Velocity Detection of Plasma Patterns from 2D BES Data Young-chul Ghim(Kim) 1,2, Anthony Field 2, Sandor Zoletnik 3 1 Rudolf Peierls Centre for Theoretical.

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Velocity Detection of Plasma Patterns from 2D BES Data Young-chul Ghim(Kim) 1,2, Anthony Field 2, Sandor Zoletnik 3 1 Rudolf Peierls Centre for Theoretical Physics, University of Oxford 2 EURATOM/CCFE Fusion Association, Culham, U.K. 3 KFKI RMKI, Association EURATOM/HAS 2, March, 2011

Prepared by Young-chul Ghim(Kim) Quantity BES measures is Density Fluctuation. 2 /

Prepared by Young-chul Ghim(Kim) Contents 3 / 1.Brief description of zonal flows, sZFs, and GAMs 2.Density fluctuation from DIII-D data using CUDA 3.Meaning of measured velocity from 2D BES data 1.Detectable range of velocity a)How the study is performed. b)Mean flow c)Temporally fluctuation flow (i.e. GAMs) 2.Velocity measurements from DIII-D Data 3.Conclusion

Prepared by Young-chul Ghim(Kim) ZFs are not divergence free in a tokamak. 4 / A Flux Surface (q=2 surface) ϕ (toroidal) θ (poloidal) 0 (out-board) π (in-board) 2π (out-board) 0π2π B-field Zonal Flow: V ZF (θ)

Prepared by Young-chul Ghim(Kim) So, consequences are generating sZF and/or GAMs. 5 / A Flux Surface (q=2 surface) ϕ (toroidal) θ (poloidal) 0 (out-board) π (in-board) 2π (out-board) 0π2π B-field Zonal Flow: V ZF (θ) sZF and/or GAMs

Prepared by Young-chul Ghim(Kim) Structure of GAMs: (m, n) = (0, 0) and (1, 0) 6 / Both modes have the same temporal behavior: Winsor et al. Phys. Fluids 11, 2448 (1968) Spatial structure of GAMs

Prepared by Young-chul Ghim(Kim) Density response to GAMs 7 / Due to m = 0 mode of GAM: Due to m = 1 mode of GAM: Temporal behavior of density fluctuation:

Prepared by Young-chul Ghim(Kim) Detecting ñ GAM using 2D BES 8 / BES cannot detect m=1 mode of ñ GAM because observation position is mid-plane. How about m= 0 mode of ñ GAM ? Krämer-Flecken et al. Phy. Rev. Lett. 97, (2006)

Prepared by Young-chul Ghim(Kim) BES can detect GAMs from motions of ñ. 9 / To the perpendicular direction on a given flux surface: These induce oscillating perpendicular motion of ñ. To the radial direction: These induce oscillating radial motion of ñ. But, their magnitudes may be small.

Prepared by Young-chul Ghim(Kim) Conclusion I 10 / As physicists, we want to know how zonal flows are generated. how they suppress turbulence. First, we need to confirm existence of zonal flows. Try to observe ñ associated with zonal flows.In general, not easy. Try to observe ñ associated with GAMs.Hard with BES at the midplane Try to observe GAM induced motions of ñPossible with BES

Prepared by Young-chul Ghim(Kim) Contents 11 / 1.Brief description of zonal flows, sZFs, and GAMs 2.Density fluctuation from DIII-D data using CUDA 3.Meaning of measured velocity from 2D BES data 1.Detectable range of velocity a)How the study is performed. b)Mean flow c)Temporally fluctuation flow (i.e. GAMs) 2.Velocity measurements from DIII-D Data 3.Conclusion

Prepared by Young-chul Ghim(Kim) Statistical analyses are performed on a GPU. 12 /

Prepared by Young-chul Ghim(Kim) DIII-D BES Data 13 / I have two sets of data which each consists of 7 poloidally separated channesl with 11 mm separation for about little bit more than ~ 2 seconds worth with 1MHz sampling frequency

Prepared by Young-chul Ghim(Kim) Data Set #1: Density spectrogram (Ch.1) 14 / Some MHD modes? IAW modes?

