7th Asia-Pacific Conference on Plasma Physics, 12-17 Nov, 2023 at Port Messe Nagoya

Development of 2D spatial displacement estimation method for turbulencevelocimetry of gas puff imaging system on EAST
L.T. Li1,2, S.C. Liu2, *, N. Yan2, X.J.Liu2, X. Gao2, *, EAST Team1
Anhui University, Hefei, People’s Republic of China,
2
Institute of Plasma Physics, Chinese Academy of Sciencese-mail (speaker):letian.li@ipp.ac.cn

The edge turbulence could contribute to remarkablecross-field transport in magnetically confined plasmas,
such as blobs or filaments [1]. During the propagation ofblobs from the plasma edge to the scrape-off layer (SOL),a large amount of heat and particles across the last closed
flux surface (LCFS) can reach the divertor plates in ashort time and lead to heat deposition on the firstplasma-facing materials. Some fast transient events, likeedge-localized mode (ELM) can cause significant energy
loss in the core plasma and high heat flux at the divertor
target, which is a crucial issue for large fusion devices
such as ITER. In consequence, the fine dynamic
evolution of the edge turbulence is important forunderstanding edge cross-field transport and core plasma
confinement.
Two-dimensional imaging technology is applied to themeasurement of edge turbulence structure and its
propagation velocity. Several 2D diagnostics forturbulence structure have been developed, including
beam emission spectroscopy (BES) [2], Langmuir probe[3], electron cyclotron imaging (ECEI) [4], and gas puff
imaging (GPI) [5]. Since the turbulence flow velocity isan essential parameter for the understanding of
turbulence instability and radial transport, various
methods are used in velocity estimation, such as thetime-delay method (TDE) [6], optical flow [7], spatial
displacement estimation (SDE) [8].
The SDE method calculates the spatial displacementfrom the spatial lag of the 2D spatial cross-correlation
coefficient function. Since the SDE could be operated for
two adjacent images, it has much higher temporal
resolution than the TDE method, which is an advantage

for the velocity estimation of fast structures. Due to theSDE method needing enough large image pixels, its
spatial resolution is limited. Based on the SDE algorithm,
we make some improvements, including an adaptive
median filter and super-resolution technology. After thedevelopment of the algorithm, a straight-line movement
and a curved-line movement are used to test the accuracyof the algorithm, and the calculated speed agrees wellwith preset speed. This SDE algorithm is applied to theEAST GPI data analysis, and the derived propagation
velocity of turbulence is consistent with that from theTDE method, but with much higher temporal resolution.
We tested the accuracy of SDE algorithm through twosections of motion, as shown in Figure 1, and thenapplied the algorithm to GPI diagnosis on EAST.
References[1] Piras F. et al 2010 Physical Review Letters 105155003[2] Harbour P. J. 1984 Nuclear Fusion 24 1211
[3] Chodura R. 1992 Contrib Plasm Phys 32 219[4] Tobias B. et al 2010 Review of Scientific Instruments
81 10d928[5] Liu S. C. et al 2012 Review of Scientific Instruments
83 123506[6] Shao L. M. et al 2013 Plasma Physics and ControlledFusion 55 105006[7] Horn B. K. P. et al 1981 Artificial Intelligence 17 185[8] Lampert M. et al 2021 Rev Sci Instrum 92 083508

Figure 1. In the subgraph Movement evolution, (a) A linear motion; (b) A curvilinear motion. In the subgraph
Algorithm test, The structure velocity for the straight and curvilinear motions calculated by the SDE method. The
turbulence propagation velocities calculated by the TDE method for discharge 103882 (right). (a) Radial velocity, withpositive value directed outside; (b) Poloidal velocity.