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Predictive Modelling of the Fundamentals of Failure in Metals

Reference Number
EP/P002188/1
Title
Predictive Modelling of the Fundamentals of Failure in Metals
Status
Completed
Energy Categories
Nuclear Fission and Fusion(Nuclear Fission, Nuclear supporting technologies)
Not Energy Related
Research Types
Basic and strategic applied research
Science and Technology Fields
PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials)
UKERC Cross Cutting Characterisation
Not Cross-cutting
Principal Investigator
Dr J R Kermode
School of Engineering
University of Warwick
Award Type
Standard
Funding Source
EPSRC
Start Date
01 August 2016
End Date
31 July 2018
Duration
24 months
Total Grant Value
£100,729
Industrial Sectors
Mechanical engineering
Region
West Midlands
Programme
NC : Engineering
Investigators
Principal Investigator
Dr J R Kermode, School of Engineering, University of Warwick
Industrial Collaborator
Project Contact, National Physical Laboratory (NPL)
Project Contact, King's College London
Project Contact, Argyll College
Project Contact, Bury College
Project Contact, University of Oxford
Project Contact, Chichester College Group
Project Contact, University of Cambridge
Web Site
Objectives
Abstract
Our lack of detailed understanding of the atomic scale mechanisms which lead to failure of metals through processes such as cracking, creep, embrittlement or fatigue is surprising, given the significant technological and economic impact that such understanding could generate. Examples of what could be achieved include designing stronger, lighter turbine blades for aeroplane engines, improved lightweight alloys for the automobile industry or improved radiation shields for the nuclear industry.Progress to date has been limited partly because the current generation of continuum models for metal failure rely heavily on empirical methods. The overarching aim of this proposal is to develop new models to enable continuum-scale modelling of failure processes, in particular crack growth, by incorporating pre-computed first-principles information. Adding reliable probabilistic "error bars'' which incorporate the effects of model error, limited data, epistemic uncertainty and coarse-graining would help to address one of the major barriers holding back wider adoption of materials modelling in industry (cf. Innovate UK/KTN special interest group on Uncertainty Quantification and Management for High Value Manufacturing).Realising these long-term aims first requires developing (i) accurate atomic scale models for `slow' failure processes in metals and (ii) a rigorous model reduction procedure to capture information lost during coarse graining, allowing complex microstructures to be modelled. This project addresses (i) in detail by developing new methodology to compute energy barriers with QM accuracy in systems large enough to capture stress concentration, with application to dislocation motion and crack growth in technologically relevant but still structurally simple single crystal model systems (nickel, aluminium and tungsten). Requirement (ii) will be explored via a case study to be further developed in future proposals. The project is aligned with research areas in which the UK is a world leader: condensed matter (electronic structure), materials engineering (metals and alloys) and numerical analysis
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Added to Database
06/02/19