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Title: Sensitivity of the Boundary Plasma to the Plasma-Material Interface

While the sensitivity of the scrape-off layer and divertor plasma to the highly uncertain cross-field transport assumptions is widely recognized, the plasma is also sensitive to the details of the plasma-material interface (PMI) models used as part of comprehensive predictive simulations. Here in this paper, these PMI sensitivities are studied by varying the relevant sub-models within the SOLPS plasma transport code. Two aspects are explored: the sheath model used as a boundary condition in SOLPS, and fast particle reflection rates for ions impinging on a material surface. Both of these have been the study of recent high-fidelity simulation efforts aimed at improving the understanding and prediction of these phenomena. It is found that in both cases quantitative changes to the plasma solution result from modification of the PMI model, with a larger impact in the case of the reflection coefficient variation. Finally, this indicates the necessity to better quantify the uncertainties within the PMI models themselves, and perform thorough sensitivity analysis to propagate these throughout the boundary model; this is especially important for validation against experiment, where the error in the simulation is a critical and less-studied piece of the code-experiment comparison.
Authors:
 [1] ;  [2]
  1. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Grant/Contract Number:
AC05-00OR22725; AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Fusion Science and Technology
Additional Journal Information:
Journal Volume: 71; Journal Issue: 1; Journal ID: ISSN 1536-1055
Publisher:
American Nuclear Society
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY; Scrape-off layer; divertor; sheath
OSTI Identifier:
1341530

Canik, John M., and Tang, X. -Z.. Sensitivity of the Boundary Plasma to the Plasma-Material Interface. United States: N. p., Web. doi:10.13182/FST16-124.
Canik, John M., & Tang, X. -Z.. Sensitivity of the Boundary Plasma to the Plasma-Material Interface. United States. doi:10.13182/FST16-124.
Canik, John M., and Tang, X. -Z.. 2017. "Sensitivity of the Boundary Plasma to the Plasma-Material Interface". United States. doi:10.13182/FST16-124. https://www.osti.gov/servlets/purl/1341530.
@article{osti_1341530,
title = {Sensitivity of the Boundary Plasma to the Plasma-Material Interface},
author = {Canik, John M. and Tang, X. -Z.},
abstractNote = {While the sensitivity of the scrape-off layer and divertor plasma to the highly uncertain cross-field transport assumptions is widely recognized, the plasma is also sensitive to the details of the plasma-material interface (PMI) models used as part of comprehensive predictive simulations. Here in this paper, these PMI sensitivities are studied by varying the relevant sub-models within the SOLPS plasma transport code. Two aspects are explored: the sheath model used as a boundary condition in SOLPS, and fast particle reflection rates for ions impinging on a material surface. Both of these have been the study of recent high-fidelity simulation efforts aimed at improving the understanding and prediction of these phenomena. It is found that in both cases quantitative changes to the plasma solution result from modification of the PMI model, with a larger impact in the case of the reflection coefficient variation. Finally, this indicates the necessity to better quantify the uncertainties within the PMI models themselves, and perform thorough sensitivity analysis to propagate these throughout the boundary model; this is especially important for validation against experiment, where the error in the simulation is a critical and less-studied piece of the code-experiment comparison.},
doi = {10.13182/FST16-124},
journal = {Fusion Science and Technology},
number = 1,
volume = 71,
place = {United States},
year = {2017},
month = {1}
}