Engineering topics

Heinonen, R. A.

Publications and source records attributed to Heinonen, R. A..

5 records

DOE OSTI2023

Generation of momentum transport in weakly turbulent β -plane magnetohydrodynamics

Magnetohydrodynamic turbulence on a β plane with an in-plane mean field, a system which serves as a simple model for the solar tachocline, is investigated analytically and computationally. We first derive two useful analytic constraints: We express the mean turbulent cross-helicity in terms of the mean turbulent magnetic energy, and then show that (for weak turbulence) the time-averaged momentum transport in the system can be expressed in terms of the cross-helicity spectrum. Here, we then complete a closure of the system using weak turbulence theory, appropriately extended to a system with multiple interacting eigenmodes. We use this closure to perturbatively solve for the spectra at lowest order in the Rossby parameter β and thereby show that the momentum transport in the system is O ⁡(β 2 ), thus quantifying the transition away from Alfvénized turbulence. Finally, we verify our theoretical results by performing direct numerical simulations of the system over a broad range of β.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2022

Magnetic ground states of a model for M Nb 3 S 6 ( M = Co, Fe, Ni)

The transition-metal-intercalated dichalcogenide CoNb 3 S 6 is a triangular antiferromagnet (AFM) that has recently been shown to exhibit a large anomalous Hall effect (AHE) below the Neel temperature, even though the response to an external field is very small. This suggests that there is an interesting magnetic structure that interacts with the electronic structure to yield the AHE, as collinear AFMs cannot exhibit a nonzero AHE. We propose a model for magnetic transition-metal-intercalated dichalcogenides and examine its ground state as a function of interaction parameters. The model exhibits transitions between planar spin spirals, nonplanar spin spirals, and a particular noncoplanar so-called 3q state. Finally, this latter state must exhibit a nonzero AHE, while the spin spirals do not.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Learning how structures form in drift-wave turbulence

Drift-wave turbulence produces anomalous transport via cross-correlations between fluctuations. This transport has profound implications for confinement, structure formation, and virtually all aspects of the non-linear turbulent dynamics. Herein, we use a data-driven method based on deep learning in order to study turbulent transport in the 2D Hasegawa–Wakatani system and infer a reduced mean-field model from numerical solution. In addition to the usual turbulent diffusion, we find an effect which couples the particle flux to the local gradient of vorticity, which tends to modulate the density profile. The direct coupling to the shear is relatively weak. In addition, the deep learning method finds a model for spontaneous zonal flow generation by negative viscosity, stabilized by non-linear and hyperviscous terms. We compare these results to analytic calculations using quasilinear theory and wave kinetics, finding qualitative agreement, though the calculations miss certain higher-order effects. A simplified, 1-D model for the evolution of the profile, flow, and intensity based on the deep learning results is solved numerically and compared to previous models for staircasing based on bistability. We see that the physics uncovered by the deep learning method provided simple explanations for the formation of zonal structures in the density, flow, and turbulence fields. We highlight the important role of symmetry in the deep learning method and speculate on the portability of the method to other applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Diffusion coefficients in the envelopes of white dwarfs

The diffusion of elements is a key process in understanding the unusual surface composition of white dwarfs and their spectral evolution. The diffusion coefficients of Paquette et al. have been widely used to model diffusion in white dwarfs. In this work, we perform new calculations of the coefficients of interdiffusion and ionic thermal diffusion with (1) a more advanced model that uses a recent modification of the calculation of the collision integrals that is more suitable for the partially ionized, partially degenerate, and moderately coupled plasma and (2) classical molecular dynamics. The coefficients are evaluated for silicon and calcium in white dwarf envelopes of hydrogen and helium. A comparison of our results with Paquette et al. shows that the latter systematically underestimates the coefficient of interdiffusion yet provides reliable estimates for the relatively weakly coupled plasmas found in nearly all types of stars, as well as in white dwarfs with hydrogen envelopes. In white dwarfs with cool helium envelopes (${T}_{\mathrm{eff}}$ < 15,000 K), the difference grows to more than a factor of two. We also explored the effect of the ionization model used to determine the charges of the ions and found that it can be a substantial source of discrepancy between different calculations. Finally, we consider the relative diffusion timescales of Si and Ca in the context of the pollution of white dwarf photospheres by accreted planetesimals and find factor of ≳3 differences between calculations based on Paquette et al. and our model.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Turbulence model reduction by deep learning

A defining problem of turbulence theory is to produce a predictive model for turbulent fluxes. These have profound implications for virtually all aspects of the turbulence dynamics. In magnetic confinement devices, drift-wave turbulence produces anomalous fluxes via cross-correlations between fluctuations. In this work, we introduce an alternative, data-driven method for parametrizing these fluxes. The method uses deep supervised learning to infer a reduced mean-field model from a set of numerical simulations. We apply the method to a simple drift-wave turbulence system and find a significant new effect which couples the particle flux to the local gradient of vorticity. Notably, here, this effect is much stronger than the oft-invoked shear suppression effect. We also recover the result via a simple calculation. The vorticity gradient effect tends to modulate the density profile. In addition, our method recovers a model for spontaneous zonal flow generation by negative viscosity, stabilized by nonlinear and hyperviscous terms. We highlight the important role of symmetry to implementation of the new method.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