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Title: On benchmarking of simulations of particle transport in ITER

Abstract

We present results of benchmarking of core particle transport simulations by a collection of codes widely used in transport modelling of tokamak plasmas. Our analysis includes formulation of transport equations, difference between electron and ion solvers, comparison of modules of the pellet and edge gas fuelling on the ITER baseline scenario. During the first phase of benchmarking we address the particle transport effects in the stationary phase. Firstly, simulations are performed with identical sources, sinks, transport coefficients, and boundary conditions prescribed in the flattop H-mode phase. The transformation of ion particle transport equations is introduced so to directly compare their results to electron transport solvers. Moreover, the pellet fuelling models are benchmarked in various conditions to evaluate the dependency of the pellet deposition on the pellet volume, injection side, pedestal and separatrix parameters. Thirdly, edge gas fuelling is benchmarked to assess sensitivities of source profile predictions to uncertainties in plasma conditions and detailed model assumptions. At the second phase, we address particle transport effects in the time-evolving plasma including the current ramp-up to the ramp-down phase. The ion and the electron solvers are benchmarked together. Differences between the simulation results of the solvers are investigated in terms of equilibrium, gridmore » resolution, radial coordinate, radial grid distribution, and plasma volume evolution term. We found that the selection of the radial coordinate can yield prominent differences between the solvers mainly due to differences in the edge grid distribution. The simulations reveal that electron and ion solvers predict noticeably different density peaking for the same diffusion and pinch velocity while with the peaked profile of helium, expected in fusion reactors. The fuelling benchmarking demonstrates that gas puffing is not efficient for core fuelling in H-modes and density control should be done by the high field side pellet injection in contrast to present machines.« less

Authors:
 [1]; ORCiD logo [2];  [3];  [1];  [1];  [1]; ORCiD logo [4]; ORCiD logo [5]; ORCiD logo [6];  [7]; ORCiD logo [8];  [9];  [9]; ORCiD logo [10];  [11];  [2];  [12]; ORCiD logo [13];  [2]; ORCiD logo [14] more »;  [8] « less
  1. Seoul National Univ. (Korea, Republic of)
  2. Culham Centre for Fusion Energy (CCFE), Abingdon (United Kingdom)
  3. ITER Organization, St. Paul Lez Durance (France)
  4. Ecole Polytechnique Federale Lausanne (Switzlerland)
  5. Kyoto Univ. (Japan)
  6. French Alternatives Energies and Atomic Energy Commission (CEA), St Paul Lez Durance (France). Institut de Recherche sur la Fusion par confinement Magnétique (IRFM)
  7. Japan Atomic Energy Agency (JAEA), Ibaraki (Japan). Advanced Plasma Modeling Group
  8. Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
  9. General Atomics, San Diego, CA (United States)
  10. Princeton Univ., NJ (United States)
  11. Ecole Polytechnique Federale Lausanne (Switzlerland). Centre de Recherche en Physique des Plasma (CRPP)
  12. Chalmers Univ. of Technology, Goteborg (Sweden)
  13. Ecole Polytechnique Federale Lausanne (Switzlerland). Swiss Plasma Center
  14. King Mongkut's Univ. of Technology Thonburi, Bangkok (Thailand)
Publication Date:
Research Org.:
Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Fusion Energy Sciences (FES) (SC-24)
OSTI Identifier:
1508251
Grant/Contract Number:  
633053; AC02-09CH11466; EP/P012450/1
Resource Type:
Accepted Manuscript
Journal Name:
Nuclear Fusion
Additional Journal Information:
Journal Name: Nuclear Fusion; Journal ID: ISSN 0029-5515
Publisher:
IOP Science
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Citation Formats

