Edge Region Research Articles

Accuracy of kinetic equilibrium reconstruction of NSTX and NSTX-U plasmas and its impact on the transport and stability analysis

Abstract An accurate magnetohydrodynamic (MHD) equilibrium reconstruction is an essential starting point for stability and transport plasma analysis. This work describes an approach for obtaining kinetic equilibrium reconstructions using the OMFIT framework, which has been applied for the first time to spherical tokamak data from NSTX and NSTX-U. The EFIT equilibrium solver is integrated with experimental data analysis procedures and subsequent TRANSP transport simulations to enhance the accuracy of the reconstruction, in particular at the edge region, by adding constraints on the total pressure and current density profiles, based on the transport code solution. The accuracy of the equilibrium depends on the uncertainty and number of constraints, as well as the choice of basis functions to represent the pressure and current density profiles. An improved fidelity of the equilibrium reconstruction is demonstrated by reducing the variability of the magnetic axis and boundary locations from several centimeters for reconstructions based on magnetic and experimental pressure constraints to only several millimeters for kinetic reconstructions based on transport code constraints, when different representations for basis functions were tested. Variability of the safety factor on-axis was reduced ten times in the same sensitivity study. The accuracy of the equilibrium reconstruction and subsequent mapping of experimental kinetic profile data have a significant impact on TGLF and linear CGYRO turbulence simulations, which predict different spectra of unstable modes and turbulent fluxes for cases with different numbers of constraints in the equilibrium reconstruction. Conversely, the stability analysis performed with the GATO code shows plasmas stable to n = 1 MHD modes in both equilibria using magnetic and experimental pressure constraints as well as the transport code constrained equilibrium. However, a scan of parameters away from these conditions shows considerable deviation in the threshold of unstable modes between these reconstructions. Therefore, for reliable plasma analysis and use in turbulence and stability calculations, a high fidelity equilibrium reconstruction with accurate kinetic constraints based on transport code solutions is necessary.

Simulation of tungsten impurity transport by DIVIMP under different divertor magnetic configurations on HL-3

Tungsten (W) accumulation in the core, depending on W generation and transport in the edge region, is a severe issue in fusion reactors. Compared to standard divertors (SDs), snowflake divertors (SFDs) can effectively suppress the heat flux, while the impact of magnetic configurations on W core accumulation remains unclear. In this study, the kinetic code DIVIMP combined with the SOLPS-ITER code is applied to investigate the effects of divertor magnetic configurations (SD versus SFD) on W accumulation during neon injection in HL-3. It is found that the W concentration in the core of the SFD is significantly higher than that of the SD with similar total W erosion flux. The reasons for this are: (1) W impurities in the core of the SFD mainly originate from the inner divertor, which has a short leg, and the source is close to the divertor entrance and upstream separatrix. Furthermore, the W ionization source (S W0) is much stronger, especially near the divertor entrance. (2) The region overlap of S W0 and pointing upstream promote W accumulation in the core. Moreover, the influence of W source locations at the inner target on W transport in the SFD is investigated. Tungsten impurity in the core is mainly contributed by target erosion in the common flux region (CFR) away from the strike point. This is attributed to the fact that the W source at this location enhances the ionization source above the W ion stagnation point, which sequentially increases W penetration. Therefore, the suppression of far SOL inner target erosion can effectively prevent W impurities from accumulating in the core.

Effects of NiO doping and trench wall tilt on Ga2O3 PiN diodes performance

Gallium Oxide (Ga2O3) is a promising material for next-generation power semiconductors due to its wide bandgap (∼4.9 eV), high Baliga's figure of merit (FOM) (3444 W/cmK), and high breakdown field (Ec, 8 MV/cm). To achieve high blocking and low leakage current, research has been conducted on PN heterojunctions and bevel structures. In this paper, we performed simulations using Sentaurus TCAD to investigate the impact of NiO doping concentration and NiO's trench tilt angle on the electrical characteristics of NiO/Ga2O3 PiN diodes with trench NiO. As the NiO doping concentration increased, the resistance decreased from 21.5 to 7.5 mΩcm2, and we observed the expansion of depletion from NiO to the NiO/Ga2O3 interface. Furthermore, we confirmed a reduction in resistance and a change in breakdown voltage with an increase in NiO trench tilt. By understanding the optimal angle to mitigate the concentration of high electric fields in the edge region, we anticipate the fabrication of stable Ga2O3 PiN diodes.

