About SMARTS

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The 2022 Bold Decadal Vision for Commercial Fusion Energy challenges us to demonstrate a path to economically attractive fusion power. Doing so will require cost-effective modeling and simulation tools to provide accurate, timely, and actionable predictions. In particular, the entire design and assessment of a fusion pilot plant (FPP) will require the capability of whole facility modeling (WFM) to address the myriad engineering challenges beyond “simply” confining and sustaining a burning plasma. Yet accurate descriptions of the burning plasma remain central to the FPP’s design, as that plasma produces the heat and neutron fluxes to be transformed into electricity. To date, the tokamak is the most well-developed FPP confinement concept, in both experimentally demonstrated performance and our ability to predict the plasma’s dynamics accurately. However, significant uncertainties remain for predictions of many key quantities, wildly when extrapolating from current-day facilities to future burning plasmas. Some of the most uncertain high-leverage quantities are the densities of various charged particle species across the plasma. Predicting these densities at different locations across the plasma is vital to optimizing FPP performance, and a validated predictive capability for multi-species particle transport and confinement is essential for a viable WFM capability.

The ultimate objective of the SMARTS (Surrogate Models for Accurate and Rapid Transport Solutions) project is to provide the modeling and simulation capabilities needed to resolve this gap by substantially advancing our ability to accurately predict multi-species particle and thermal confinement in tokamak burning plasmas. To do so, we will combine demonstrated advances in GPU acceleration of gyrokinetic codes, applications of Bayesian optimization and surrogate models to transport in fusion plasmas, and tokamak-integrated modeling capabilities. Through this approach, we will deliver: