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Physics Analysis and Flexibility Issues for FIRE

This article discusses recent physics activities and analysis for the FIRE project, including burning plasma workshop, MHD and plasma transport studies, disruption studies, and future directions. It also explores the role of m=1 mode and neoclassical tearing mode in plasma performance.

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Physics Analysis and Flexibility Issues for FIRE

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  1. Physics Analysis and Flexibility Issues for FIRE S. C. Jardin with input from C.Kessel, J.Mandrekas, D.Meade, and the FIRE team NSO PAC-2 Meeting January 17-18, 2001

  2. Recent FIRE Physics Activities Since the last PAC meeting: • UFA Burning Plasma Workshop • MHD and Energetic Particle studies • Transport Studies • TSC perturbation studies and scenario development • SCIDAC Proposal Development • MHD in a burning plasma • Nonlinear GK turbulent transport simulations • Development of AT Modes for FIRE • Disruption Studies for Engineering Analysis

  3. Outline • Lower beta operating modes with Q=10 • Perturbation Studies • Long Pulse AT modes • Future Directions Kessel • More on AT Modes • Disruptions Studies

  4. Guidelines for Predicting Plasma Performance Confinement (Elmy H-mode) ITER98(y,2): E = 0.144 I0.93 R1.39 a0.58 n200.41 B0.15 Ai0.19 0.78 P heat-0.69 H(y,2) Density Limit: n20 < 0.75 nGW = 0.75 IP/a2 H-Mode Power Threshold: Pth > (2.84/Ai) n200.58 B0.82 R a0.81

  5. High Field: H ~ 1.0 (12 T, 7.7 MA) Low Field: H ~ 1.2 (10 T, 6.5 MA) total total a-heating a-heating ICRF ICRF Time (sec) Time (sec) N < 2 N < 2.8 Q > 10 for 9 sec Q > 10 for 18 sec

  6. TSC Simulation of Low N high Q operating point at BT = 12T, IP=7.7MA, H~1 Note: Q ~ 12-20 Max PAUX 15MW N ~ 1.5 N time

  7. Example of Perturbation Study that can be done on FIRE: ICRF heating power increased by 5 or 10MW for 6 sec BT=10T, IP = 6.4 MA, H(y,2) = 1.2 Shows that fusion power amplifies ICRF power over a wide range of input powers

  8. Identification of AT Targets for FIRE • Long pulse AT modes are targeted to operate at reduced field (8.5T) for about 40 sec ( > 3 Skin Times) • We can project backwards from Standard Operating Modes to get requirements on N and H(y,2) for AT modes: Stored Energy: W ~ B2 ~ NIB Energy Confiment time: E ~ H(y,2) IP.93 n.41 BT.15 ~ H(y,2) IP1.34 BT.15

  9. Q=5, BT=10,IP=6.44, H=1, N=2.1 base case W ~ B2 ~ NIB q95 The operating points on this graph will have the same stored energy for the N values shown on the contours. No wall n=1 stab AT rule* need 2.8 3.45 2.8 3.2 3.5 3.5 3.7 3.2 2.5 3.6 2.3 2.9 3.1 3.1 3.4 2.7 *AT rule: lower of 4i and 1.15 N

  10. Q=5, BT=10,IP=6.44, H=1, N=2.1 base case E ~ H(y,2) IP.93 n.41 BT.15 ~ H(y,2)IP1.34 BT.15 The operating points on this graph will have the same energy confinement times for the H(y,2) values shown on the contours. AT modes need H factor in range 1.2 – 1.6 for same confinement time in sec.

  11. Physics Question: Role of the m=1 mode • 3D Extended MHD simulation taking part as part of the SCIDAC initiative will study the m=1 mode in a burning plasma • Proper physics description must take into account: • energetic particle drive, • kinetic stabilization, • 2-fluid effects, and • non-linear saturation mechanism • This is one of the major thrusts of the 3D macroscopic simulations communities..similar to turbulent transport simulations in transport community • FIRE will provide critical data point for code benchmarking and hence for extrapolations

  12. Physics question: NTM • neoclassical tearing mode sets  limits in many long-pulse discharges • scaling of this to new devices largely result of empirical fitting of quasi-linear formula • this is another major thrust of 3D macroscopic modeling effort • active feedback looks feasible • FIRE will provide critical data point (From LaHaye, Butter, Guenter, Huysmans, Marashek, and Wilson)

  13. Summary • FIRE should have considerable flexibility to demonstrate high Q operation at a range of N values down to ~1.5 at 12T • Families of AT modes can be generated with same W and E as baseline operating modes • What science will we learn (MHD area)? • How does core self-organize with ’s and m=1 mode? • How does edge self-organize with bootstrap and ELMs • How does interior self-organize with NTM, at new (*,*) • How well can our codes predict these nonlinear events ?

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