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Edge shear flow and its effect on regulating turbulent transport have long been suspected to play an important role in plasmas operating near the Greenwald density limit n G . In this study, equilibrium profiles as well as the turbulent particle flux and Reynolds stress across the separatrix in the HL-2A tokamak are examined as n G is approached in ohmic L-mode discharges. As the normalized line-averaged densityn e /n G is raised, the shearing rate of the mean poloidal flow ω sh drops, and the turbulent drive for the low-frequency zonal flow (the Reynolds power P Re ) collapses. Correspondingly, the turbulent particle transport increases drastically with increasing collision rates. The geodesic acoustic modes (GAMs) gain more energy from the ambient turbulence at higher densities, but have smaller shearing rate than low-frequency zonal flows. The increased density also introduces decreased adiabaticity which not only enhances the particle transport but is also related to reduction in the eddy-tilting and the Reynolds power. Both effects may lead to cooling of edge plasmas and therefore the onset of MHD instabilities that limit the plasma density.1

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The oscillations of poloidal plasma flows induced by radially sheared zonal flows are investigated by newly developed correlation Doppler reflectometers in the HL-2A tokamak. The non-disturbing diagnostic allows one to routinely measure the rotation velocity of turbulence, and hence the radial electric field fluctuations. With correlation Doppler reflectometers, a three-dimensional spatial structure of geodesic acoustic mode (GAM) is surveyed, including the symmetric feature of poloidal and toroidal E r fluctuations, the dependence of GAM frequency on radial temperature and the radial propagation of GAMs. The co-existence of low-frequency zonal flow and GAM is presented. The temporal behaviors of GAM during ramp-up experiments of plasma current and electron density are studied, which reveal the underlying damping mechanisms for the GAM oscillation level.

Maize tassels play a critical role in plant growth and yield. Extensive RGB images obtained using unmanned aerial vehicle (UAV) and the prevalence of deep learning provide a chance to improve the accuracy of detecting maize tassels. We used images from UAV, a mobile phone, and the Maize Tassel Counting dataset (MTC) to test the performance of faster region-based convolutional neural network (Faster R-CNN) with residual neural network (ResNet) and a visual geometry group neural network (VGGNet). The results showed that the ResNet, as the feature extraction network, was better than the VGGNet for detecting maize tassels from UAV images with 600 × 600 resolution. The prediction accuracy ranged from 87.94% to 94.99%. However, the prediction accuracy was less than 87.27% from the UAV images with 5280 × 2970 resolution. We modified the anchor size to [852, 1282, 2562] in the region proposal network according to the width and height of pixel distribution to improve detection accuracy up to 89.96%. The accuracy reached up to 95.95% for mobile phone images. Then, we compared our trained model with TasselNet without training their datasets. The average difference of tassel number was 1.4 between the calculations with 40 images for the two methods. In the future, we could further improve the performance of the models by enlarging datasets and calculating other tassel traits such as the length, width, diameter, perimeter, and the branch number of the maize tassels.

ITER and to the advanced tokamak operation (e.g. the operation of future HL-2M), such as the access of H-mode, energetic particle physics, edge-localized mode (ELM) mitigation/suppression and disruption mitigation. Since the 2016 Fusion Energy Conference, the HL-2A team has focused on the investigations on the following areas: (i) pedestal dynamics and L-H transition, (ii) techniques of ELM control, (iii) the turbulence and transport, (iv) energetic particle physics. The HL-2A results demonstrated that the increase of mean E × B shear flow plays a key role in triggering L-I and I-H transitions. While the change of E × B flow is mainly induced by the ion pressure gradient. Both mitigation and suppression of ELMs were realized by laser blow-off (LBO) seeded impurity (Al, F e, W). The 30% N e mixture supersonic molecular beam injection (SMBI) seeding also robustly induced ELM mitigation. The ELMs were mitigated by low-hybrid current drive (LHCD). The stabilization of m/n=1/1 ion fishbone activities by electron cyclotron resonance heating (ECRH) was found on the HL-2A. A new m/n=2/1 ion fishbone activity was observed recently, and the modelling indicated that passing fast ions dominantly contribute to the driving of 2/1 fishbone. The non-linear coupling between toroidal Alfven eigenmode (TAE) and tearing mode (TM) leads to the generation of a high frequency mode with the toroidal mode number n=0. The turbulence is modulated by tearing mode when the island width exceeds a threshold and the modulation is localized merely in the inner area of the islands. Meanwhile, turbulence radially spreading takes place across the island region.

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