A5038291431- Magnetic confinement fusion research
- Fusion materials and technologies
- Superconducting Materials and Applications
- Ionosphere and magnetosphere dynamics
- Network Security and Intrusion Detection
- Laser-Plasma Interactions and Diagnostics
- Anomaly Detection Techniques and Applications
- Sentiment Analysis and Opinion Mining
- Topic Modeling
- Semantic Web and Ontologies
- Authorship Attribution and Profiling
- Solar and Space Plasma Dynamics
- Traffic Prediction and Management Techniques
- Mental Health via Writing
- Data Quality and Management
- COVID-19 diagnosis using AI
Shenyang Aerospace University
2024-2025
Massachusetts Institute of Technology
2019-2024
Plasma Technology (United States)
2019-2023
Fusion Academy
2019-2023
Fusion (United States)
2020-2023
The SPARC tokamak is a critical next step towards commercial fusion energy. designed as high-field ( $B_0 = 12.2$ T), compact $R_0 1.85$ m, $a 0.57$ m), superconducting, D-T with the goal of producing gain $Q>2$ from magnetically confined plasma for first time. Currently under design, will continue path Alcator series tokamaks, utilizing new magnets based on rare earth barium copper oxide high-temperature superconductors to achieve high performance in device. achievable conservative...
SPARC is being designed to operate with a normalized beta of $\beta _N=1.0$ , density $n_G=0.37$ and safety factor $q_{95}\approx 3.4$ providing comfortable margin their respective disruption limits. Further, low poloidal _p=0.19$ at the $q=2$ surface reduces drive for neoclassical tearing modes, which together frozen-in classically stable current profile might allow access robustly tearing-free operating space. Although inherent stability expected reduce frequency disruptions, loading...
Detecting personalities in social media content is an important application of personality psychology. Most early studies apply a coherent piece writing to detection, but today, the challenge identify dominant traits from series short, noisy posts. To this end, recent have attempted individually encode deep semantics posts, often using attention-based methods, and then relate them, or directly assemble them into graph structures. However, due inherently disjointed nature content,...
Next generation high performance (HP) tokamaks risk damage from unmitigated disruptions at current and power. Achieving reliable disruption prediction for a device's HP operation based on its low (LP) data is key to success. In this letter, through explorative analysis dedicated numerical experiments multiple existing tokamaks, we demonstrate how the operational regimes of can affect power trained predictor. First, our results suggest data-driven predictors abundant LP discharges work poorly...
Abstract Analyses of the DIII-D ITER Baseline Scenario database support that disruptive m,n =2,1 magnetic islands are pressure gradient driven, non-linear instabilities seeded in a sequence stochastic transient perturbations, and current profile relaxation does not affect island onset rate. At low torque, these Neoclassical Tearing Modes most commonly by 3-wave coupling when differential rotation between q =1 & =2 rational surfaces approaches zero. Lack statistically significant...
Abstract Databases of physics events have been used in various fusion research applications, including the development scaling laws and disruption avoidance algorithms, yet they can be time-consuming tedious to construct. This paper presents a novel application label spreading semi-supervised learning algorithm accelerate this process by detecting distinct large dataset discharges, given few manually labeled examples. A high detection accuracy (>85%) for H–L back transitions initially...
m, n = 2, 1 tearing mode onset empirical probability and machine learning analyses of a multiscenario DIII-D database over 14 000 H-mode discharges show that the normalized plasma beta, rotation profile, magnetic equilibrium shape have strongest impact on 2,1 stability, in qualitative agreement with neoclassical modes (m are poloidal toroidal numbers, respectively). In addition, most likely to destabilize when > already present core plasma. The covariance matrix sensitive parameters...
An O-mode microwave reflectometry system has been developed to measure the density fluctuation on Zheda Plasma Experiment Device (ZPED). The frequency range of this diagnostic is from 10 GHz 18 GHz, corresponding cutoff densities 0.13×1019m-3 0.4×1019m-3. fluctuations are measured with a fixed for plasma in different magnetic field. It observed that power changes field nonlinearly: increase linearly when less than critical field, while almost no change larger
As an important task in the field of information extraction, event detection is widely used graph construction and network public opinion monitoring. Although existing methods (such as BGCN, MGRN-EE, etc.) have obtained well performance on by utilizing various features from text, they neglect that events data follows a long-tailed distribution, which leads to serious bias trained model. To address this issue, we propose model based sentence pre-determination, termed ES4ED, simple but...
Event extraction is a complex and challenging task in the field of information extraction. It aims to identify event types, triggers, argument from text. In recent years, overlapping has attracted attention researchers because its higher challenge practicability, some work carried out in-depth research on achieved remarkable results. But these works (1) ignore role ontology knowledge extraction; (2) use same semantic encoding for multi-stage models, lacking consideration independent...