arXiv subjects

Leonhard A. Leppin

Publications and source records attributed to Leonhard A. Leppin.

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↗

arXiv2026

Microtearing Thresholds and Second-Stable Ballooning in the DIII-D Pedestal: Reduced Modeling and Core-Edge Implications

Global and local linear gyrokinetic simulations of 42 pedestal equilibria from three DIII-D discharges are used to investigate pedestal stability and its impact on pedestal structure and confinement. Microtearing modes (MTMs) and kinetic ballooning modes (KBMs) represent the main ion scale instabilities. For all three discharges, MTMs lie near a stability boundary in the mid-pedestal and exhibit threshold behavior, with growth rates increasing at and beyond pre-ELM pressure gradients. Pedestal MTMs retain conventional signatures but also show enhanced particle transport and partial density-gradient drive, indicating they can constrain pedestal {\it pressure} rather than electron temperature alone. KBMs are typically second-stable in this region due to low magnetic shear and large pressure gradients, though they can become active near the pedestal foot where magnetic shear is higher. These findings suggest MTMs play the role of inter-ELM pressure limit in the mid-pedestal when KBM is second stable. A preliminary quasilinear mixing-length transport model, with properly tuned free parameters, reproduces experimental temperature and density profiles when coupled to ASTRA. When applied to a case with doubled separatrix density, the model predicts reduced pedestal pressure consistent with ITPA H-mode confinement trends, attributable to increased MTM and ETG transport. These results clarify pedestal-limiting mechanisms and establish a physics-based link between separatrix conditions, pedestal structure, and global confinement. This work lays the foundation for new predictive modeling capabilities for core-edge integration in burning plasma regimes.

physics.plasm-ph↗

arXiv2020

Capturing Velocity Gradients and Particle Rotation Rates in Turbulence

Turbulent fluid flows exhibit a complex small-scale structure with frequently occurring extreme velocity gradients. Particles probing such swirling and straining regions respond with an intricate shape-dependent orientational dynamics, which sensitively depends on the particle history. Here, we systematically develop a reduced-order model for the small-scale dynamics of turbulence, which captures the velocity gradient statistics along particle paths. An analysis of the resulting stochastic dynamical system allows pinpointing the emergence of non-Gaussian statistics and non-trivial temporal correlations of vorticity and strain, as previously reported from experiments and simulations. Based on these insights, we use our model to predict the orientational statistics of anisotropic particles in turbulence, enabling a host of modeling applications for complex particulate flows.

physics.flu-dyn↗