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Details of Grant 

EPSRC Reference: GR/K23263/01
Title: QUANTITATIVE ALLOY DESIGN TOOLS FOR NI-BASE SUPERALLOYS
Principal Investigator: Bhadeshia, Professor H
Other Investigators:
MacKay, Professor DJ
Researcher Co-Investigators:
Project Partners:
Rolls-Royce Plc (UK)
Department: Materials Science & Metallurgy
Organisation: University of Cambridge
Scheme: Standard Research (Pre-FEC)
Starts: 30 March 1995 Ends: 29 August 1998 Value (£): 145,351
EPSRC Research Topic Classifications:
Eng. Dynamics & Tribology
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine
Related Grants:
Panel History:  
Summary on Grant Application Form
The main objectives of the project are to develop quantitative models for strength and fatigue life in Ni-base superalloys. Such models are intended for use in alloy design, to replace the initial stages of the current process, which involve making up and testing numerous different alloy compositions. Two approaches to strength modelling will be taken, a fundamental one based on firm physical principles, i.e. theory of strengthening mechanisms, and an essentially blind one, based on the use of artificial neural networks. The physical model will then be used to check that the neural network is generating appropriate relationships between inputs such as chemical composition and microstructural parameters. For the fatigue modelling the focus will be on fatigue crack growth behaviour. Because our understanding of crack growth is less well developed than that of strength, the physical model will not be quantitatively predictive, but will be used for testing concepts and identification of the appropriate inputs for the neural network. Most of the data required for the modelling can be obtained from existing sources such as manufacturers' data sheets, PhD theses and the vast NI-base alloys literature, a limited experimental programme is required to fill gaps in the data and to test the models. If time allows other relevant properties such as stress rupture will be included in the neural network modelling. An important final objective will be to assemble the modelling tools in a friendly form for use in the alloy design process.
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Organisation Website: http://www.cam.ac.uk