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Title: Integrated fusion simulation with self-consistent core-pedestal coupling

Journal Article · · Physics of Plasmas
DOI:https://doi.org/10.1063/1.4947204· OSTI ID:1319224

Accurate predictions of fusion performance requires including the strong interplay that exists between core transport, pedestal structure, current profile and plasma equilibrium. An integrated modeling workflow capable of finding the steady-state self-consistent solution to this strongly coupled problem has been developed. The workflow, leverages first principles calculations and does not require prior knowledge of the kinetic profiles. Validation against DIII-D discharges shows that the workflow is capable of robustly predicting the kinetic profiles (electron and ion temperature and electron density) from the axis to the separatrix in agreement with the experiments. Results of a self-consistent optimization of the 15 MA D-T ITER baseline scenario show that controlling the pedestal density and impurity content during ITER operations will be critical to achieve high fusion performance while satisfying the requirements imposed by the density-limit. Further, we developed two neural-network (NN) based models as a means to perform a non-linear multivariate regression of theory-based models for the core transport fluxes, as well as for the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. The coupled core-pedestal workflow using these NN-accelerated models has been validated against a large database of DIII-D discharges, showing overall excellent agreement and performance. The NN paradigm is capable of breaking the speed-accuracy tradeoff that is expected of traditional numerical models, and can provide the missing link towards self-consistent coupled core-pedestal WDM simulations that are physically accurate and yet take only seconds to run.

Research Organization:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); General Atomics, San Diego, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
Grant/Contract Number:
AC05-00OR22725; FC02-06ER54873; AC02-05CH11231; FC02-04ER54698; FG02-95ER54309; SC0012633; SC0012656
OSTI ID:
1319224
Alternate ID(s):
OSTI ID: 1248239; OSTI ID: 1372261; OSTI ID: 1489411
Journal Information:
Physics of Plasmas, Vol. 23, Issue 4; ISSN 1070-664X
Publisher:
American Institute of Physics (AIP)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 48 works
Citation information provided by
Web of Science

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Cited By (14)

Integrated modeling of high β N steady state scenario on DIII-D journal January 2018
Integrated Tokamak modeling: When physics informs engineering and research planning journal May 2018
Finite Larmor radius effects at the high confinement mode pedestal and the related force-free steady state journal April 2019
Predict-first experiments and modeling of perturbative cold pulses in the DIII-D tokamak journal June 2019
Self-consistent pedestal prediction for JET-ILW in preparation of the DT campaign journal July 2019
Integrated modelling of H-mode pedestal and confinement in JET-ILW journal November 2017
Dominant two-fluid magnetohydrodynamic instabilities in CFETR upgrade phase-I scenario in presence of perfect conducting wall journal February 2019
Self-consistent core-pedestal transport simulations with neural network accelerated models journal July 2017
Ideal MHD stability and characteristics of edge localized modes on CFETR journal November 2017
Evaluating the effects of tungsten on CFETR phase I performance journal October 2018
Progress of the CFETR design journal June 2019
Perturbative transport modeling of cold-pulse dynamics in Alcator C-Mod Ohmic plasmas journal May 2019
High fusion performance in Super H-mode experiments on Alcator C-Mod and DIII-D journal June 2019
Optimisation of confinement in a fusion reactor using a nonlinear turbulence model text January 2016

Figures / Tables (6)