Adaptive Idle Model Fusion in Hierarchical Federated Learning for Unbalanced Edge Regions

Adaptive Idle Model Fusion in Hierarchical Federated Learning for Unbalanced Edge Regions

Phase transformation during solid-solution and aging treatment of a Mg-Gd-Y-Zn-Zr alloy containing LPSO and W phases

In this study, solid-solution and aging treatments were conducted on a hot-drawn Mg-9.5Gd-4Y–2Zn-0.3Zr alloy wire, which included long period stacking order (LPSO) phases and a Mg3Zn3RE2 (W phase) with a diameter of 4 mm. Subsequently, the phase transformations within the alloy were meticulously analyzed. Following solid solution treatment, the W-Mg3Zn3RE2 phase in the edge region almost completely dissolved, leaving behind blocky RE-rich phases. Conversely, the core region retained more of the original LPSO phase, resulting in significant microstructural differences between the core and the edge. The aging treatment induced a more pronounced hardening response in the core region, achieving a peak hardness of 136.33 HV at 96 h. By contrast, the edge regions exhibited a weaker aging response. Specifically, edge region 1 showed minimal fluctuations in hardness without significant hardening, while edge region 2 reached its peak hardness of 103.13 HV at 96 h. The differential hardening effects induced by aging treatment primarily stemmed from the formation and distribution of precipitate phases. Both the core region and edge regions initially precipitated β-Mg5Gd at the grain boundaries, with stacking faults (SFs) forming within the grains. However, dense and uniform precipitation of the β′-Mg7Gd phase also occurred within the core region. Therefore, controlling the precipitation of the W phase was crucial for tuning the mechanical properties of the Mg-9.5Gd-4Y–2Zn-0.3Zr alloy.

Inlet distortion of a rear engines concept aircraft and its effect on a fan

Boundary layer ingesting technology (BLI) has been widely developed, but the relevant research on the rear engine concept (REC) still needs to be expanded, especially for the different characteristics of the total pressure distortion and the swirl distortion. The paper investigates the BLI inlet distortion of a REC aircraft and its effect on the fan performance by commercial software CFX. Numerical simulation is conducted to obtain the inlet distortions first and the impact of these distortions on the characteristics of NASA rotor 67 is evaluated. Results show that the distortion tends to increase with the increase of the fluid redistribution effect of the fuselage-propulsor fusion part. Comparatively, the inlet distortion caused by AOS has a more significant influence on the performance of the fan. The swirl distortion is concentrated in the edge region of AIP. The total pressure distortion which coupled higher level of swirl has a more significant effect and is offset in the circumferential direction with the continuation effect of distortion in other leaf channels not obvious.

Segment-based Eulerian-Lagrangian transition method for flat nozzle spray atomization simulation

This paper presents a novel segment-based Eulerian-Lagrangian transition method for predicting the primary and secondary breakup behavior of a flat nozzle spray. It combines the Volume of Fluid (VOF) method for simulating liquid sheet disintegration and primary breakup with the Discrete Phase Model (DPM) method for secondary breakup. The VOF simulation predicts the varying thickness and local velocity characteristics of the liquid sheet from the center region to the edge region near the nozzle exit. Meanwhile, the proposed segment-based linear stability analysis in this study is capable of predicting the initial droplet variation resulting from primary breakup, considering the varying behavior of the liquid sheet from different regions. The simulation results match reasonably well with experimental data at both macroscopic and microscopic levels, effectively predicting the overall spray structure, mass flow rate, and droplet size variations across different regions with good accuracy. Both experimental and numerical data show that the Sauter mean diameter (SMD) values differ between the center and edge regions, with the edge region displaying larger droplets than the center region. This indicates that the segment-based approach is crucial for successfully predicting the spatial distributions of droplet size characteristics.

Poloidally asymmetric potential formation on plasma boundary in axisymmetric magnetic field

To study the symmetry of electrical potential, we model plasma transport in the edge region of a toroidal device with two spatial dimensions (2D) and three coordinates for velocities (3V) using a Particle-In-Cell (PIC) code. A two-dimensional magnetic field is applied, including poloidal and toroidal components, which are periodic in the poloidal direction. We discover relationships between the magnetic gradient drift and potential formation using PIC simulation, which has not been captured in other numerical models. We find that the inverse aspect ratio influences the asymmetry of the potential in an axisymmetric magnetic configuration.

