arXiv subjects

Chris Holland

Publications and source records attributed to Chris Holland.

3 recordsLinked to original sources

arXiv2026

MGKDB: An IMAS-aligned multicode gyrokinetic simulation database for reproducible fusion turbulence modeling and data-driven analysis

Expensive fusion simulations are commonly preserved in code-specific formats that limit discovery, comparison, and reuse. We present the Multiscale GyroKinetic DataBase (MGKDB), an open-source software framework and curated archive that converts heterogeneous simulation campaigns into traceable scientific records. Each record links code-native inputs and outputs to provenance and quality metadata, an IMAS-aligned physics representation, and derived diagnostics, preserving model-specific evidence while enabling common-field queries. Production pathways support linear and nonlinear GENE and CGYRO calculations and reduced quasilinear TGLF evaluations. At the September 1, 2026 snapshot, MGKDB contained 1,068,089 records, nearly all of which included a populated gyrokinetics IMAS branch. The software is openly available, while access to the NERSC-hosted production records is managed. Three demonstrations show how these linked representations support scientific reuse. Standardized quantities stored in the Diagnostics branch enable population-scale analysis of archived linear modes; common input coordinates reveal coverage, redundancy, and campaign-driven sampling structure across a multicode collection; and record-level retrieval of native CGYRO inputs drives matched TGLF calculations and produces a traceable dataset for exploratory surrogate modeling. Together, these examples demonstrate how MGKDB supports archive characterization, candidate cross-code and cross-fidelity comparisons, campaign planning, and reproducible data-driven modeling without treating different models as automatically equivalent.

physics.plasm-ph↗

arXiv2020

The Dependence of the Impurity Transport on the Dominant Turbulent Regime in ELM-y H-mode Discharges

Laser blow-off injections of aluminum and tungsten have been performed on the DIII-D tokamak to investigate the variation of impurity transport in a set of dedicated ion and electron heating scans with a fixed value of the external torque. The particle transport is quantified via the Bayesian inference method, which, constrained by a combination of a charge exchange recombination spectroscopy, soft X-ray measurements, and VUV spectroscopy provides a detailed uncertainty quantification of the transport coefficients. Contrasting discharge phases with a dominant electron and ion heating reveal a factor of 30 increase in midradius impurity diffusion and a 3-fold drop in the impurity confinement time when additional electron heating is applied. Further, the calculated stationary aluminum density profiles reverse from peaked in electron heated to hollow in the ion heated case, following a similar trend as electron and carbon density profiles. Comparable values of a core diffusion have been observed for W and Al ions, while differences in the propagation dynamics of these impurities are attributed to pedestal and edge transport. Modeling of the core transport with non-linear gyrokinetics code CGYRO [J. Candy and E. Belly J. Comput. Phys. 324,73 (2016)], significantly underpredicts the magnitude of the variation in Al transport. The experiment demonstrates a 3-times steeper increase of impurity diffusion with additional electron heat flux and 10-times lower diffusion in ion heated case than predicted by the modeling. However, the CGYRO model correctly predicts that the Al diffusion dramatically increases below the linear threshold for the transition from the ion temperature gradient (ITG) to trapped electron mode (TEM).

physics.plasm-ph↗

arXiv2019

Quantifying the Temporal Uncertainties of Nonlinear Turbulence Simulations

Nonlinear initial value turbulence simulations often exhibit large temporal variations in their dynamics. Quantifying the temporal uncertainty of turbulence simulation outputs is an important component of validating the simulation results against the experimental measurements, as well as for code-code comparisons. This paper assesses different methods of uncertainty quantification of temporally varying simulated quantities previously used within plasma turbulence community, to evaluate their strengths and potential pitfalls. The use of Autoregressive Moving-Average (ARMA) models for forecasting the uncertainty of turbulence quantities at later simulation times is also studied. These discussions are framed in the practical context of calculating the time-averaging uncertainties of turbulent energy fluxes calculated via gyrokinetic simulations. Particular attention is paid to how standard approaches are challenged as the driving gradient is reduced to the critical value for instability onset.

physics.plasm-ph↗