Effect of pressure gradient in the connection region on the stability of the edge pedestal

Kim, SangKyeun; Saarelma, S.; Na, Yong-Su; Kwon, Oh-Jin

doi:10.1088/1741-4326/ab826c

Cited by 6 publications

(3 citation statements)

References 58 publications

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“…As pointed out in [5], plasmas with a higher percentage of impurities may require smaller pedestal densities in order to maintain the pedestal electron collisionality sufficiently small. Notice that the increase of pedestal collisionality is likely to yield a reduction of the bootstrap current, and a consequent increase of the local magnetic shear [32][33][34][35]. Hence, the collisionality threshold may be associated with a critical value of the magnetic shear below which EHOs can develop [36], in accordance with recent analytic and numerical modelling [18,[37][38][39][40].…”

Section: Pedestal Density and Temperature Conditions For The Q-eho Ph...supporting

confidence: 64%

Understanding JET-C quiescent phases with edge harmonic magnetohydrodynamic activity and comparison with behaviour under ITER-like wall conditioning

Brunetti

Ham

Graves

et al. 2022

Plasma Phys. Control. Fusion

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The analysis of ELM-free (quiescent) H-mode discharges exhibiting edge harmonic magnetoydro- dynamic activity in the JET-carbon wall machine is presented. It is observed that the otherwise quiescent pulses with multiple-n harmonic oscillations are sustained until a threshold in pedestal electron density and collisionality is crossed. The macroscopic pedestal parameters associated with the quiescent phase are compared with those of a database of JET-ELMy discharges with both car- bon and ITER-like wall (ILW). This comparison provides the identification of the existence regions in the relevant pedestal and global plasma parameters for edge harmonic oscillations (EHOs) in JET plasmas. Although the ELMy database scans pedestal collisionality and β values typical of JET-carbon quiescent operation, shaping and current are not simultaneuously compatible with EHO existence. Nevertheless, ILW operation with JET-carbon quiescent-like parameters could in prin- ciple be achieved, and improved pedestal performance could be observed in more recent JET-ILW pulses.

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Section: Pedestal Density and Temperature Conditions For The Q-eho Ph...supporting

confidence: 64%

Understanding JET-C quiescent phases with edge harmonic magnetohydrodynamic activity and comparison with behaviour under ITER-like wall conditioning

Brunetti

Ham

Graves

et al. 2022

Plasma Phys. Control. Fusion

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show abstract

“…When using this technique to color match two different domains, the gradient of the images is more important than the intensity. As such, Poisson blending was used to replace the gradients of the target image with the gradients of the source image, while maintaining the overall intensity to the target image 22 . To ensure a seamless transition between the patch and its surroundings, we used an additional gradient filter that preserves the central information of the new Poisson blended patch and the edges of the original patch.…”

Section: Methodsmentioning

confidence: 99%

Near-pair patch generative adversarial network for data augmentation of focal pathology object detection models

Tu,

Burkow,

Tsai

et al. 2024

J. Med. Imag.

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The limited volume of medical training data remains one of the leading challenges for machine learning for diagnostic applications. Object detectors that identify and localize pathologies require training with a large volume of labeled images, which are often expensive and time-consuming to curate. To reduce this challenge, we present a method to support distant supervision of object detectors through generation of synthetic pathology-present labeled images.Approach: Our method employs the previously proposed cyclic generative adversarial network (cycleGAN) with two key innovations: (1) use of "near-pair" pathologypresent regions and pathology-absent regions from similar locations in the same subject for training and (2) the addition of a realism metric (Fréchet inception distance) to the generator loss term. We trained and tested this method with 2800 fracture-present and 2800 fracture-absent image patches from 704 unique pediatric chest radiographs. The trained model was then used to generate synthetic pathology-present images with exact knowledge of location (labels) of the pathology. These synthetic images provided an augmented training set for an object detector.Results: In an observer study, four pediatric radiologists used a five-point Likert scale indicating the likelihood of a real fracture (1 = definitely not a fracture and 5 = definitely a fracture) to grade a set of real fracture-absent, real fracture-present, and synthetic fracture-present images. The real fracture-absent images scored 1.7 AE 1.0, real fracture-present images 4.1 AE 1.2, and synthetic fracture-present images 2.5 AE 1.2. An object detector model (YOLOv5) trained on a mix of 500 real and 500 synthetic radiographs performed with a recall of 0.57 AE 0.05 and an F 2 score of 0.59 AE 0.05. In comparison, when trained on only 500 real radiographs, the recall and F 2 score were 0.49 AE 0.06 and 0.53 AE 0.06, respectively. Conclusions: Our proposed method generates visually realistic pathology and that provided improved object detector performance for the task of rib fracture detection.

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“…The EPED model will naturally provide a pedestal near the PB stability boundary. However, a study in reference [26] suggests the connection region between the pedestal and the core could affect the stability of the PB mode. To check if the PB stability boundary changes, the VARYPED and ELITE code are used to identify the PB stability boundary [27,28].…”

Section: Simulation Setupmentioning

confidence: 99%

Edge-localized-mode simulation in CFETR steady-state scenario

Tang

Li³

2021

Nucl. Fusion

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The EPED1 model and self-consistent core-pedestal coupling in integrated modeling are used to design the pedestal structure of the China Fusion Engineering Testing Reactor (CFETR) steady-state scenario. The key parameters, such as β p and q 95, are based on the grassy edge-localized-mode (ELM) experimental database. In this work, we use the BOUT++ six-field two-fluid code to simulate the onset of the ELM in the CFETR steady-state scenario. The ELM size is around 0.2% in nonlinear simulations, which is in the experimental range of the grassy ELM discharges, 0.1%–1% observed in multiple tokamak devices. Linear and nonlinear simulations show that the dominant high-n ballooning modes peak around n = 40. Compared to type-I ELM crashing dynamics, grassy ELM crashing has a smaller initial crash and is then followed by three phases of turbulence spreading, which are dominated by multi-modes, a high-n mode of n = 45 and low-n mode of n = 5, respectively. In contras to type-I ELM, the perturbation of the high-n mode has a narrow width around ψ = 0.95, and magnetic island formation and reconnection occur only beyond ψ = 0.95, leading to a small initial crash. Mode–mode interaction in the multi-mode coexistence stage stops the growth of individual modes and reduces the transport of particles and heat, and these are the two reasons why the ELM size is small. In–out asymmetry of transient heat flux with a ratio of E out/E in = 3.5 is found during grassy ELM crash. The rise and delay times of the heat flux match the calculation from the free-streaming model. To evaluate the erosion of the divertor target, the energy fluence at the outer divertor target is calculated, which is 0.029 MJ m−2, 5.5 times smaller than the tungsten melting limit 0.16 MJ m−2. The calculated energy fluency still follows the experimental scaling law from type-I ELM experiments. The fluctuation eddies in the toroidal direction show a filament structure at the outer mid-plane. Parallel heat flux patterns with a toroidal mode number n = 10 are found at the outer divertor with an amplitude of 680 MW m−2.

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Effect of pressure gradient in the connection region on the stability of the edge pedestal

Cited by 6 publications

References 58 publications

Understanding JET-C quiescent phases with edge harmonic magnetohydrodynamic activity and comparison with behaviour under ITER-like wall conditioning

Understanding JET-C quiescent phases with edge harmonic magnetohydrodynamic activity and comparison with behaviour under ITER-like wall conditioning

Near-pair patch generative adversarial network for data augmentation of focal pathology object detection models

Edge-localized-mode simulation in CFETR steady-state scenario

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