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Title: Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT

Abstract

TRANSP simulations are being used in the OMFIT work- flow manager to enable a machine independent means of experimental analysis, postdictive validation, and predictive time dependent simulations on the DIII-D, NSTX, JET and C-MOD tokamaks. The procedures for preparing the input data from plasma profile diagnostics and equilibrium reconstruction, as well as processing of the time-dependent heating and current drive sources and assumptions about the neutral recycling, vary across machines, but are streamlined by using a common workflow manager. Settings for TRANSP simulation fidelity are incorporated into the OMFIT framework, contrasting between-shot analysis, power balance, and fast-particle simulations. A previously established series of data consistency metrics are computed such as comparison of experimental vs. calculated neutron rate, equilibrium stored energy vs. total stored energy from profile and fast-ion pressure, and experimental vs. computed surface loop voltage. Discrepancies between data consistency metrics can indicate errors in input quantities such as electron density profile or Zeff, or indicate anomalous fast-particle transport. Measures to assess the sensitivity of the verification metrics to input quantities are provided by OMFIT, including scans of the input profiles and standardized post-processing visualizations. For predictive simulations, TRANSP uses GLF23 or TGLF to predict core plasma profiles, with usermore » defined boundary conditions in the outer region of the plasma. ITPA validation metrics are provided in post-processing to assess the transport model validity. By using OMFIT to orchestrate the steps for experimental data preparation, selection of operating mode, submission, post-processing and visualization, we have streamlined and standardized the usage of TRANSP.« less

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [1];  [2];  [1];  [3];  [3];  [2];  [1];  [1];  [1]
  1. Princeton Plasma Physics Lab. (PPPL), Princeton, NJ (United States)
  2. General Atomics, San Diego, CA (United States)
  3. Culham Science Centre, Abingdon (United Kingdom). Culham Centre for Fusion Energy (CCFE), EURATOM/UKAEA Fusion Association
Publication Date:
Research Org.:
General Atomics, San Diego, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Fusion Energy Sciences (FES) (SC-24)
OSTI Identifier:
1424383
Grant/Contract Number:  
FC02-04ER54698; AC02-09CH11466
Resource Type:
Accepted Manuscript
Journal Name:
Fusion Science and Technology
Additional Journal Information:
Journal Volume: 73; Journal Issue: 2018; Related Information: Pages 1-15; Journal ID: ISSN 1536-1055
Publisher:
American Nuclear Society
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY; TRANSP; integrated simulations; plasma transport

Citation Formats

Grierson, B. A., Yuan, X., Gorelenkova, M., Kaye, S., Logan, N. C., Meneghini, O., Haskey, S. R., Buchanan, J., Fitzgerald, M., Smith, S. P., Cui, L., Budny, R. V., and Poli, F. M. Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT. United States: N. p., 2018. Web. doi:10.1080/15361055.2017.1398585.
Grierson, B. A., Yuan, X., Gorelenkova, M., Kaye, S., Logan, N. C., Meneghini, O., Haskey, S. R., Buchanan, J., Fitzgerald, M., Smith, S. P., Cui, L., Budny, R. V., & Poli, F. M. Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT. United States. doi:10.1080/15361055.2017.1398585.
Grierson, B. A., Yuan, X., Gorelenkova, M., Kaye, S., Logan, N. C., Meneghini, O., Haskey, S. R., Buchanan, J., Fitzgerald, M., Smith, S. P., Cui, L., Budny, R. V., and Poli, F. M. Wed . "Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT". United States. doi:10.1080/15361055.2017.1398585. https://www.osti.gov/servlets/purl/1424383.
@article{osti_1424383,
title = {Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT},
author = {Grierson, B. A. and Yuan, X. and Gorelenkova, M. and Kaye, S. and Logan, N. C. and Meneghini, O. and Haskey, S. R. and Buchanan, J. and Fitzgerald, M. and Smith, S. P. and Cui, L. and Budny, R. V. and Poli, F. M.},
abstractNote = {TRANSP simulations are being used in the OMFIT work- flow manager to enable a machine independent means of experimental analysis, postdictive validation, and predictive time dependent simulations on the DIII-D, NSTX, JET and C-MOD tokamaks. The procedures for preparing the input data from plasma profile diagnostics and equilibrium reconstruction, as well as processing of the time-dependent heating and current drive sources and assumptions about the neutral recycling, vary across machines, but are streamlined by using a common workflow manager. Settings for TRANSP simulation fidelity are incorporated into the OMFIT framework, contrasting between-shot analysis, power balance, and fast-particle simulations. A previously established series of data consistency metrics are computed such as comparison of experimental vs. calculated neutron rate, equilibrium stored energy vs. total stored energy from profile and fast-ion pressure, and experimental vs. computed surface loop voltage. Discrepancies between data consistency metrics can indicate errors in input quantities such as electron density profile or Zeff, or indicate anomalous fast-particle transport. Measures to assess the sensitivity of the verification metrics to input quantities are provided by OMFIT, including scans of the input profiles and standardized post-processing visualizations. For predictive simulations, TRANSP uses GLF23 or TGLF to predict core plasma profiles, with user defined boundary conditions in the outer region of the plasma. ITPA validation metrics are provided in post-processing to assess the transport model validity. By using OMFIT to orchestrate the steps for experimental data preparation, selection of operating mode, submission, post-processing and visualization, we have streamlined and standardized the usage of TRANSP.},
doi = {10.1080/15361055.2017.1398585},
journal = {Fusion Science and Technology},
number = 2018,
volume = 73,
place = {United States},
year = {2018},
month = {2}
}

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