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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Nonlinear magnetohydrodynamic modeling of ideal ballooning modes in high- β Wendelstein 7-X plasmas

We present nonlinear magnetohydrodynamic (MHD) simulations of high- β Wendelstein 7-X plasmas using the stellarator extension of the M3D- C 1 code, building on the recent work that shows benign saturation of ideal ballooning modes above the designed β limit in the standard configuration [Zhou et al., Phys. Rev. Lett. 133, 135102 (2024)]. First, we examine the results' sensitivity to the parallel thermal conductivity. It is found that while an increased parallel conductivity reduces the linear growth rate, the saturated pressure profile is barely affected. Second, we consider the dependence on the profile shape. It is shown that an equilibrium with a peaked pressure profile and lower β is subject to more significant change than a broad profile with higher β and a larger growth rate, suggesting that benign saturation, or nonlinear stability, is not guaranteed and not dictated by linear growth. Third, we study the influence of the magnetic configuration, with the equilibrium rotational transform varied by adjusting the planar coil current. With similar growth rates, similar magnitudes of profile change are found regardless of the presence of a low-order resonance, which implies that the saturation mechanism is not specific to a resonant or non-resonant mode. These results indicate that MHD stability should still be treated seriously in stellarator operation and design, for which nonlinear modeling using tools like M3D- C 1 can play an instrumental role.

Zhou, Yao [Shanghai Jiao Tong University (China)] ↗
DOE OSTI2026

Expansion-driven Weibel instability in magnetohydrodynamics: Linear theory for static systems

The Weibel dispersion relation is obtained in the magnetohydrodynamic (MHD) approximation by including a tensor expression for temperature. MHD gives an upper cutoff wavenumber for Weibel growth identical to kinetic theory if the electron drift velocity is included in the evolution of the electron temperature. MHD overestimates growth rates compared to kinetic theory and gives maximum growth at larger wavenumbers, but it only leads to divergent results as temperature anisotropy tends to infinity. Thermal conduction in MHD lowers the growth rates and shifts maximum growth to smaller wavenumbers, but flux-limited or nonlocal thermal conduction is found to significantly limit these effects. The results are used as a first step in evaluating the potential of MHD to simulate expansion-driven Weibel instability, which occurs due to the temperature tensor only cooling in the direction of expansion. Finally, the small temperature anisotropy found in expansion-driven Weibel instability means that MHD could be an adequate model because growth rates are much less than the electron plasma frequency, and wavelengths are much greater than the Debye length.

Davies, J. R. [Univ. of Rochester, NY (United Stat↗
DOE OSTI2025

Numerical investigation of two-dimensional buoyancy-driven eddies in liquid metal magnetohydrodynamic flows in breeding blankets *

Abstract Lead–lithium flows are key features in the design of tokamak breeding blanket concepts such as the dual-coolant lead–lithium (DCLL). Since they flow under magnetic fields, they are affected by magnetohydrodynamic (MHD) effects. The neutron flux originating in the tokamak plasma heats the breeding blanket channels in a non-uniform manner, inducing buoyancy forces in the liquid metal. Buoyancy may become a source of quasi-two-dimensional (Q2D) turbulence, and the appearance of eddies may affect the transport of heat and tritium across the blanket. Blankets characterized by high-speed liquid metal flows (such as DCLL) will need ceramic insulating walls to reduce the MHD-related pressure drop in the channels. In our simulations, we have used the Q2D model proposed by Sommeria and Moreau (SM82) which is especially suitable for modeling electrically insulating channel flows. On top of that, we have modelled buoyancy forces in the momentum equation using the Oberbeck–Boussinesq approximation. In this work, we include a validation of the implemented Q2D model in buoyancy-driven cases and identify a thermohydraulic configuration that promotes the generation of eddies and the accumulation of tritium. We also show the results provided by our post-processing tool based on the bi-dimensional fast Fourier transform for eddy detection and characterization. We complete our investigation by performing an initial assessment of how eddies can accumulate tritium in the breeding blanket. We conclude by discussing the relevance of preventing accumulation of tritium within the blanket and suggest a possible solution.