Deconfinement of runaway electrons by local vertical magnetic field perturbation

Runaway electron (RE) deconfinement and subsequent suppression is of prime importance for successful long-term operation of any tokamak. In this work, to deconfine and mitigate REs, the efficacy of local vertical field (LVF) perturbation has been explored numerically. LVF perturbation-assisted RE loss studies are carried out by simulating the drift orbits of the REs in magnetostatic perturbed fields and estimating the resulting orbit losses for different initial energies and magnitudes of LVF perturbation. To this end, the pre-existing PARTICLE code has been extended to the relativistic full-orbit-following code PARTICLE-3D (P3D) integrated with the magnetic field calculation code EFFI and plasma equilibrium field calculation code IPREQ to include the required fields for studying particle dynamics in general; this is then used to numerically model LVF perturbation-assisted RE deconfinement experiments conducted in the ADITYA tokamak. Simulation results show a significant (∼90%) deconfinement of REs with the application of LVF perturbation of a suitable amplitude (∼0.1% of the total magnetic field) in a preferred direction. The existence of a threshold magnitude of the applied field is also established, which is observed to be dependent on the energy of the REs. The simulation results reproduce all the experimental observations and reveal other interesting features of RE mitigation using LVF perturbation. The temporal map of orbiting time of REs shows that REs originating from the inboard side edge region ( ψ N > 0.5) of the plasma are relatively more prone to be lost with the application of suitable LVF perturbation than those originating from the plasma core. Interestingly, the simulation results demonstrate the existence of strong correlation between the safety factor (q) profile in the plasma edge region ( ψ N > 0.7) and the level of RE deconfinement using LVF perturbation.

Enhanced cooling performance of blade tip slot cooling: Effect of slot open length

Addressing the critical challenge of thermal load-induced damage in turbine blade tips, this study aims to elucidate the effects of slot open length on film cooling effectiveness (FCE) across turbine blade tips with Pressure Side (PS) and Suction Side (SS) slots considering the application of additive manufacturing to turbine blade tips. Employing a linear cascade setup and the pressure sensitive paint (PSP) technique, we examined and quantified cooling performance across turbine blade tips with PS or SS slots at various slot open lengths. We revealed that while short slot open lengths enhance FCE at the leading edge (LE) due to increased averaged blowing ratios, they fail to adequately cover the trailing edge (TE) region. This decrease in cooling performance is largely attributable to the mixing of coolant with hot gas. In contrast, longer slot open lengths achieve a consistent FCE distribution across the blade tip despite a slight decrease in FCE at the LE region. The study suggests that integrating additional thermal design strategies, such as partition walls with slots, could effectively manage hot gas behaviors, thus enhancing the overall cooling design of turbine blade tips. This research makes a significant contribution to the field of turbine blade tip cooling design, providing insights into optimizing cooling performance through advanced slot configurations enabled by additive manufacturing technologies.

Core and edge modeling of JT-60SA H-mode highly radiative scenarios using SOLEDGE3X–EIRENE and METIS codes

In its first phase of exploitation, JT-60SA will be equipped with an inertially cooled divertor, which can sustain heat loads of 10 MW/m2 on the targets for a few seconds, which is much shorter than the intended discharge duration. Therefore, in order to maximize the duration of discharges, it is crucial to develop operational scenarios with a high radiated fraction in the plasma edge region without unacceptably compromising the scenario performance. In this study, the core and edge conditions of unseeded and neon-seeded deuterium H-mode scenarios in JT-60SA were investigated using METIS and SOLEDGE3X–EIRENE codes. The aim was to determine whether, and under which operational conditions, it would be possible to achieve heat loads at the targets significantly lower than 10 MW/m2 and potentially establish a divertor-detached regime while keeping favorable plasma core conditions. In first analysis, an investigation of the edge parameter space of unseeded scenarios was carried out. Simulations at an intermediate edge power of 15 MW indicate that, without seeded impurities, the heat loads at the targets are higher than 10 MW/m2 in attached cases, and achieving detachment is challenging, requiring upstream electron densities at least above 4 × 1019 m−3. This points toward the need for impurity injection during the first period of exploitation of the machine. Therefore, neon seeding simulations were carried out, performing a seeding rate scan and an injected power scan while keeping the upstream electron density at the separatrix at 3 × 1019 m−3. They show that at 15 MW of power injected into the edge plasma, the inner target is easily detached and presents low heat loads when neon is injected. However, at the outer target, the heat fluxes are not lowered below 10 MW/m2, even when the power losses in the edge plasma are equal to 50% of the power crossing the separatrix. Therefore, the tokamak will probably need to be operated in a deep detached regime in its first phase of exploitation for discharges longer than a few seconds. In the framework of core–edge integrated modeling, using METIS, the power radiated in the core was computed for the most interesting cases.

