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Recent Progress in Modeling of CFETR Plasma Profiles from Core to Edge

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Abstract

Simulation studies of core plasmas and edge plasmas are performed in ASIPP to accommodate plasma profiles from core to edge based on physics modeling for the CFETR physics design. The coupling between the modeling for core plasmas and edge plasmas are described. The recent progress of the integrated core-pedestal simulations for core plasmas and the SOLPS simulations for plasmas in pedestal-SOL-divertor region are presented, respectively. In the optimization study for core plasma performance, moderate Z eff (~ 2.2) at pedestal top and a high ratio of density at separatrix to density at pedestal (n sep /n ped ~ 0.5) are found to be beneficial for the achievement of a high fusion gain in CFETR hybrid scenarios. The edge plasma simulations using the SOLPS code show that using either neon or argon impurity seeding can reduce the stationary power density on the divertor target to an acceptable level (< 10 MW/m2) but Z eff at pedestal top is still high (Z eff ~ 3). Future works to improve the consistence between the simulations of core and edge plasmas are discussed.

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References

  1. J. Candy et al., Phys. Plasmas 16(6), 060704 (2009)

    MathSciNet  ADS  Google Scholar 

  2. J. Citrin et al., Plasma Phys. Controlled Fusion 59(12), 124005 (2017)

    ADS  Google Scholar 

  3. A.R. Polevoi et al., Nucl. Fusion 55(6), 063019 (2015)

    ADS  Google Scholar 

  4. A.R. Polevoi et al., Nucl. Fusion 57(2), 022014 (2017)

    ADS  Google Scholar 

  5. A.R. Polevoi et al., Nucl. Fusion 58(5), 056020 (2018)

    ADS  Google Scholar 

  6. A.Y. Dnestrovskiy et al., Nucl. Fusion 59(9), 096053 (2019)

    ADS  Google Scholar 

  7. L. Garzotti et al., Nucl. Fusion 59(2), 026006 (2019)

    ADS  Google Scholar 

  8. B. Wan et al., IEEE Trans. Plasma Sci. 42(3), 495–502 (2014)

    ADS  Google Scholar 

  9. Y.T. Song et al., IEEE Trans. Plasma Sci. 42(3), 503–509 (2014)

    ADS  Google Scholar 

  10. V.S. Chan et al., Nucl. Fusion 55(2), 023017 (2015)

    ADS  Google Scholar 

  11. Y. Wan et al., Nucl. Fusion 57(10), 102009 (2017)

    ADS  Google Scholar 

  12. G. Zhuang et al., Nucl. Fusion 59(11), 112010 (2019)

    ADS  Google Scholar 

  13. J.E. Kinsey et al., Nucl. Fusion 43(12), 1845–1854 (2003)

    ADS  Google Scholar 

  14. X. Litaudon et al., Nucl. Fusion 53(7), 073024 (2013)

    ADS  Google Scholar 

  15. G.Z. Jia et al., Phys. Plasmas 27(6), 062509 (2020)

    ADS  Google Scholar 

  16. O. Meneghini et al., Phys. Plasmas 23(4), 042507 (2016)

    ADS  Google Scholar 

  17. O. Meneghini et al., Nucl. Fusion 55(8), 083008 (2015)

    ADS  Google Scholar 

  18. G.M. Staebler et al., Phys. Plasmas 12(10), 102508 (2005)

    ADS  Google Scholar 

  19. G.M. Staebler et al., Phys. Plasmas 14(5), 055909 (2007)

    ADS  Google Scholar 

  20. E.A. Belli, J. Candy, Plasma Phys. Controlled Fusion 50(9), 095010 (2008)

    ADS  Google Scholar 

  21. E. Belli, J. Candy, Plasma Phys. Controlled Fusion 51(7), 075018 (2009)

    ADS  Google Scholar 

  22. G.M. Staebler, Nucl. Fusion 58(11), 115001 (2018)

    ADS  Google Scholar 

  23. W.A. Houlberg et al., Nucl. Fusion 45(11), 1309–1320 (2005)

    ADS  Google Scholar 