Na, Yong-Su, Koechl, Florian, Polevoi, Alexei R., Byun, Cheol-Sik, Na, DongHyeon, Seo, Jaemin, Felici, Federico, Fukuyama, Atsushi, Garcia, Jeronimo, Hayashi, Nobuhiko, Kessel, Charles E., Luce, Timothy C., Park, Jin Myung, Poli, Francesca M., Sauter, Olivier, Sips, George, Strand, Pär, Teplukhina, Anna, Voitsekhovitch, Irina, Wisitsorasak, Apiwat, and Yuan, Xingqiu. On benchmarking of simulations of particle transport in ITER. United States: N. p., 2019. Web. doi:10.1088/1741-4326/ab15e0.
Na, Yong-Su, Koechl, Florian, Polevoi, Alexei R., Byun, Cheol-Sik, Na, DongHyeon, Seo, Jaemin, Felici, Federico, Fukuyama, Atsushi, Garcia, Jeronimo, Hayashi, Nobuhiko, Kessel, Charles E., Luce, Timothy C., Park, Jin Myung, Poli, Francesca M., Sauter, Olivier, Sips, George, Strand, Pär, Teplukhina, Anna, Voitsekhovitch, Irina, Wisitsorasak, Apiwat, & Yuan, Xingqiu. On benchmarking of simulations of particle transport in ITER. United States. doi:10.1088/1741-4326/ab15e0.
Na, Yong-Su, Koechl, Florian, Polevoi, Alexei R., Byun, Cheol-Sik, Na, DongHyeon, Seo, Jaemin, Felici, Federico, Fukuyama, Atsushi, Garcia, Jeronimo, Hayashi, Nobuhiko, Kessel, Charles E., Luce, Timothy C., Park, Jin Myung, Poli, Francesca M., Sauter, Olivier, Sips, George, Strand, Pär, Teplukhina, Anna, Voitsekhovitch, Irina, Wisitsorasak, Apiwat, and Yuan, Xingqiu. Thu . "On benchmarking of simulations of particle transport in ITER". United States. doi:10.1088/1741-4326/ab15e0.
@article{osti_1508251,
title = {On benchmarking of simulations of particle transport in ITER},
author = {Na, Yong-Su and Koechl, Florian and Polevoi, Alexei R. and Byun, Cheol-Sik and Na, DongHyeon and Seo, Jaemin and Felici, Federico and Fukuyama, Atsushi and Garcia, Jeronimo and Hayashi, Nobuhiko and Kessel, Charles E. and Luce, Timothy C. and Park, Jin Myung and Poli, Francesca M. and Sauter, Olivier and Sips, George and Strand, Pär and Teplukhina, Anna and Voitsekhovitch, Irina and Wisitsorasak, Apiwat and Yuan, Xingqiu},
abstractNote = {We present results of benchmarking of core particle transport simulations by a collection of codes widely used in transport modelling of tokamak plasmas. Our analysis includes formulation of transport equations, difference between electron and ion solvers, comparison of modules of the pellet and edge gas fuelling on the ITER baseline scenario. During the first phase of benchmarking we address the particle transport effects in the stationary phase. Firstly, simulations are performed with identical sources, sinks, transport coefficients, and boundary conditions prescribed in the flattop H-mode phase. The transformation of ion particle transport equations is introduced so to directly compare their results to electron transport solvers. Moreover, the pellet fuelling models are benchmarked in various conditions to evaluate the dependency of the pellet deposition on the pellet volume, injection side, pedestal and separatrix parameters. Thirdly, edge gas fuelling is benchmarked to assess sensitivities of source profile predictions to uncertainties in plasma conditions and detailed model assumptions. At the second phase, we address particle transport effects in the time-evolving plasma including the current ramp-up to the ramp-down phase. The ion and the electron solvers are benchmarked together. Differences between the simulation results of the solvers are investigated in terms of equilibrium, grid resolution, radial coordinate, radial grid distribution, and plasma volume evolution term. We found that the selection of the radial coordinate can yield prominent differences between the solvers mainly due to differences in the edge grid distribution. The simulations reveal that electron and ion solvers predict noticeably different density peaking for the same diffusion and pinch velocity while with the peaked profile of helium, expected in fusion reactors. The fuelling benchmarking demonstrates that gas puffing is not efficient for core fuelling in H-modes and density control should be done by the high field side pellet injection in contrast to present machines.},
doi = {10.1088/1741-4326/ab15e0},
journal = {Nuclear Fusion},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {4}
}

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