EBC-Net: 3D semi-supervised segmentation of pancreas based on edge-biased consistency regularization in dual perturbation space.

Deep learning technology has made remarkable progress in pancreatic image segmentation tasks. However, annotating 3D medical images is time-consuming and requires expertise, and existing semi-supervised segmentation methods perform poorly in the segmentation task of organs with blurred edges in enhanced CT such as the pancreas. To address the challenges of limited labeled data and indistinct boundaries of regions of interest (ROI). We propose Edge-Biased Consistency Regularization (EBC-Net). 3D edge detection is employed to construct edge perturbations and integrate edge prior information into limited data, aiding the network in learning from unlabeled data. Additionally, due to the one-sidedness of a single perturbation space, we expand the dual-level perturbation space of both images and features to more efficiently focus the model's attention on the edges of the ROI. Finally, inspired by the clinical habits of doctors, we propose a 3D Anatomical Invariance Extraction Module and Anatomical Attention to capture anatomy-invariant features. Extensive experiments have demonstrated that our method outperforms state-of-the-art methods in semi-supervised pancreas image segmentation. Moreover, it can better preserve the morphology of pancreatic organs and excel at edges region accuracy. Incorporated with edge prior knowledge, our method mixes disturbances in dual-perturbation space, which shifts the network's attention to the fuzzy edge region using a few labeled samples. These ideas have been verified on the pancreas segmentation dataset.

Quantitative impacts of dominant large-scale circulation systems on surface ozone pollution in China

Tropospheric ozone pollution has been worsened over most regions of China, adversely affecting human health and ecosystems. The long-term ozone concentration depends largely upon atmospheric circulations. Here, we conducted meteorological adjustment to quantitatively assess the influences of meteorological factors on the ozone evolution in China's seven city clusters during the warm season (April to October) from 2013 to 2020. Our analysis indicated that northern and eastern regions experienced ozone increases driven by emission changes. Southern regions, particularly the Pearl River Delta (PRD), exhibited ozone rise primarily due to meteorological conditions despite emission changes. In the Sichuan Basin (SCB) and Central Yangtze River Plain (CYP), where ozone levels decreased, meteorological conditions played a significant role in suppressing the ascent of ozone. Empirical orthogonal functions (EOF) analyses suggested that the spatiotemporal trend of meteorology-associated ozone was strongly correlated with the variation of East Asian Trough (EAT), South Asian High (SAH) and the western Pacific subtropical high (WPSH). The top three EOF patterns explained 33.4 %, 21.8 %, and 16.0 % of the total variance in meteorology-associated ozone. Absolute principal component scores-multiple linear regression (APCS-MLR) analyse quantitatively identified that enhanced EAT and SAH with a northward location of WPSH were favourable to surface ozone formation in central and eastern regions, but unfavourable to ozone formation in edge regions such as SCB.

Category-agnostic semantic edge detection by measuring neural representation randomness

Edge detection plays a fundamental role in computer vision tasks and gains wide applications. In particular, semantic edge detection recently draws more attention due to the high demand for a fine-grained understanding of visual scenes. However, detecting high-level semantic edges hidden in visual scenes is quite challenging. Existing semantic edge detection methods focus on category-aware semantic edges and require elaborate category annotations. Instead, we first propose the category-agnostic semantic edge detection task without additional semantic category annotations. To achieve this goal, we propose to utilize only edge position annotations and leverage the information randomness of semantic edges. Specifically, we align semantic edge positions to the ground truth by maximizing randomness on edge regions and minimizing randomness on non-edge regions in the training process. In the inference process, we first obtain neural representations by the trained network, and then generate semantic edges by measuring neural randomness. We evaluate our method by comparisons with alternative methods on two well-known datasets: Cityscapes (Cordts et al., 2016) and SBD (Hariharan et al., 2014). The results demonstrate our superiority over the alternatives, which is more significant under weak annotations. We also provide comprehensive mechanism studies to verify the generalizability, rationality, and validity of our working mechanism.

