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Title: Validation metrics for turbulent plasma transport

Abstract

Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnostics to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. The utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak [J. L. Luxon, Nucl. Fusion 42, 614 (2002)], as part of a multi-year transport model validation activity.

Authors:
 [1]
  1. Center for Energy Research, University of California, San Diego, La Jolla, California 92093-0417 (United States)
Publication Date:
OSTI Identifier:
22598964
Resource Type:
Journal Article
Resource Relation:
Journal Name: Physics of Plasmas; Journal Volume: 23; Journal Issue: 6; Other Information: (c) 2016 Author(s); Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
70 PLASMA PHYSICS AND FUSION TECHNOLOGY; COMPARATIVE EVALUATIONS; COMPUTERIZED SIMULATION; DOUBLET-3 DEVICE; FLUCTUATIONS; METRICS; PLASMA; TRANSPORT THEORY; TURBULENT FLOW; VALIDATION

Citation Formats

Holland, C., E-mail: chholland@ucsd.edu. Validation metrics for turbulent plasma transport. United States: N. p., 2016. Web. doi:10.1063/1.4954151.
Holland, C., E-mail: chholland@ucsd.edu. Validation metrics for turbulent plasma transport. United States. doi:10.1063/1.4954151.
Holland, C., E-mail: chholland@ucsd.edu. 2016. "Validation metrics for turbulent plasma transport". United States. doi:10.1063/1.4954151.
@article{osti_22598964,
title = {Validation metrics for turbulent plasma transport},
author = {Holland, C., E-mail: chholland@ucsd.edu},
abstractNote = {Developing accurate models of plasma dynamics is essential for confident predictive modeling of current and future fusion devices. In modern computer science and engineering, formal verification and validation processes are used to assess model accuracy and establish confidence in the predictive capabilities of a given model. This paper provides an overview of the key guiding principles and best practices for the development of validation metrics, illustrated using examples from investigations of turbulent transport in magnetically confined plasmas. Particular emphasis is given to the importance of uncertainty quantification and its inclusion within the metrics, and the need for utilizing synthetic diagnostics to enable quantitatively meaningful comparisons between simulation and experiment. As a starting point, the structure of commonly used global transport model metrics and their limitations is reviewed. An alternate approach is then presented, which focuses upon comparisons of predicted local fluxes, fluctuations, and equilibrium gradients against observation. The utility of metrics based upon these comparisons is demonstrated by applying them to gyrokinetic predictions of turbulent transport in a variety of discharges performed on the DIII-D tokamak [J. L. Luxon, Nucl. Fusion 42, 614 (2002)], as part of a multi-year transport model validation activity.},
doi = {10.1063/1.4954151},
journal = {Physics of Plasmas},
number = 6,
volume = 23,
place = {United States},
year = 2016,
month = 6
}
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