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Results for “emergent rotational phenomena”

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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5 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Packing and flow particle simulations

Granular material is present across natural and industrial processes on Earth and other planets. Granular particles show up in space exploration (lunar regolith), avalanches (boulders), food (coffee), construction (concrete powder) and manufacturing (additive manufacturing powder, battery slurries). Important phenomena emerge from large collections of granular particles. The size scales of the particles in granular material, 10 μm diameter or larger, makes particle-based simulations a tractable computational method. This seminar will present the packing and flow of granular matter using particle-based discrete element modeling simulations. Particles modeled with rotational friction only require as few as 2.6 contacts for mechanical stability, as opposed to 6 contacts for frictionless particles. Optimal parameters for in-space manufacturing particulate material are identified. Specifically, the maximum density and contacts occurs for a large-to-small particle volume ratio of 0.265. Stress and contact fabric fluctuations of flowing dry granular matter have power-law scaling with strain rate, and a kink. The pressure-dependent slope change kink could identify the transition between slower, quasistatic and faster, inertial flows.

granular↗
NASA NTRSDate not supplied

Packing and flow particle simulations

Granular material is present across natural and industrial processes on Earth and other planets. Granular particles show up in space exploration (lunar regolith), avalanches (boulders), food (coffee), construction (concrete powder) and manufacturing (additive manufacturing powder, battery slurries). Important phenomena emerge from large collections of granular particles. The size scales of the particles in granular material, 10 μm diameter or larger, makes particle-based simulations a tractable computational method. This seminar will present the packing and flow of granular matter using particle-based discrete element modeling simulations. Particles modeled with rotational friction only require as few as 2.6 contacts for mechanical stability, as opposed to 6 contacts for frictionless particles. Optimal parameters for in-space manufacturing particulate material are identified. Specifically, the maximum density and contacts occurs for a large-to-small particle volume ratio of 0.265. Stress and contact fabric fluctuations of flowing dry granular matter have power-law scaling with strain rate, and a kink. The pressure-dependent slope change kink could identify the transition between slower, quasistatic and faster, inertial flows.

granular↗
NASA NTRS1989

Boundary value problems in magnetohydrodynamics (and fluid dynamics). I - Radiation boundary condition

In view of the difficulties that emerge in numerical simulations of time-dependent phenomena involving MHD waves due to waves' artificial reflection at numerical boundaries, where time-dependent magnetic fields outside those boundaries are unknown, a method previously developed for the determination of radiative boundary conditions is generalized for the treatment of isothermal MHD waves. The illustrative problem thus treated is that of the magnetic braking of a rigidly rotating disk which is embedded in a differentially-rotating fluid. The analytic results obtained are compared with those from numerical simulations with and without the present boundary treatment.

Vanajakshi, T. C.↗
NASA NTRS1979

Global magnetohydrodynamic simulation of the two-dimensional magnetosphere

The time-dependent magnetohydrodynamic interaction of the solar wind with a two-dimensional dipole magnetic field has been simulated using a novel Lagrangian particle type of MHD code that can treat local low density or vacuum regions without numerical instability. This enables one to simulate the time-dependent magnetic tail. When the solar wind field is southward, a magnetic field line topology consistent with Dungey's model emerges in steady state. The tail, however, is short, and the x-points are only slightly shifted from their vacuum locations, because of strong numerical resistivity. Different configurations resulting from different relative orientations of the solar wind magnetic field and dipole axis are also presented. While the magnetic field is relatively steady, the density and flow in the magnetosheath are turbulent, as are the bow shock and magnetopause; the Kelvin-Helmholtz instability may account for these phenomena. We also model a 'substorm' as the passage of a rotational discontinuity in the solar wind over the dipole. Both 90 and 180 deg shifts to a southward solar wind field cause a violent readjustment of the magnetic tail which eventually settles down to the Dungey configuration.

Leboeuf, J. N.↗
NASA NTRSDate not supplied

Exploring the Capabilities of a Machine Learning Algorithm to Detect Space Weather-Significant Emerging Active Regions

Active regions are a source of various phenomena responsible for Space Weather disturbances; therefore, developing a technology for early warning about upcoming magnetic activity is crucial to mitigate its impact. However, observational limitations and the high nonlinearity of processes associated with the accumulation of magnetic flux and its interaction with the surrounding plasma during the emergence through the convection zone make early activity detection a challenging problem. To address these challenges, we developed a physics-driven machine learning model that allows us to detect active regions (ARs) before they become visible on the solar surface by analyzing the power spectra of acoustic oscillations observed by the SDO/HMI instrument. This study is based on a time series of Doppler shift maps of 31x31-degree areas tracked with the Carrington rotation rate for four days before and after the emergence. The Doppler shift time series are processed into the oscillation power maps for four frequency ranges and accompanied by line-of-sight magnetograms and the continuum intensity maps from SDO/HMI. The resulting data are converted into a 1D time series representing the mean temporal variations of these quantities. The redacted time series are used as input to predict AR emergence using the Long Short Term Memory (LSTM) method. The training of the LSTM model is based on 40 ARs, which includes an independent analysis for each sub region that exhibits AR emergence or remains quiet. The emergence of magnetic flux (defined as a decrease of the continuum intensity) was detected with the developed LSTM algorithm from 5 to 48 hours before the reported time by NOAA. The developed model is capable of pointing to the time and location of active region formation. In this presentation, we discuss reasons that impact how early in advance the model can identify the upcoming activity and the possibility of improving the current predictive skills and steps to transition to the operational forecast.

Heliophysics↗