Inertial Confinement Fusion - exploring the options for ignition.
Lead Research Organisation:
University of Oxford
Department Name: Oxford Physics
Abstract
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People |
ORCID iD |
| Steven Rose (Principal Investigator) |
Publications
Hatfield P
(2020)
Augmenting machine learning photometric redshifts with Gaussian mixture models
in Monthly Notices of the Royal Astronomical Society
Hatfield P
(2020)
Using Sparse Gaussian Processes for Predicting Robust Inertial Confinement Fusion Implosion Yields
in IEEE Transactions on Plasma Science
Hatfield P
(2019)
The blind implosion-maker: Automated inertial confinement fusion experiment design
in Physics of Plasmas
P.W.Hatfield
(2021)
The data-driven future of high energy density physics
in Nature
Rose S
(2020)
Modelling burning thermonuclear plasma
in Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
| Description | Inertial confinement fusion (ICF) is one possible pathway to nuclear fusion becoming a viable energy source, with the premier ICF facility being the National Ignition Facility (NIF) in California. Progress towards high-yield experiments on NIF is hindered (among other things) by the fact that space of all possible different designs that can be tested is of very high dimension. We have have developed two novel methods of using computer algorithms to explore this space and create new designs for use at NIF, some of which might hopefully contribute to developing ICF as a viable source of energy production. |
| Exploitation Route | The algorithms being developed have general application for designing a range of other high energy density experiments e.g. optimising laboratory astrophysics experiments for maximum statistical significance etc. The uncertainty quantification methods developed have already been used by multiple other researchers and in national labs etc. |
| Sectors | Energy,Environment |
| Description | Collaboration with industry (First Light Fusion) have helped them use machine learning in their work |
| First Year Of Impact | 2019 |
| Sector | Energy |
| Impact Types | Economic |
| Description | Development and exploitation of the GPz algorithm |
| Amount | £46,974 (GBP) |
| Funding ID | DBD00050 |
| Organisation | University of Oxford |
| Sector | Academic/University |
| Country | United Kingdom |
| Start | 04/2019 |
| End | 03/2021 |
| Description | Extreme Physics, Extreme Data - Lorentz Center Meeting |
| Amount | € 20,000 (EUR) |
| Organisation | Netherlands Organisation for Scientific Research (NWO) |
| Sector | Public |
| Country | Netherlands |
| Start | 01/2020 |
| End | 01/2020 |
| Description | Extreme Physics, Extreme Data support from the Fell Fund |
| Amount | £5,000 (GBP) |
| Funding ID | 0007750 |
| Organisation | Oxford University Press |
| Sector | Private |
| Country | United Kingdom |
| Start | 01/2020 |
| End | 05/2020 |
| Title | Database of ICF Implosions |
| Description | Database of 10'000s of Hyades ICF simulations |
| Type Of Material | Database/Collection of data |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | Creation of a database of simulated ICF implosions that researchers can use to test machine learning methods on |
| Description | Collaboration with Imperial Centre for Inertial Fusion Studies |
| Organisation | Imperial College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Development of algorithmic approach to ICF design development; 1D Hyades simulations |
| Collaborator Contribution | Understanding of hydrodynamic instabilities; 3D Chimera simulations |
| Impact | Ongoing work developing novel ICF designs |
| Start Year | 2017 |
| Description | Collaboration with Lawrence Livermore National Laboratory |
| Organisation | Lawrence Livermore National Laboratory |
| Country | United States |
| Sector | Public |
| PI Contribution | Contribution of various algorithms and data developed in Oxford |
| Collaborator Contribution | Visits to LLNL, share some of their algorithms |
| Impact | Presented at the first LLNL Data Science Workshop (only person from outside of the University of California and the US National Lab system) |
| Start Year | 2018 |
| Description | Collaboration with RAL Central Laser Facility |
| Organisation | Rutherford Appleton Laboratory |
| Department | Central Laser Facility |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Development of algorithmic approaches to ICF design |
| Collaborator Contribution | Expertise in modelling high-energy density experiments on laser facilities; host and manage the proprietary software used in research |
| Impact | Ongoing work developing new ICF designs |
| Start Year | 2017 |
| Title | Machine Learning for ICF Design |
| Description | Developed code for researchers to use machine learning to design inertial confinement fusion experiments |
| Type Of Technology | Software |
| Year Produced | 2020 |
| Impact | Now used by two PhD students to design their experiments |
| Description | Royal Society Summer Exhibition - How to make a Supernova |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Schools |
| Results and Impact | Week long exhibition at the Royal Society Summer Exhibition in which I and many others showed a range of physics activities to school groups and the public, based around high powered lasers |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://royalsociety.org/science-events-and-lectures/2017/summer-science-exhibition/exhibits/how-to-... |
| Description | School Research Project |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | ~10 students from a local network of secondary schools have worked with the research group on a project over the last ~two years They received the real data from the experiment, and have visited Imperial College, received visits in their school, and have written up their results |
| Year(s) Of Engagement Activity | 2018,2019,2020 |
| Description | Stargazing Live Oxford |
| Form Of Engagement Activity | Participation in an open day or visit at my research institution |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | Open day in the Oxford Physics department themed around space, where I talked to people about laboratory astrophysics experiments Around 1100 people visits the department, and I talked to 200-300 of them |
| Year(s) Of Engagement Activity | 2020 |
| URL | https://www2.physics.ox.ac.uk/events/2020/01/25/stargazing-oxford-2020 |
| Description | Talk at AWE |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Industry/Business |
| Results and Impact | Gave a talk about machine learning methods in HEDP |
| Year(s) Of Engagement Activity | 2018 |