Nonlinear growth of magnetic islands by passing fast ions in NSTX

Yang, James; Fredrickson, Eric; Podestà, Mario; Poli, Francesca

doi:10.11578/1888280

Title: Nonlinear growth of magnetic islands by passing fast ions in NSTX

Dataset
Other Related Research

Abstract

The growth of magnetic islands in NSTX is modeled successfully, with the consideration of passing fast ions. It is shown that a good quantitative agreement between simulation and experimental measurement can be achieved when the uncompensated cross-field current induced by passing fast ions is included in the island growth model. The fast ion parameters, along with other equilibrium parameters, are obtained self-consistently using the TRANSP code with the assumptions of the ‘kick’ model (Podestà et al 2017 Plasma Phys. Control. Fusion 59 095008). The results show that fast ions can contribute to overcoming the stabilizing effect of polarization current for magnetic island growth.

Authors:

Yang, James; Fredrickson, Eric; Podestà, Mario; Poli, Francesca

Princeton Plasma Physics Laboratory

Publication Date:: Wed Jul 13 00:00:00 EDT 2022

DOE Contract Number:: AC02-09CH11466

Research Org.:: Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ (United States)

Sponsoring Org.:: USDOE Office of Science (SC)

Subject:: Fast ions; NSTX; kick model; neoclassical tearing modes

OSTI Identifier:: 1888280

DOI:: https://doi.org/10.11578/1888280

Citation Formats


                    Yang, James, Fredrickson, Eric, Podestà, Mario, and Poli, Francesca. Nonlinear growth of magnetic islands by passing fast ions in NSTX.  United States: N. p., 2022. 
        Web.  doi:10.11578/1888280.

Copy to clipboard


                    Yang, James, Fredrickson, Eric, Podestà, Mario, & Poli, Francesca. Nonlinear growth of magnetic islands by passing fast ions in NSTX.  United States.  doi:https://doi.org/10.11578/1888280

Copy to clipboard


                    Yang, James, Fredrickson, Eric, Podestà, Mario, and Poli, Francesca. 2022.  
"Nonlinear growth of magnetic islands by passing fast ions in NSTX".  United States.  doi:https://doi.org/10.11578/1888280.  https://www.osti.gov/servlets/purl/1888280. Pub date:Wed Jul 13 00:00:00 EDT 2022

Copy to clipboard


                    
@article{osti_1888280,

  title        = {Nonlinear growth of magnetic islands by passing fast ions in NSTX},

  author       = {Yang, James and Fredrickson, Eric and Podestà, Mario and Poli, Francesca},

  abstractNote = {The growth of magnetic islands in NSTX is modeled successfully, with the consideration of passing fast ions. It is shown that a good quantitative agreement between simulation and experimental measurement can be achieved when the uncompensated cross-field current induced by passing fast ions is included in the island growth model. The fast ion parameters, along with other equilibrium parameters, are obtained self-consistently using the TRANSP code with the assumptions of the ‘kick’ model (Podestà et al 2017 Plasma Phys. Control. Fusion 59 095008). The results show that fast ions can contribute to overcoming the stabilizing effect of polarization current for magnetic island growth.},

  doi          = {10.11578/1888280},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Jul 13 00:00:00 EDT 2022},

  month        = {Wed Jul 13 00:00:00 EDT 2022}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.11578/1888280

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

Nonlinear growth of magnetic islands by passing fast ions in NSTX

Journal Article Yang, James ; Fredrickson, Eric D. ; Podestà, Mario ; ... - Plasma Physics and Controlled Fusion

The growth of magnetic islands in NSTX is modeled successfully, with the consideration of passing fast ions. It is shown that a good quantitative agreement between simulation and experimental measurement can be achieved when the uncompensated cross-field current induced by passing fast ions is included in the island growth model. The fast ion parameters, along with other equilibrium parameters, are obtained self-consistently using the TRANSP code with the assumptions of the 'kick' model (Podestà et al 2017 Plasma Phys. Control. Fusion 59 095008). Overall, the results show that fast ions can contribute to overcoming the stabilizing effect of polarization currentmore » for magnetic island growth.« less
On the scattering correction of fast-ion D-alpha signal on NSTX-U

Dataset Hao, G Z ; Heidbrink, W W ; Liu, D ; ...

Analysis of fast-ion D-alpha (FIDA) data on National Spherical Torus Experiment-Upgrade (NSTX-U) shows that the cold Dα line contaminates the FIDA baseline. The scattered light is comparable to the FIDA emission. A scattering correction is required to extract the FIDA signal. Two methods that relate the scattered light contamination to the intensity of the cold Dα line are employed. One method uses laboratory measurements with a calibration lamp; the other method uses data acquired during plasma operation and singular value decomposition analysis. After correction, both the FIDA spectra and spatial profile are in better agreement with theoretical predictions.
Role of fast ions in spontaneous neoclassical tearing mode instabilities in NSTX

Dataset Yang, James ; Podesta, Mario ; Fredrickson, Eric ; ...
Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX

Dataset Woods, B. J. Q. ; Duarte, V. N. ; Fredrickson, E. D. ; ...

Abrupt large events in the Alfvenic and sub-Alfvenic frequency bands in tokamaks are typically correlated with increased fast-ion loss. Here, machine learning is used to speed up the laborious process of characterizing the behavior of magnetic perturbations from corresponding frequency spectrograms that are typically identified by humans. The analysis allows for comparison between different mode character (such as quiescent, fixed frequency, and chirping, avalanching) and plasma parameters obtained from the TRANSP code, such as the ratio of the neutral beam injection (NBI) velocity and the Alfven velocity (v_inj./v_A), the q-profile, and the ratio of the neutral beam beta and themore »« less
Machine Learning Characterization of Alfvénic and Sub-Alfvénic Chirping and Correlation With Fast-Ion Loss at NSTX

Dataset Woods, B J Q ; Duarte, V N ; Fredrickson, E D ; ...

Abrupt large events in the Alfvenic and sub-Alfvenic frequency bands in tokamaks are typically correlated with increased fast-ion loss. Here, machine learning is used to speed up the laborious process of characterizing the behavior of magnetic perturbations from corresponding frequency spectrograms that are typically identified by humans. The analysis allows for comparison between different mode character (such as quiescent, fixed frequency, and chirping, avalanching) and plasma parameters obtained from the TRANSP code, such as the ratio of the neutral beam injection (NBI) velocity and the Alfven velocity (v_inj./v_A), the q-profile, and the ratio of the neutral beam beta and themore »« less

Similar Records