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Details of Grant 

EPSRC Reference: GR/M85791/01
Title: DARP: DEVELOPMENT OF PREDICTION METHODS FOR TURBINE BLADE HEAT TRANSFER & FILM COOLING FLOWS
Principal Investigator: Dawes, Professor WN
Other Investigators:
Savill, Professor AM Hodson, Professor H
Researcher Co-Investigators:
Project Partners:
Rolls-Royce Plc (UK)
Department: Engineering
Organisation: University of Cambridge
Scheme: Standard Research (Pre-FEC)
Starts: 01 January 2000 Ends: 31 December 2002 Value (£): 158,045
EPSRC Research Topic Classifications:
Aerodynamics
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Energy
Related Grants:
Panel History:  
Summary on Grant Application Form
The present proposal attempts to address and rectify the remaining key weakness in current Computational Fluid Dynamic methods for predicting gas turbine flows - their inability to predict heat transfer and associated film cooling effectiveness - which places severe restrictions on their use for evaluating metal temperatures and hence component life, within the design process. Recent developments in steady and unsteady modelling, simulations and parallelisation of code, now make it possible to consider performing sufficiently resolved full Navier-Stokes computations for film cooling flows and thus improving considerably on the coupled boundary layer, trajectory/stripping models employed by industry. These utilise empirical correlations to simply fix averaged mass, momentum and energy inputs from the secondary to primary flow path through engines without resolving any details of the cooling flows. Work is proposed at both PhD and postdoctoral level with the PhD student first reassessing available design methods and model treatments and then establishing the best academic and industrial approaches by reference to generic blading cases, whilst the RA performs unstructured, adaptively resolved, RANS and LES, for comparison with industrial proprietary data and their own structured and unstructured design code computations. As well as to establish a database for PhD analysis.
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Organisation Website: http://www.cam.ac.uk