Prepared by Young-chul Ghim(Kim) 15 / Data Set #1: Density spectrogram (Ch.1 and 7)

Prepared by Young-chul Ghim(Kim) Contents 16 / 1.Brief description of zonal flows, sZFs, and GAMs 2.Density fluctuation from DIII-D data using CUDA 3.Meaning of measured velocity from 2D BES data 1.Detectable range of velocity a)How the study is performed. b)Mean flow c)Temporally fluctuation flow (i.e. GAMs) 2.Velocity measurements from DIII-D Data 3.Conclusion

Prepared by Young-chul Ghim(Kim) 17 / Mean flows in a tokamak is mostly toroidal. ϕ (toroidal) θ (poloidal) B-field line v || v  (~v ExB ) v plasma v plasma = v || + v 

Prepared by Young-chul Ghim(Kim) 18 / Mean flows in a tokamak is mostly toroidal. ϕ (toroidal) θ (poloidal) B-field line v || v  (~v ExB ) v plasma v plasma = v || + v  = v ϕ + v θ vϕvϕ vθvθ

Prepared by Young-chul Ghim(Kim) 19 / Poloidal motion: mostly ‘barber pole’ effect.

Prepared by Young-chul Ghim(Kim) 20 / Poloidal velocity from barber shop effect is close to ExB drift velocity. ϕ (toroidal) θ (poloidal) B-field line v || vv v plasma v plasma = v || + v  = v ϕ + v θ vϕvϕ vθvθ v detected α α

Prepared by Young-chul Ghim(Kim) In addition, we have GAM induced velocity. 21 / ϕ (toroidal) θ (poloidal) B-field line v || vv v plasma vϕvϕ vθvθ v detected α α v GAM v GAM cos(α)

Prepared by Young-chul Ghim(Kim) 22 / Conclusion III We have to be careful when we say ‘poloidal motion’ of a plasma in a tokamak measured by BES. Poloidal motion of plasma  small (on the order of diamagnetic flow) Poloidal motion of patterns  can be on the order of ExB flow (due to ‘barber pole’ effect)

Prepared by Young-chul Ghim(Kim) Contents 23 / 1.Brief description of zonal flows, sZFs, and GAMs 2.Density fluctuation from DIII-D data using CUDA 3.Meaning of measured velocity from 2D BES data 1.Detectable range of velocity a)How the study is performed. b)Mean flow c)Temporally fluctuation flow (i.e. GAMs) 2.Velocity measurements from DIII-D Data 3.Conclusion

Prepared by Young-chul Ghim(Kim) 24 / Eddies generated by using GPU (CUDA programming) Equation to generate ‘eddies’ Assumed that eddies have Gaussian shapes in R, z, and t-directions plus wave structure in z-direction. R Z t v z (R,t)

Prepared by Young-chul Ghim(Kim) v z (R,t) is set to have sheared and GAM induced flows. 25 /

Prepared by Young-chul Ghim(Kim) 26 / Synthetic BES data are generated by using PSFs and generated eddies.

Prepared by Young-chul Ghim(Kim) v z (t) is estimated using the CCTD method. 27 /

Prepared by Young-chul Ghim(Kim) 28 / Data Set #1: Mean v z (t) of plasma patterns

Prepared by Young-chul Ghim(Kim) 29 / Back-of-envelope calculation of detectable range of mean velocity using CCTD method Upper LimitLower Limit Using adjacent Channel 40 km/s1.3 km/s Using Farthest apart channels 120 km/s4.0 km/s Numerical Results~ 80 km/s~ 5 km/s Sampling Frequency: 2 MHz  0.5 usec Adjacent channel distance: 2.0 cm Farthest apart channel distance: 6.0cm Life time of an eddy: 15 usec (This plays a role in lower limit. i.e. before an eddy dies away, it needs to be seen by the next channel.)

