Integrated Modeling of SPARC H-mode Scenarios: Exploration of the Impact of Modeling Assumptions on Predicted Performance
Marco Muraca, Pablo Rodriguez-Fernandez, Nathaniel T. Howard, Joe, Hall, Emiliano Fable, Giovanni Tardini

TL;DR
This study uses extensive simulations to analyze how modeling assumptions affect the predicted performance of SPARC H-mode scenarios, emphasizing the sensitivity of fusion gain to various input parameters.
Contribution
It provides a comprehensive database of SPARC H-mode predictions and examines the impact of input assumptions on plasma performance, highlighting the importance of sensitivity analysis.
Findings
Q > 5 achieved at 12T with 11 MW power for low W concentration
SPARC can reach Q > 1 at 8T with low W, indicating breakeven potential
Pedestal parameters significantly influence fusion gain predictions
Abstract
In this paper an extensive database of SPARC H-modes confinement predictions has been provided, to assess its variability with respect to few input assumptions. The simulations have been performed within the ASTRA framework, using the quasi-linear model TGLF SAT2, including electromagnetic effects, for the core transport, and a neural network trained on EPED simulations to predict the pedestal height and width self-consistently. The database has been developed starting from two SPARC H-mode discharges (12.2 T, i.e. Primary Reference Discharge or PRD, and 8 T, i.e. reduced field) and permuting 4 input parameters (W concentration, DT mixture concentration, temperature ratio at top of pedestal and deviation of pedestal pressure from the EPED prediction), to perform a sensitivity study. For the PRD a scan of auxiliary input power (ion cyclotron heating) has been performed up to 25MW, to…
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Taxonomy
TopicsMachine Learning in Materials Science