Suarez, Daniel (ORCID:0000000251740100)↗
DOE OSTI2025

Neural network-based classification and regression of magnetohydrodynamic modes in tokamaks

We present a machine learning-based magnetohydrodynamic (MHD) classifier and regressor that utilizes real or complex-valued 3D magnetic sensor array data to determine neoclassical tearing mode (NTM) onset times in tokamaks with millisecond accuracy. The input dataset consists of poloidal profiles of complex Fourier amplitudes with an n = 1 toroidal mode number from 144 human-labeled ITER Baseline Scenario discharges in the DIII-D tokamak, spanning both tearing-dominated and sawtooth-dominated regimes. Since m, n = 2,1 NTMs frequently emerge alongside sawteeth at the same frequency in this scenario, the focus is on isolating the m = 1 and m = 2 components of the n = 1 MHD mode near the tearing onset. To improve model regularization and prediction stability, singular value decomposition was applied to balance the sawtooth and tearing datasets. The enriched datasets facilitated training neural networks that learn the key distinguishing features of sawtooth and tearing modes in the poloidal profiles of their magnetic amplitude and phase. When the modes occur independently, the networks achieve perfect classification due to the modes’ distinct characteristics and low measurement noise. In the more experimentally relevant case where both modes coexist, the networks maintain exceptional performance across key metrics. Tests on synthetic data with known ground truth demonstrate the superior accuracy of the neural network trained on complex-valued input compared to models using real amplitude, phase, or pseudo-complex data, achieving both a mean time delay and standard deviation below 1 ms. Notably, standard linear regression methods fitting the dominant singular modes to the data closely match the neural network’s performance. Applying these methods across a broad range of H-mode scenarios will enable future studies to systematically identify dominant NTM triggers as scenario-specific variables, paving the way for more effective tearing mode avoidance strategies in future fusion reactor designs.

machine learning↗
DOE OSTI2024

Structure Formation Through Magnetohydrodynamical Instabilities in Primordial Disks

The shear flow instabilities under the presence of magnetic fields in the primordial disk can greatly facilitate the formation of density structures that serve as seeds prior to the onset of the gravitational Jeans instability. We evaluate the effects of the Parker, magnetorotational and kinematic dynamo instabilities by comparing the properties of these instabilities. We calculate the mass spectra of coagulated density structures by the above mechanism in the radial direction for an axisymmetric magnetohydrodynamic (MHD) torus equilibrium and power density profile models. Our local three-dimensional MHD simulation indicates that the coupling of the Parker and magnetorotational instability creates spiral arms and gas blobs in an accretion disk, reinforcing the theory and model. Such a mechanism for the early structure formation may be tested in a laboratory. The recent progress in experiments involving shear flows in rotating tokamak, field reversed configuration (FRC) and laser plasmas may become a key element to advance in nonlinear studies.

Noguchi, Koichi↗
DOE OSTI2025

Magnetically Driven Neutron-rich Ejecta Unleashed: Global 3D Neutrino–General Relativistic Magnetohydrodynamic Simulations of Collapsars Probe the Conditions for r -process Nucleosynthesis