Prepared by Young-chul Ghim(Kim) Numerical results of detecting mean velocities. 30 / Upper limit Lower limit

Prepared by Young-chul Ghim(Kim) 31 / Numerical results of detecting fluctuating velocities.

Prepared by Young-chul Ghim(Kim) 32 / Numerical results of detecting fluctuating velocities.

Prepared by Young-chul Ghim(Kim) Conclusion IV 33 / We saw upper and lower limits of detectable mean flow velocity using BES with CCTD technique. o Upper Limit is set by 1)Sampling frequency 2)Distance from a channel to next one o Lower Limit is set by 1)Life time of a structure 2)Distance from a channel to next one We saw that o The worse the NSR, the harder to detect GAMs o the faster the mean flow, the harder to detect GAMs

Prepared by Young-chul Ghim(Kim) Contents 34 / 1.Brief description of zonal flows, sZFs, and GAMs 2.Density fluctuation from DIII-D data using CUDA 3.Meaning of measured velocity from 2D BES data 1.Detectable range of velocity a)How the study is performed. b)Mean flow c)Temporally fluctuation flow (i.e. GAMs) 2.Velocity measurements from DIII-D Data 3.Conclusion

Prepared by Young-chul Ghim(Kim) 35 / Data Set #1: Mean v z (t) of plasma patterns

Prepared by Young-chul Ghim(Kim) 36 / Data Set #1: Fluct. v z (t) of plasma patterns Density is filtered 50.0 kHz < f < kHz before v z (t) is calculated.

Prepared by Young-chul Ghim(Kim) 37 / Data Set #1: Fluct. v z (t) of plasma patterns Density is filtered 0.0 kHz < f < 30.0 kHz before v z (t) is calculated.

Prepared by Young-chul Ghim(Kim) Conclusion V 38 / As we just saw, detecting GAM features are not straight forward. o It may be helpful to consider radial motions as well since we have radial motions of eddies due to 1)Polarization drift 2)Finite poloidal wave-number associated with m=1 mode of GAM  However, we do not know whether these radial motions are big enough to be seen by the 2D BES.

Prepared by Young-chul Ghim(Kim) Final Conclusions 39 / 1.Discussed about ZFs, sZFs, and GAMS. Because of the observation positions of 2D BES, we use GAMs to “confirm” the existence of zonal flows. 2.Discussed the meaning of poloidal velocities seen by the 2D BES. BES sees poloidal motions of ‘plasma patterns’ rather than bulk plasmas. 3.Discussed detectable ranges of poloidal motions using the CCTD method. Mean v z : sampling freq., ch. separation dist., lifetime of eddies. Fluct. v z : NSR levels, v GAM /v mean. 4.DIII-D data showed that we have to be careful for detecting GAM-like features.

Velocity Detection of Plasma Patterns from 2D BES Data Young-chul Ghim(Kim) 1,2, Anthony Field 2, Sandor Zoletnik 3 1 Rudolf Peierls Centre for Theoretical Physics, University of Oxford 2 Culham Centre for Fusion Energy, Culham, U.K. 3 KFKI RMKI, Association EURATOM/HAS 28, February, 2011

Prepared by Young-chul Ghim(Kim) Data Set #2: Density spectrogram (Ch.1) 41 /

Prepared by Young-chul Ghim(Kim) Data Set #2: Density spectrogram (Ch.1) 42 / Some MHD modes? IAW modes? Probably LH transition

Prepared by Young-chul Ghim(Kim) 43 / Data Set #2: Density spectrogram (Ch.1 and 7)

Prepared by Young-chul Ghim(Kim) 44 / Data Set #2: Mean v z (t) of plasma patterns

Prepared by Young-chul Ghim(Kim) 45 / Data Set #2: Fluct. v z (t) of plasma patterns Density is filtered 50.0 kHz < f < kHz before v z (t) is calculated.

Prepared by Young-chul Ghim(Kim) 46 / Data Set #2: Fluct. v z (t) of plasma patterns Density is filtered 0.0 kHz < f < 30.0 kHz before v z (t) is calculated.