  24. C.E. Kessel et al., Nucl. Fusion 47(9), 1274–1284 (2007)

    ADS  Google Scholar 

  25. R. Budny et al., Nucl. Fusion 48(7), 075005 (2008)

    ADS  Google Scholar 

  26. A.H. Kritz et al., Nucl. Fusion 51(12), 123009 (2011)

    ADS  Google Scholar 

  27. M. Murakami et al., Nucl. Fusion 51(10), 103006 (2011)

    ADS  Google Scholar 

  28. A. Pankin et al., Comput. Phys. Commun. 159(3), 157–184 (2004)

    ADS  Google Scholar 

  29. Y.R. Lin-Liu et al., Phys. Plasmas 10(10), 4064–4071 (2003)

    ADS  Google Scholar 

  30. Smirnov A. and Harvey R. 2001 CompX Report CompX-2000–01.

  31. Pfeiffer W.W. et al. ONETWO: a computer code for modeling plasa transport in tokamaks. ; General Atomic Co., San Diego, CA (USA); 1980. Report No.: GA-A-16178; TRN: 81–006489 United States TRN: 81–006489 NTIS, PC A10/MF A01. GA English.

  32. P.B. Snyder et al., Phys. Plasmas 16(5), 056118 (2009)

    ADS  Google Scholar 

  33. P.B. Snyder et al., Nucl. Fusion 51(10), 103016 (2011)

    ADS  Google Scholar 

  34. J. Chen et al., Nuclear Fusion (accepted) (2021). https://doi.org/10.1088/741-4326/abd7b8

    Article  Google Scholar 

  35. M. Wakatani et al., Nucl. Fusion 39(12), 2175–2249 (1999)

    Google Scholar 

  36. B. Li et al., Fusion Eng. Des. 148, 111295 (2019)

    Google Scholar 

  37. C.X. Zhou et al., Nucl. Fusion 60(9), 096029 (2020)

    ADS  Google Scholar 

  38. M. Greenwald, Plasma Phys. Controlled Fusion 44(8), R27–R80 (2002)

    ADS  Google Scholar 

  39. Chen J. et al. 2019 23rd TOPICAL CONFERENCE ON RADIOFREQUENCY POWER IN PLASMAS. p. I3.4.

  40. J. Huang et al., Plasma Phys. Controlled Fusion 62(1), 014019 (2020)

    ADS  Google Scholar 

  41. J. Huang et al., Nucl. Fusion 60(12), 126007 (2020)

    ADS  Google Scholar 

  42. R.A. Pitts et al., Nuclear Materials and Energy 20, 100696 (2019)

    Google Scholar 

  43. X.J. Liu et al., Phys. Plasmas 27(9), 092508 (2020)

    ADS  Google Scholar 

  44. Bonnin X. et al 2016 Plasma and Fusion Research. 11 1403102

  45. I.Y. Senichenkov et al., Plasma Phys. Controlled Fusion 61(4), 045013 (2019)

    ADS  Google Scholar 

  46. E. Sytova et al., Nuclear Materials and Energy 19, 72–78 (2019)

    Google Scholar 

  47. E. Kaveeva et al., Nucl. Fusion 60(4), 046019 (2020)

    ADS  Google Scholar 

  48. P.C. Stangeby, Plasma Phys. Controlled Fusion 43(2), 223 (2000)

    Google Scholar 

Download references

Acknowledgement

This work is supported by the National Magnetic Confinement Fusion Program of China under Contracts No. 2017YFE0300500 and No. 2017YFE0300501. The authors acknowledge fruitful cooperation in the CFETR physics team and especially Prof. Vincent. S. Chan for his introduction of schemes to simulate a whole plasma in tokamaks. We appreciate the theory and computational sciences group in General Atomic for their valuable supports in the use of the GA code suites. Numerical computations were performed on the ShenMa High Performance Computing Cluster in Institute of Plasma Physics, Chinese Academy of Sciences.

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Correspondence to Guozhang Jia.

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Chen, J., Jia, G. & Xiang, N. Recent Progress in Modeling of CFETR Plasma Profiles from Core to Edge. J Fusion Energ 40, 1 (2021). https://doi.org/10.1007/s10894-021-00292-7

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