Real-time confinement regime detection in fusion plasmas with convolutional neural networks and high-bandwidth edge fluctuation measurements

A real-time detection of the plasma confinement regime can enable new advanced plasma control capabilities for both the access to and sustainment of enhanced confinement regimes in fusion devices. For example, a real-time indication of the confinement regime can facilitate transition to the high-performing wide-pedestal (WP) quiescent H-mode, or avoid unwanted transitions to lower confinement regimes that may induce plasma termination. To demonstrate real-time confinement regime detection, we use the 2D beam emission spectroscopy (BES) diagnostic system to capture localized density fluctuations of long wavelength turbulent modes in the edge region at a 1 MHz sampling rate. BES data from 330 discharges in either L-mode, H-mode, quiescent H (QH)-mode, or WP QH-mode were collected from the DIII-D tokamak and curated to develop a high-quality database to train a deep-learning classification model for real-time confinement detection. We utilize the 6×8 spatial configuration with a time window of 1024 µs and recast the input to obtain spectral-like features via fast Fourier transform preprocessing. We employ a shallow 3D convolutional neural network for the multivariate time-series classification task and utilize a softmax in the final dense layer to retrieve a probability distribution over the different confinement regimes. Our model classifies the global confinement state on 44 unseen test discharges with an average F 1 score of 0.94, using only ∼1 ms snippets of BES data at a time. This activity demonstrates the feasibility for real-time data analysis of fluctuation diagnostics in future devices such as ITER, where the need for reliable and advanced plasma control is urgent.

Cracking mechanism of CMAS-corroded thermal barrier coatings based on a coupled thermo-chemo-mechanically phase-field fracture model

A thermo-chemo-mechanically coupled theoretical framework is proposed to describe the calcium-magnesium-alumina-silicate (CMAS) corrosion process during the cooling process. A phase-field fracture model is developed to investigate the effect of cooling temperature and CMAS concentration on the degree of corrosion reaction, the stress evolution and the crack initiation and propagation. σ11 concentrates in the region beneath the overlay of CMAS and σ22 appears at the interface between top ceramic coating (TC) and bond coating (BC). The higher stress concentration of σ11 and σ22 contribute to the formation of both vertical and transverse cracks. Transverse cracks first emerge at the interface between TC and BC in the edge region, followed by the formation of vertical cracks in the CMAS-coated region. Vertical cracks propagate to the interface and deflect into transverse cracks. The transverse cracks at the interface further propagate and merge, ultimately leading to the coating delamination. The higher initial cooling temperature and CMAS concentration contribute to the accelerated development of vertical cracking and the increase of the quantity and length of transverse and vertical cracks. The model provides a significant advantage in predicting the failure of TBCs during the cooling stage of CMAS corrosion.

Experimental and numerical study on the loading rate dependent tensile behavior of carbon fiber/epoxy interface

A series of experiments and simulations were performed to explore the effect of loading rate on the tensile behavior of carbon fiber/epoxy composite interface via the fiber bundle tensile method. Varying velocities were used to test the stress‒time and stress‒displacement curves of the samples, and a high-speed camera was used to study the in situ failure behavior of the carbon fiber/epoxy interface. Increasing the loading rate from 5 × 10−6 m/s to 12.0 m/s leds to an increase in the interfacial tensile strength from 6.1 ± 0.9 MPa to 16.4 ± 0.3 MPa, an increase in the interfacial stiffness from 1.58 ± 0.3 N/m to 17.4 ± 3.1 N/m, and a decrease in the fracture displacement from 0.23 ± 0.03 mm to 0.10 ± 0.01 mm. Optical microscopy analysis revealed rougher crack surfaces at higher loading rates. The fracture mode of interface transitioned from fiber breakage and pull-out to brittle matrix cracking with increasing loading rate. The finite element method was employed to verify the effectiveness of the fiber bundle tensile method with a split Hopkinson tension bar and study the failure behavior of the interface under dynamic loading. The simulation results showed that the calculated failure stress was 20 % lower than the actual value, and the cohesive layer was found to have greater stress at the edge region. This investigation deepens the understanding of the effects of the loading rate on the interfacial tensile behaviors of carbon fiber/epoxy composites.

