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Details of Grant 

EPSRC Reference: EP/K014188/1
Title: Theme 5/6 High Performance Computing (HPC) and Simulation Knowledge Mining and Abstraction (SKMA)
Principal Investigator: Payne, Professor MC
Other Investigators:
Clarkson, Professor J Nikiforakis, Professor N Calleja, Dr PJ
Researcher Co-Investigators:
Dr DC Wynn
Project Partners:
Department: Physics
Organisation: University of Cambridge
Scheme: Standard Research
Starts: 18 February 2013 Ends: 31 March 2018 Value (£): 1,437,554
EPSRC Research Topic Classifications:
Computer Graphics & Visual. Design Processes
High Performance Computing Information & Knowledge Mgmt
Numerical Analysis
EPSRC Industrial Sector Classifications:
Manufacturing
Related Grants:
Panel History:
Panel DatePanel NameOutcome
03 Oct 2012 Programme for Simulation Innovation (JLR) Announced
Summary on Grant Application Form
It costs roughly £0.5 million to build a prototype of a car. Many prototypes need to be constructed during the process of designing a new vehicle and also when developing a new version of an existing vehicle. Clearly, anything that can reduce the number of prototypes needed will have a significant impact on the cost of automobile design. Simulation is already used extensively in the automotive industry. For instance, assessing car crash worthiness during the design process is now entirely performed computationally. The aim of the Programme for Simulation Innovation is to increase the use of simulation in car design. Indeed it can be seen as a further significant step towards the goal of 'virtual vehicle design' where the entire design process is carried out on the computer. However, increasing the amount of simulation used in the design process will significantly increase the demands on the computational ecosystem and, perhaps more seriously, introduce many layers of complexity which could lead to inefficient use of the computational ecosystem and poor decision making. Our work is targeted at addressing these potential problems by increasing the efficiency of individual computational tasks, automatically documenting simulation data to avoid misintepretation, allow data re-use and enable automated data archiving protocols and, finally, modelling the complexity of the virtual vehicle design task and, based on this, implementing rules to resolve conflicts in the computational and data flows and in the decision stages of the design process.
Key Findings
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Summary
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Organisation Website: http://www.cam.ac.uk