Abstract Collapsars—rapidly rotating stellar cores that form black holes—can power gamma-ray bursts and are proposed to be key contributors to the production of heavy elements in the Universe via the rapid neutron capture process ( r -process). Previous neutrino-transport collapsar simulations have been unable to unbind neutron-rich material from the disk. However, these simulations have not included sufficiently strong magnetic fields and the black hole (BH), both of which are essential for launching mass outflows. We present ν h-amr , a novel neutrino-transport general relativistic magnetohydrodynamic ( ν GRMHD) code, which we use to perform the first 3D global ν GRMHD collapsar simulations. We find a self-consistent formation of a weakly magnetized dense accretion disk, which has sufficient time to neutronize. Eventually, substantial magnetic flux accumulates near the BH, becomes dynamically important, leads to a magnetically arrested disk (MAD), and unbinds some of the neutron-rich material. However, the strong flux also hinders accretion, lowers density, and increases neutrino-cooling timescale, which prevents further disk neutronization. Typical collapsar progenitors with mass accretion rates, M ̇ ∼ 0.1 − 1 M ⊙ s - 1 , do not produce significant neutron-rich ( Y e < 0.25) ejecta. However, we find that MADs at higher mass accretion rates, M ̇ ≳ few M ⊙ s - 1 (e.g., for more centrally concentrated progenitors), can unbind M ej ≲ M ⊙ of neutron-rich ejecta. The outflows inflate a shocked cocoon that mixes with the infalling neutron-poor stellar gas and raises the final outflow Y e ; however, the final r -process yield may be determined earlier at the point of neutron capture freeze-out. Future work will explore under what conditions more typical collapsar engines become r -process factories.

Issa, Danat (ORCID:0009000524787631)↗
DOE OSTI2025

Self-similar Cosmic-Ray Transport in High-resolution Magnetohydrodynamic Turbulence

We study the propagation of cosmic rays (CRs) through a simulation of magnetohydrodynamic (MHD) turbulence at an unprecedented resolution of 10,240 3 . We drive turbulence that is subsonic and super-Alfvénic, characterized by δB rms /B 0 = 2. The high resolution enables an extended inertial range such that the Alfvén scale l A , where δB(l A ) ≈ B 0 , is well resolved. This allows us to properly capture how the cascade transitions from large amplitudes on large scales to small amplitudes on small scales. We find that sharp bends in the magnetic field are key mediators of particle transport even on small scales via resonant curvature scattering. We further find that particle scattering in the turbulence shows strong hints of self-similarity: (1) the diffusion has a weak energy dependence over almost two decades in particle energy, and (2) the particles’ random walk exhibits a broad power-law distribution of collision times such that the diffusion is dominated by the rarest, long-distance excursions. Our results suggest that large-amplitude MHD turbulence can provide efficient scattering over a wide range of CR energies and may help explain many CR observations above a ∼TeV: the flattening of the B/C spectrum, the hardening of CR primary spectra, and the weak dependence of arrival anisotropy on CR energy.

Kempski, Philipp [Princeton Univ., NJ (United Stat↗
NASA NTRS1968

Study of convective magnetohydrodynamic channel flow

Study involves the effects of the interactions of electromagnetic, velocity, and temperature fields to aid in the design of a magnetohydrodynamic device. It concerns a theoretical analysis of the convective flow of an electrically conducting gas in a channel composed of conducting walls.

Singer, R. M.↗
NASA NTRS1969

Magnetohydrodynamic generators using two-phase liquid-metal flows

Two-phase flow generator cycle of a magnetohydrodynamic /MHD/ generator uses a working fluid which is compressible and treated as an expanding gas. The two-phase mixture passes from the heat source through the MHD generator, where the expansion process takes place and the electrical energy is extracted.

Petrick, M.↗
NASA NTRS1969

Studies of cycles for liquid-metal magnetohydrodynamic generation of power

Studies of liquid-metal magnetohydrodynamic power cycles indicate that the overall efficiency of a binary cycle, employing a liquid-metal topping cycle and a bottoming steam cycle, may reach 60 percent. Details of analyses and data on cycles are presented, and the commercial potential of the binary cycle is discussed.

Lee, K.↗
NASA NTRS1969

Channel-wall limitations in the magnetohydrodynamic induction generator

Discussion of magnetohydrodynamic induction generator examines the machine in detail and materials problems influencing its design. The higher upper-temperature limit of the MHD system promises to be more efficient than present turbine systems for generating electricity.

Jackson, W. D.↗