automatic analysis of edge pedestal gradient degradation during elms
DESCRIPTION
Automatic Analysis of Edge Pedestal Gradient Degradation during ELMs. S. González, J. Vega, A. Murari, A. Pereira and JET-EFDA contributors 7 th Workshop on Fusion Data Processing, Validation and Analysis, March 2012. Introduction (I). H-mode features [1]: Improved particle confinement - PowerPoint PPT PresentationTRANSCRIPT
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S. González 1 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Automatic Analysis of Automatic Analysis of Edge Pedestal Edge Pedestal Gradient Degradation Gradient Degradation during ELMsduring ELMs
S. González, J. Vega, A. Murari, A. Pereira and JET-EFDA contributorsS. González, J. Vega, A. Murari, A. Pereira and JET-EFDA contributors
77thth Workshop on Fusion Data Processing, Validation and Analysis, March 2012 Workshop on Fusion Data Processing, Validation and Analysis, March 2012
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S. González 2 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Introduction (I)
• H-mode features [1]:– Improved particle
confinement
– Existence of an External Transport Barrier (ETB)
– Existence of Edge Localised Modes (ELMs)
[1] F. Wagner et al., Regime of improved confinement and high beta in neutral-beam-heated divertor discharges of the ASDEX tokamak, Physical Review Letters 49 (19), pages 1408-1412, 1982
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S. González 3 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Introduction (II)
• ELMs [2]:– Instabilities at the plasma
edge
– H-mode plasmas
– At each burst:• The ETB is reduced
• The plasma confinement degrades
• Quantify the edge pedestal gradient degradation during ELMs
[2] H. Zohm, Edge localized modes (ELMs), Plasma Physics and Controlled Fusion 38, pages 105-128, 1996
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S. González 4 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Edge Pedestal Gradient (I): ELMs location
• ELMs location [3]:– UMEL [4]
• Dα peaks
• Diamagnetic energy drops
– Automatic
[3] S. González, J. Vega, A. Murari, A. Pereira, M. Beurskens and JET-EDA contributors, Automatic ELM location in JET using a Universal Multi-Event Locator, Fusion Science and Technology 58 (3), pages 755-762, 2010
[4] J. Vega, A. Murari, S. González and JET-EFDA contributors, A universal supprt vector machines based method for automatic event location in waveforms and video-movies: applications to massive nuclear fusion databases , Review of Scientific Instruments 81, 023505, 2010
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S. González 5 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Edge Pedestal Gradient (II): ET, SGT and SGB
• At each instant, two signals are considered:– Electron Temperature (ET)
profile– Steep Gradient
Temperature (SGT): difference of temperature between two consecutive radial points of ET
• Steep Gradient Baseline (SGB): mean value of the SGT between the plasma core and the ETB
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S. González 6 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Edge Pedestal Gradient (III): ET, SGT and SGB
• JET pulse 78072: L & H temperature profiles comparison
a) b)
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S. González 7 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Edge Pedestal Gradient (IV): ELMs analysis
• For each ELM burst:– SGT is compared at two
different times:• At the ELM time (ELM)
• 2 ms before (ELM-0.002)
– SGT is measure at the ETB• At the ELM time (SGTETB
ELM )
• 2 ms before ( SGTETBELM-0.002)
SGTETB
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S. González 8 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Edge pedestal gradient (V): degradation
ELM-0.002 ELM
ELMETB
ELM-0.002
SGT
SGBELMcoef
ELM-0.0020.002 ETB
ELM-0.002
SGT
SGBELMcoef
0.002
0.002 0.002
1degradation = 1
1 1ELM ELMELM
ELM ELM
coef coefcoef
coef coef
ELM-0.002 ELMETB ETB
ELM-0.002 ELM-0.002ETB
SGT -SGTdegradation =
SGT -SGB
SGTETBELM-0.002
SGTETBELM
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S. González 9 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Edge Pedestal Gradient (VI): example
ELM-0.002 ELM
ELMETB
ELM-0.002
SGT 107.4161.822
SGB 58.940ELMcoef
ELM-0.0020.002 ETB
ELM-0.002
SGT 341.6915.797
SGB 58.940ELMcoef
0.002
0.002 0.002
1 5.797 1.822degradation = 1 0.8286 82.86%
1 1 5.797 1ELM ELMELM
ELM ELM
coef coefcoef
coef coef
ELM-0.002 ELMETB ETB
ELM-0.002 ELM-0.002ETB
SGT -SGT 341.691 107.416degradation = 0.8286 82.86%
SGT -SGB 341.691 58.940
SGTETBELM-0.002
SGTETBELM
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S. González 10 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Results (I)
• Edge Pedestal Gradient degradation results:– # pulses analysed: 409
– # ELMs analysed: 22486
– Edge pedestal gradient degradation mean value: 33.98%
– # ELMs, degradation higher than 80%: 924, 4.11%
– # ELMs, degradation higher than 90%: 291 1.29%
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S. González 11 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Edge Pedestal Gradient (VII): evolution
• Edge Pedestal Gradient 2ms after the ELM
• Pulse 789072, time = 8.9951 s
Mean degradation:
17.34 %
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S. González 12 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Results (II)
Degradation between ELM time -0.002 and ELM time
Mean Value: 33.98%
Degradation between ELM time -0.002 and ELM time+0.002
Mean Value: 17.34%(degradation = 0 not shown, 6380 ELMs)
• Distribution of the edge pedestal gradient degradation of analysed ELMs
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S. González 13 (14) 7th Workshop on Fusion Data Processing, Validation and Analysis, Frascati, Roma, Italy
Questions
• Thank you very much for your attention
• Questions?