Estimation of LAI of tobacco plant using selected spectral subsets of visible and near-infrared reflectance spectroscopy

Flue-cured tobacco is a main economic crop, and leaves are the direct product of tobacco plant. Monitoring leaf area index (LAI) of tobacco plant is important to field management, yield prediction, and industry regulation. Hyperspectral data have hundreds of narrow spectral bands in continuous spectral ranges, significantly advancing monitoring of LAI. However, considering spectral responses of LAI vary with wavelength, the use of the full spectral range in estimation of LAI is redundant. To reduce spectral redundancy and improve estimation of LAI, spectral subsets were selected based on importance of spectral bands. Variable importance in the projection (VIP) score obtained by partial least squares regression (PLSR) was adopted to measure the importance. The study was conducted in Yunnan Province, China. Canopy reflectance spectra of tobacco plant were measured in two consecutive growth seasons. Genetic algorithm (GA) and PLSR were used for model calibration. The identified important spectral regions for estimation of LAI were red edge, near-infrared (NIR), and green regions. In estimation of LAI of tobacco plant, compared with the estimation using the full spectral range of VNIR reflectance spectra, normalized root mean square error (NRMSE) and coefficient of determination (R2) values were improved from 10.30% and 0.83 to 7.68% and 0.90 and from 18.78% and 0.43 to 7.65% and 0.90 by using the reflectance spectra in identified spectral regions in the growth seasons in 2021 and 2022 separately. In addition to the identified continuous spectral regions, central bands of the identified spectral regions also achieved estimation of LAI, with the highest R2 value reaching 0.72. The selected spectral subsets improved estimation accuracy and reduced model complexity. The results indicate that selected spectral subsets are effective and promising in estimation of LAI, providing an alternative for estimation of LAI using hyperspectral data.

Effects of edge disorder on the stability of quantum oscillations in two-dimensional coupled systems

This paper utilizes the theory of quantum diffusion to analyze the electron probability and spreading width of a wavepacket on each layer in a two-dimensional (2D) coupled system with edge disorder, aiming to clarify the effects of edge disorder on the stability of the electron periodic oscillations in 2D coupled systems. Using coupled 2D square lattices with edge disorder as an example, we show that, the electron probability and wavepacket spreading width exhibit periodic oscillations and damped oscillations, respectively, before and after the wavepacket reaches the boundary. Furthermore, these electron oscillations exhibit strong resistance against disorder perturbation with a longer decay time in the regime of large disorder, due to the combined influences of ordered and disordered site energies in the central and edge regions. Finally, we numerically verified the universality of the results through bilayer graphene, demonstrating that this anomalous quantum oscillatory behavior is independent of lattice geometry. Our findings are helpful in designing relevant quantum devices and understanding the influence of edge disorder on the stability of electron periodic oscillations in 2D coupled systems.

Wavelength calibration and spectral analysis of vacuum ultraviolet spectroscopy in EAST

A vacuum ultraviolet (VUV) spectroscopy with a focal length of 1 m has been engineered specifically for observing edge impurity emissions in Experimental Advanced Superconducting Tokamak (EAST). In this study, wavelength calibration for the VUV spectroscopy is achieved utilizing a zinc lamp. The grating angle and charge-coupled device (CCD) position are carefully calibrated for different wavelength positions. The wavelength calibration of the VUV spectroscopy is crucial for improving the accuracy of impurity spectral data, and is required to identify more impurity spectral lines for impurity transport research. Impurity spectra of EAST plasmas have also been obtained in the wavelength range of 50–300 nm with relatively high spectral resolution. It is found that the impurity emissions in the edge region are still dominated by low-Z impurities, such as carbon, oxygen, and nitrogen, albeit with the application of full-tungsten divertors on the EAST tokamak.