Thomas Body

Integrated modeling of the flat-top phase of ARC H-modes has been conducted to assess the feasibility of high-performance scenarios compatible with divertor detachment. The analysis incorporates self-consistent evolution of impurity radiation and density profiles, demonstrating that fusion power levels approaching a GW can be achieved while maintaining divertor temperatures below 2 eV with Ar seeding. Sensitivity studies reveal a strong dependence of fusion power on the separatrix density, with performance spanning 750–1000 MW, and a weaker dependence on enrichment factor and pedestal density. Alternative seeding strategies using Neon have also been explored. Plasmas with Argon seeding consistently access H-mode, providing the highest fusion power and detached divertor operation, whereas Neon seeding leads to lower performance (600–850 MW) and less robust H-mode access, due to excessive core impurity accumulation. A small W impurity peaking has been found, with decreasing values at higher Z eff . Further analyses incorporate reduced momentum transport modeling, and sensitivity studies of neoclassical impurity transport, confirming the robustness of the results. Overall, these findings support the viability of high-performing H-mode operation in ARC, ensuring divertor protection, enabled through Argon and Neon impurity seeding.

This paper introduces the MAESTRO workflow, which enables the coupling of the PORTALS framework (Rodriguez-Fernandez et al 2024 Nucl. Fusion 64 076034) with external solvers for the plasma equilibrium, pedestal physics, divertor constraints and heating. The surrogate-based optimization nature of the transport solver is ideally suited for external coupling, allowing efficient steady-state predictions of plasma profiles with full physics models. Improvements in the surrogate modeling of quasilinear transport models with PORTALS are presented, which enable the efficient handling of discontinuities in the transport fluxes that can arise from numerical issues or physical instabilities with extreme stiffness. The combination of physics-informed methods and advanced numerical techniques allows the MAESTRO workflow to provide efficient predictions of steady-state plasma profiles, which are critical for fusion reactor design and optimization.

The transition between the ELMy H-mode and the EDA H-mode is studied on Alcator C-Mod using an experimental database and recently-developed predictive pedestal models. High-resolution Thomson scattering measurements are used to inspect both the separatrix and pedestal operational space using two independent fit functions, each tailored to analyze either the pedestal or the separatrix and near-SOL profiles. The pedestal density, n _e ^ped , and the separatrix density, n _e ^sep are compared to main chamber neutral measurements. n _e ^ped is sensitive to neutral sources only in the ELMy H-mode regime and not in the EDA H-mode regime. Density fluctuation spectra reveal that quasi-coherent structures become stronger at higher densities and more coherent in the EDA relative to the inter-ELM phases of ELMy H-modes, before weakening again at the highest values of n _e ^ped . The Saarelma-Connor pedestal density prediction model is validated for ELMy H-modes up to n _e ^ped = 2.0×10 ²⁰ m ^-3 . An additional transport channel driven by resistive ballooning modes (RBM), D _RBM , scaling directly with α _t , a collisional turbulence control parameter, and inversely with k _RBM ² q _cyl , the product of the square of the characteristic RBM turbulence wavenumber and the cylindrical safety factor, is shown to improve the prediction for EDA H-modes, finding good model agreement up to n _e ^ped = 3.0×10 ²⁰ m ^-3 . For comparison, EPED scans in n _e ^ped are then performed at three values of n _e ^sep /n _e ^ped . Increasing this ratio moves the peeling-ballooning branch transition to lower n _e ^ped , increasing n ^ped in the peeling branch and decreasing it in the ballooning branch. Agreement is found for large ELM H-modes. SPARC pedestal density predictions for an ELMy and an EDA/QCE-like H-mode are performed using the extension to the standalone Saarelma-Connor model and are found consistent with earlier assumptions used in EPED modeling. Inclusion of D _RBM significantly weakens the density gradient near the separatrix, lowering n _e ^ped by approximately 20%.

A direct quantitative comparison of scrape-off layer (SOL) filament properties obtained from fluid turbulence simulations with the GBS code and from experiments on the Tokamak à configuration variable (TCV) tokamak is performed within the TCV-X21 validation case. This comparison is made possible by extending the open TCV-X21 dataset with 2D turbulence measurements obtained with gas puff imaging (GPI), providing critical information on the size, velocity, and other key characteristics of turbulent filaments at the outboard midplane and in the divertor region. For the comparison, GBS simulations of TCV-X21 are analyzed using a dedicated synthetic GPI diagnostic that models the neutral helium-plasma interaction and emission processes and accounts for line-integration effects. Poloidal and radial filament velocities are found to be in good agreement between simulations and experiments, while the simulations overestimate the filament radial and poloidal sizes. The simulations further indicate that filaments in the SOL are predominantly represented by density perturbations rather than temperature perturbations, consistent with previous assumptions in experimental analyses of cross-field turbulent transport from GPI data. The direction of the poloidal velocity of filaments in this scenario is found to agree with the time-averaged E × B direction at the outboard midplane and X -point region, but not in the divertor leg. Possible explanations are proposed and discussed, highlighting the influence of the instantaneous E × B velocity components in both poloidal and radial directions. This study provides new insights into turbulent filament behavior and contributes to guiding future efforts to improve first-principles simulations of the boundary plasma.

In this paper, an overview of the impurity transport for three H-mode plasmas in the upcoming SPARC tokamak has been provided. The simulations have been performed within the ASTRA+STRAHL framework, using FACIT and TGLF-SAT2 to predict, respectively, neoclassical and turbulent core transport. A neural network trained on EPED simulations has been employed to calculate the pedestal height and width self-consistently. A benchmark with previous simulations at constant impurity fraction has been provided for three H-modes, spanning different plasma current and magnetic field values. Turbulent impurity transport has been found to systematically dominate over the neoclassical contribution. A sufficient on-axis accumulation of the ICRH minority species has been computed, ensuring efficient plasma heating. For one scenario, additional simulations have been performed to account for uncertainties in the modeling assumptions. The predictions are nearly insensitive to changes in the top of pedestal W concentrations. Varying the Ar pedestal concentration has shown a small effect on the impurity peaking and nearly constant fusion gain values, due to multiple effects on pedestal pressure, main ion dilution and density peaking. The inclusion of rotation in ASTRA simulations has shown minimal impact on confinement and impurity transport predictions. An exploratory study has been provided with a first set of simulations treating D and T separately, indicating a maximum fusion power at 55%–45% DT fuel composition, and an asymmetric distribution with respect to the D concentration. All the results, including sensitivity scans of toroidal velocity and ion temperature and density gradients, highlight that turbulent impurity transport prevails on the neoclassical component, aligning with previous ITER predictions, and suggesting that next generation devices like SPARC, operating at low collisionality, will experience low W accumulation.

Understanding and accounting for uncertainty is one aspect of ensuring next-step tokamaks such as SPARC will robustly achieve their goals. While traditional Plasma OPerating CONtour (POPCON) analyses guide design, they often overlook the significant impact of uncertainties in scaling laws, plasma profiles, and impurity concentrations on performance predictions. This work confronts these challenges by introducing statistical POPCONs, which leverage Monte Carlo analysis to quantify the sensitivity of SPARC’s operating points (Creely et al 2020 J. Plasma Phys. 86 5) to these crucial variables. For profiles, a physically motivated gradient-based functional form is introduced. We further develop a multi-fidelity Bayesian optimization workflow that effectively identifies operating points maximizing the probability of meeting performance goals, which gives a significant speed-up over brute force search methods. Our findings reveal that accounting for these uncertainties leads to an optimal operating point different from deterministic predictions, which balances H-mode access, confinement, impurity dilution, and auxiliary power.