EPSRC Reference: |
GR/S63106/01 |
Title: |
Performance Based Engineering: The Computional Challenge |
Principal Investigator: |
Taylor, Professor CA |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Civil Engineering |
Organisation: |
University of Bristol |
Scheme: |
Standard Research (Pre-FEC) |
Starts: |
21 August 2003 |
Ends: |
20 February 2004 |
Value (£): |
46,606
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EPSRC Research Topic Classifications: |
New & Emerging Comp. Paradigms |
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EPSRC Industrial Sector Classifications: |
Aerospace, Defence and Marine |
Construction |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
It is now an essential requirement to view modern engineering in terms of the performance of the whole system over its complete life cycle. Such a philosophy poses extreme computational challenges in the creation of reliable models for forecasting the short, medium and long term performance of highly complex, nonlinear, dynamic systems. The aim of this proposed network is to develop novel computational strategies which will meet these challenges and enable the new performance based engineering paradigm to be applied to highly complex engineering systems. The work will be undertaken in two interlinked themes. The first theme is that of computational modelling of large scale complex engineering systems. A key issue is to understand how to identify, and if possible control through design and operation, the emergent properties and performance characteristics of these systems. The computational approach will need to include parametric studies, optimisation, and crucially, uncertainty and risk. The second theme relates to a novel technique in combined computational - experimental testing called 'real time dynamic substructuring'. This technique enables 'critical components' from complex engineering systems to be tested experimentally while coupled to a real time computational model of the remaining part of the system. Here, the computational challenges are in real time control, synchronisation, multiple time scale, forward predictive algorithms and data transfer.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.bris.ac.uk |