go to top scroll for more

Projects


Projects: Projects for Investigator
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) 10%;
Not Energy Related 90%;
Research Types Basic and strategic applied research 100%
Science and Technology Fields PHYSICAL SCIENCES AND MATHEMATICS (Metallurgy and Materials) 100%
UKERC Cross Cutting Characterisation Not Cross-cutting 100%
Principal Investigator Dr J R Kermode
No email address given
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 No relevance to Underpinning Sectors
Region West Midlands
Programme NC : Engineering
 
Investigators Principal Investigator Dr J R Kermode , School of Engineering, University of Warwick (100.000%)
  Industrial Collaborator Project Contact , University of Oxford (0.000%)
Project Contact , University of Cambridge (0.000%)
Project Contact , National Physical Laboratory (NPL) (0.000%)
Project Contact , King's College London (0.000%)
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
Publications (none)
Final Report (none)
Added to Database 06/02/19