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

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

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

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

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

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)

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

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

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

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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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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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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Questions

• Thank you very much for your attention

• Questions?