Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers

Rodriguez-Fernandez, P.; Howard, N. T.; Saltzman, A.; Kantamneni, S.; Candy, J.; Holland, C.; Balandat, M.; Ament, S.; White, A. E.

doi:10.1088/1741-4326/ad4b3d

Title: Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers

Journal Article · 05 June 2024 · Nuclear Fusion

DOI: https://doi.org/10.1088/1741-4326/ad4b3d · OSTI ID:2370606

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; Kantamneni, S.;

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Abstract This work presents the PORTALS framework (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), which leverages surrogate modeling and optimization techniques to enable the prediction of core plasma profiles and performance with nonlinear gyrokinetic simulations at significantly reduced cost, with no loss of accuracy. The efficiency of PORTALS is benchmarked against standard methods, and its full potential is demonstrated on a unique, simultaneous 5-channel (electron temperature, ion temperature, electron density, impurity density and angular rotation) prediction of steady-state profiles in a DIII-D ITER Similar Shape plasma with GPU-accelerated, nonlinear CGYRO (Candy et al 2016 J. Comput. Phys. 324 73–93). This paper also provides general guidelines for accurate performance predictions in burning plasmas and the impact of transport modeling in fusion pilot plants studies.

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Sponsoring Organization:: USDOE Office of Science (SC), Fusion Energy Sciences (FES)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2370606

Journal Information:: Nuclear Fusion, Journal Name: Nuclear Fusion Journal Issue: 7 Vol. 64; ISSN 0029-5515

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: IAEA

Language:: English

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