Gyrokinetic GENE simulations of DIII-D near-edge L-mode plasmas
Gyrokinetic GENE simulations of DIII-D near-edge L-mode plasmas
复制标题
DIII-D 近边缘 L 模式等离子体的回旋 GENE 模拟
DOI:
10.1063/1.5052047
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发表时间:
2018
影响因子:
2.2
通讯作者:
Z. Yan
中科院分区:
文献类型:
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作者:
T. Neiser;F. Jenko;T. Carter;L. Schmitz;D. Told;G. Merlo;A. Navarro;P. Crandall;G. McKee;Z. Yan
We present gyrokinetic simulations with the GENE code addressing the near-edge region of an L-mode plasma in the DIII-D tokamak. At radial position $\rho=0.80$, simulations with the ion temperature gradient increased by $40\%$ above the nominal value give electron and ion heat fluxes that are in simultaneous agreement with the experiment. This gradient increase is consistent with the combined statistical and systematic uncertainty $\sigma$ of the Charge Exchange Recombination Spectroscopy (CER) measurements at the $1.6 \sigma$ level. Multi-scale simulations are carried out with realistic mass ratio and geometry for the first time in the near-edge. These multi-scale simulations suggest that the highly unstable ion temperature gradient (ITG) modes of the flux-matched ion-scale simulations suppress electron-scale transport, such that ion-scale simulations are sufficient at this location. At radial position $\rho=0.90$, nonlinear simulations show a hybrid state of ITG and trapped electron modes~(TEMs), which was not expected from linear simulations. The nonlinear simulations reproduce the total experimental heat flux with the inclusion of $\mathbf{E} \times \mathbf{B}$ shear effects and an increase in the electron temperature gradient by $\sim 23\%$. This gradient increase is compatible with the combined statistical and systematic uncertainty of the Thomson scattering data at the $1.3 \sigma$ level. These results are consistent with previous findings that gyrokinetic simulations are able to reproduce the experimental heat fluxes by varying input parameters close to their experimental uncertainties, pushing the validation frontier closer to the edge region.
影响因子:
1.7
作者:
D. Batchelor;Micah Beck;A. Becoulet;R. Budny;Choong-Seock Chang;P. Diamond;J. Dong;G. Fu;A. Fukuyama;T. Hahm;D. Keyes;Y. Kishimoto;S. Klasky;L. Lao;K. Li;Zhihong Lin;Bertram Ludäscher;J. Manickam;N. Nakajima;T. Ozeki;N. Podhorszki;W. Tang;M. Vouk;R. Waltz;Shaojie Wang;H. Wilson;X. Xu;M. Yagi;F. Zonca
通讯作者:
D. Batchelor;Micah Beck;A. Becoulet;R. Budny;Choong-Seock Chang;P. Diamond;J. Dong;G. Fu;A. Fukuyama;T. Hahm;D. Keyes;Y. Kishimoto;S. Klasky;L. Lao;K. Li;Zhihong Lin;Bertram Ludäscher;J. Manickam;N. Nakajima;T. Ozeki;N. Podhorszki;W. Tang;M. Vouk;R. Waltz;Shaojie Wang;H. Wilson;X. Xu;M. Yagi;F. Zonca
影响因子:
2.2
作者:
C. Holland;L. Schmitz;T. Rhodes;W. Peebles;J. Hillesheim;Gang Wang;L. Zeng;E. Doyle;Sterling P. Smith;R. Prater;K. Burrell;J. Candy;R. Waltz;J. Kinsey;G. Staebler;J. Deboo;C. Petty;G. McKee;Zheng Yan;A. White
通讯作者:
C. Holland;L. Schmitz;T. Rhodes;W. Peebles;J. Hillesheim;Gang Wang;L. Zeng;E. Doyle;Sterling P. Smith;R. Prater;K. Burrell;J. Candy;R. Waltz;J. Kinsey;G. Staebler;J. Deboo;C. Petty;G. McKee;Zheng Yan;A. White
DOI:
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发表时间:
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影响因子:
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