Reducing Risk through Uncertainty Quantification for Past, Present and Future Generations of Nuclear Power Plant
Lead Research Organisation:
University of Warwick
Department Name: Sch of Engineering
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
People |
ORCID iD |
James Kermode (Principal Investigator) |
Publications
Goryaeva A
(2021)
Efficient and transferable machine learning potentials for the simulation of crystal defects in bcc Fe and W
in Physical Review Materials
Darby J
(2022)
Compressing local atomic neighbourhood descriptors
in npj Computational Materials
Anand G
(2022)
Exploiting Machine Learning in Multiscale Modelling of Materials
in Journal of The Institution of Engineers (India): Series D
Podgurschi V
(2022)
Atomistic modelling of iodine-oxygen interactions in strained sub-oxides of zirconium
in Journal of Nuclear Materials
Klawohn S
(2023)
Massively parallel fitting of Gaussian approximation potentials
in Machine Learning: Science and Technology
Ghiringhelli LM
(2023)
Shared metadata for data-centric materials science.
in Scientific data
Klawohn S
(2023)
Gaussian approximation potentials: Theory, software implementation and application examples
in The Journal of Chemical Physics
Witt WC
(2023)
ACEpotentials.jl: A Julia implementation of the atomic cluster expansion.
in The Journal of chemical physics
Grigorev P
(2023)
Calculation of dislocation binding to helium-vacancy defects in tungsten using hybrid ab initio-machine learning methods
in Acta Materialia
Grigorev P
(2024)
matscipy: materials science at the atomic scale with Python
in Journal of Open Source Software
Description | The project developed and applied quantum mechanically accurate simulations of defects in metals and ceramics to make predictions about how these materials fail. Our findings also allowed the uncertainty associated with our predictions to be quantified to allow an assessment of their validity. Please see also the Key Findings description provided for EP/R012423/1. |
Exploitation Route | Our findings could be incorporated in larger scale models such as finite element method simulations of fracture, crystal plasticity and discrete dislocation dynamics. They can also be directly compared with experiments. They are relevant to inform the use of materials in fracture-relevant applications such as the Nuclear and Oil and Gas industries. |
Sectors | Aerospace, Defence and Marine,Education,Energy |
Description | A PDRA associated with the project has moved to a new research position elsewhere in Europe, consolidating an international collaboration and improving cultural links. |
First Year Of Impact | 2021 |
Sector | Aerospace, Defence and Marine,Education |
Impact Types | Cultural,Societal,Economic |
Description | EPSRC Centre for Doctoral Training in Modelling of Heterogeneous Systems |
Amount | £5,752,474 (GBP) |
Funding ID | EP/S022848/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2019 |
End | 09/2027 |
Description | EPSRC standard grant |
Amount | £442,958 (GBP) |
Funding ID | EP/R043612/1 |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 10/2018 |
End | 03/2022 |
Description | European Database for Multiscale Modelling of Radiation Damage (ENTENTE) |
Amount | € 4,000,000 (EUR) |
Funding ID | 900018 |
Organisation | European Commission |
Sector | Public |
Country | European Union (EU) |
Start | 09/2020 |
End | 08/2024 |
Description | Support for advanced transition state search techniques in CASTEP |
Amount | £29,000 (GBP) |
Funding ID | 2nd ARCHER2 eCSE call |
Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2021 |
End | 08/2021 |