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Parametric study of hydrogenic inventory in the ITER divertor based on machine learning
A parametric study is performed with the 2D FESTIM code for the ITER monoblock geometry. The influence of the monoblock surface temperature, the incident ion energy and particle flux on the monoblock hydrogen inventory is investigated. The simulated data is analysed with a Gaussian regression proces...
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| Udgivet i: | Sci Rep |
|---|---|
| Main Authors: | , , , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Nature Publishing Group UK
2020
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7576168/ https://ncbi.nlm.nih.gov/pubmed/33082471 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-74844-w |
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