au , Engineering (Level 1), University of Liverpool Professor S Elliott , School of Engineering Sciences, University of Southampton Professor MI Friswell , Engineering, Swansea University Professor K Worden , Mechanical Engineering, University of Sheffield Professor J Clarkson , Engineering, University of Cambridge Professor RS Langley , Engineering, University of Cambridge |
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| Industrial Collaborator | Project Contact , Stirling Dynamics Ltd Project Contact , Siemens AG, Germany Project Contact , Ultra Electronics Limited Project Contact , LOC Group (London Offshore Consultants) Project Contact , Leonardo (UK) Project Contact , Romax Technology Project Contact , Schlumberger Cambridge Research Ltd Project Contact , EDF Energy Project Contact , Airbus UK Ltd |
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| 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 | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 14/09/18 | |
