Bowman, Christopher, Harrison, James Robert, Lipschultz, Bruce orcid.org/0000-0001-5968-3684 et al. (5 more authors) (Accepted: 2020) Development and simulation of multi-diagnostic Bayesian analysis for 2D inference of divertor plasma characteristics. Plasma Physics and Controlled Fusion. ISSN 1361-6587 (In Press)
Abstract
We present results of the design, implementation and testing of a Bayesian multi-diagnostic inference system which combines various divertor diagnostics to infer the 2D fields of electron temperature T e, density n e and deuterium neutral density n 0 in the divertor. The system was tested using synthetic diagnostic measurements derived from SOLPS-ITER fluid code predictions of the MAST-U Super-X divertor which include appropriate added noise. Two SOLPS-ITER simulations in different states of detachment, taken from a scan of the nitrogen seeding rate, were used as test-cases. Taken across both test-cases, the median absolute fractional errors in the inferred electron temperature and density estimates were 10.3% and 10.1% respectively. Differences between the inferred fields and the test-cases were well explained by solution uncertainty estimates derived from posterior sampling. This work represents a step toward a larger goal of obtaining a quantitative, 2D description of the divertor plasma state directly from experimental data, which could be used to gain better understanding of divertor physics phenomena.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Physics (York) |
Funding Information: | Funder Grant number EPSRC EP/N023846/1 |
Depositing User: | Pure (York) |
Date Deposited: | 25 Feb 2020 16:00 |
Last Modified: | 17 Oct 2024 08:43 |
Published Version: | https://doi.org/10.1088/1361-6587/ab759b |
Status: | In Press |
Refereed: | Yes |
Identification Number: | 10.1088/1361-6587/ab759b |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157685 |