Engineering topics

Smith, S. P. (ORCID:000000031526380X)

Publications and source records attributed to Smith, S. P. (ORCID:000000031526380X).

3 records

DOE OSTI2024

Thinking Bayesian for plasma physicists

Bayesian statistics offers a powerful technique for plasma physicists to infer knowledge from the heterogeneous data types encountered. To explain this power, a simple example, Gaussian Process Regression, and the application of Bayesian statistics to inverse problems are explained. The likelihood is the key distribution because it contains the data model, or theoretic predictions, of the desired quantities. By using prior knowledge, the distribution of the inferred quantities of interest based on the data given can be inferred. Because it is a distribution of inferred quantities given the data and not a single prediction, uncertainty quantification is a natural consequence of Bayesian statistics. The benefits of machine learning in developing surrogate models for solving inverse problems are discussed, as well as progress in quantitatively understanding the errors that such a model introduces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

On the origin of the DIII-D L-H power threshold isotope effect

Abstract The increased low to high confinement mode (L to H-mode) power threshold P L H in DIII-D low collisionality hydrogen plasmas (compared to deuterium) is shown to result from lower impurity (carbon) content, consistent with reduced (mass-dependent) physical and chemical sputtering of graphite. Trapped gyro-Landau fluid (TGLF) quasilinear calculations and local non-linear gyrokinetic CGYRO simulations confirm stabilization of ion temperature gradient (ITG) driven turbulence by increased carbon ion dilution as the most important isotope effect. In the plasma edge, electron non-adiabaticity is also predicted to contribute to the isotope dependence of thermal transport and P L H , however its effect is subdominant compared to changes from impurity isotopic behavior. This L-H power threshold reduction with increasing carbon content at low collisionality is in stark contrast to high collisionality results, where additional impurity content appears to increase the power necessary for H-mode access.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Flexible, integrated modeling of tokamak stability, transport, equilibrium, and pedestal physics

The STEP (Stability, Transport, Equilibrium, and Pedestal) integrated-modeling tool has been developed in OMFIT to predict stable, tokamak equilibria self-consistently with core-transport and pedestal calculations. STEP couples theory-based codes to integrate a variety of physics, including magnetohydrodynamic stability, transport, equilibrium, pedestal formation, and current-drive, heating, and fueling. The input/output of each code is interfaced with a centralized ITER-Integrated Modelling & Analysis Suite data structure, allowing codes to be run in any order and enabling open-loop, feedback, and optimization workflows. This paradigm simplifies the integration of new codes, making STEP highly extensible. STEP has been verified against a published benchmark of six different integrated models. Core-pedestal calculations with STEP have been successfully validated against individual DIII-D H-mode discharges and across more than 500 discharges of the H98,y2 database, with a mean error in confinement time from experiment less than 19%. STEP has also reproduced results in less conventional DIII-D scenarios, including negative-central-shear and negative-triangularity plasmas. Predictive STEP modeling has been used to assess performance in several tokamak reactors. Simulations of a high-field, large-aspect-ratio reactor show significantly lower fusion power than predicted by a zero-dimensional study, demonstrating the limitations of scaling-law extrapolations. STEP predictions have found promising scenarios for an EXhaust and Confinement Integration Tokamak Experiment, including a high-pressure, 80%-bootstrap-fraction plasma. ITER modeling with STEP has shown that pellet fueling enhances fusion gain in both the baseline and advanced-inductive scenarios. Finally, STEP predictions for the SPARC baseline scenario are in good agreement with published results from the physics basis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