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Orchestrating TRANSP Simulations for Interpretative and Predictive Tokamak Modeling with OMFIT

托卡马克 外推法 计算机科学 公制(单位) 一致性(知识库) 核工程 等离子体 物理 核物理学 数学 人工智能 工程类 运营管理 数学分析
作者
B. A. Grierson,Xingqiu Yuan,M. Gorelenkova,S. Kaye,N.C. Logan,O. Meneghini,S. R. Haskey,J. Buchanan,M. Fitzgerald,S. P. Smith,Lang Cui,R. Budny,F. M. Poli
出处
期刊:Fusion Science and Technology [Taylor & Francis]
卷期号:74 (1-2): 101-115 被引量:66
标识
DOI:10.1080/15361055.2017.1398585
摘要

TRANSP simulations are being used in the OMFIT workflow 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 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 versus calculated neutron rate, equilibrium stored energy versus total stored energy from profile and fast-ion pressure, and experimental versus computed surface loop voltage. Discrepancies between data consistency metrics can indicate errors in input quantities such as electron density profile or , 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 postprocessing 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. International Tokamak Physics Activity (ITPA) validation metrics are provided in postprocessing to assess the transport model validity. By using OMFIT to orchestrate the steps for experimental data preparation, selection of operating mode, submission, postprocessing, and visualization, we have streamlined and standardized the usage of TRANSP.
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