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Results for “heliospheric and magnetospheric physics”

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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The SpacePy space science package at 12 years

For over a decade, the SpacePy project has contributed open-source solutions for the production and analysis of heliophysics data and simulation results. Here we introduce SpacePy’s functionality for the scientific user and present relevant design principles. We examine recent advances and the future of SpacePy in the broader scientific Python ecosystem, concluding with some of the work that has used SpacePy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Data-Driven Specification of Earth's Magnetic Field

As our society is increasingly dependent on technologies in space, predicting space weather becomes ever more important. We have come to rely on technologies such as cellphones, GPS, the Internet, and other commercial and military assets. In order to protect these systems a high priority is to develop better understanding of the harmful conditions of space weather encountered in the near-Earth radiation environment which are mostly dictated by the dynamics of energetic charged particles. The main objective of our proposal was to improve the specification and forecast of the particle distribution in the Earth’s inner magnetosphere using data assimilation together with machine learning (ML) algorithms in our ring current-atmosphere interactions model with self-consistent magnetic and electric fields (RAM-SCBE). Specifically, we explored the application of machine learning algorithms to emulate and improve, through infusion of observational data, the magnetic field (SCBE) of our ring current model. Our work advanced towards the characterization of the RAM-SCBE particle flux field and its potentially different simulation scenarios. We explored how the model behaves in a number of simulation scenarios in order to better understand how the model reacts to perturbations in the solar wind. We were able to capture this behavior through the simulation of an ensemble of RAM-SCB model solutions. The ensemble showed the important correlations between the particle fluxes and the magnetic field. We were able to start the training of a neural network (Autoencoder) to identify the dominant features of the magnetic field, and the main correlations (linear and non-linear) between the particle fluxes and the magnetic field. Our next steps consists of training a neural network to capture the time evolution of the dominant features and obtain a consistent surrogate model for the RAM-SCB.

42 ENGINEERING↗
DOE OSTI2024

Anti-symmetric and positivity preserving formulation of a spectral method for Vlasov-Poisson equations

We analyze the anti-symmetric properties of a spectral discretization for the one-dimensional Vlasov-Poisson equations. The discretization is based on a spectral expansion in velocity with the symmetrically weighted Hermite basis functions, central finite differencing in space, and an implicit Runge Kutta integrator in time. The proposed discretization preserves the anti-symmetric structure of the advection operator in the Vlasov equation, resulting in a stable numerical method. We apply such discretization to two formulations: the canonical Vlasov-Poisson equations and their continuously transformed square-root representation. The latter preserves the positivity of the particle distribution function. We derive analytically the conservation properties of both formulations, including particle number, momentum, and energy, which are verified numerically on the following benchmark problems: manufactured solution, linear and nonlinear Landau damping, two-stream instability, bump-on-tail instability, and ion-acoustic wave.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Prediction of the SYM-H Index Using a Bayesian Deep Learning Method With Uncertainty Quantification

We propose a novel deep learning framework, named SYMHnet, which employs a graph neural network and a bidirectional long short-term memory network to cooperatively learn patterns from solar wind and interplanetary magnetic field parameters for short-term forecasts of the SYM-H index based on 1- and 5-min resolution data. SYMHnet takes, as input, the time series of the parameters' values provided by NASA's Space Science Data Coordinated Archive and predicts, as output, the SYM-H index value at time point t + w hours for a given time point t where w is 1 or 2. By incorporating Bayesian inference into the learning framework, SYMHnet can quantify both aleatoric (data) uncertainty and epistemic (model) uncertainty when predicting future SYM-H indices. Experimental results show that SYMHnet works well at quiet time and storm time, for both 1- and 5-min resolution data. The results also show that SYMHnet generally performs better than related machine learning methods. For example, SYMHnet achieves a forecast skill score (FSS) of 0.343 compared to the FSS of 0.074 of a recent gradient boosting machine (GBM) method when predicting SYM-H indices (1 hr in advance) in a large storm (SYM-H = -393 nT) using 5-min resolution data. When predicting the SYM-H indices (2 hr in advance) in the large storm, SYMHnet achieves an FSS of 0.553 compared to the FSS of 0.087 of the GBM method. In addition, SYMHnet can provide results for both data and model uncertainty quantification, whereas the related methods cannot.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Simulating ‘Two Ribbon’ Type Solar Flares [Slides]

The underlying mechanism in solar flares in a process known as magnetic reconnection. This astrophysical process is when magnetic field lines, running anti-parallel, break and reconnect. The change in configuration of field lines results in an explosive release of energy as the leftover magnetic energy is converted to kinetic and thermal energies. In this project, we are using an astrophysical magnetohydrodynamic (MHD) simulation code known as Athena++ with a reconnection problem generator file created by Li et al. 2018. Our current research is to successfully implement a radiative cooling term into the MHD equations as it could have important physical effects on the plasma. We use Klimchuk et al. 2008 and SPEX_DM as our chosen cooling functions. The results from the SPEX_DM function show there is a condensation forming that we had predicted but had not seen before with our simulation code. We will continue to analyze the SPEX_DM function and potentially implement thermal conduction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Temperature of Suprathermal Electron Strahl at ACE as an Indicator of Solar Coronal Origin Temperature [Slides]

Determine the effectiveness of using electron strahl temperature to infer coronal source temperature. Suprathermal electron strahl temperature derived from measurements at 1 AU does retain information regarding the coronal source temperature from which it originates. This correlation is most strongly measured during the leading edges of coronal hole events but is generally also present in full event measurements. This correlation is also observed in CME events during a coronal hole.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Cold Plasma IC Report

This past year we completed the simulation campaign in support of our magnetospheric cold plasma research project. This project aimed to develop the next-generation particle instruments to measure the properties of the cold particle populations in the Earth’s magnetosphere.

58 GEOSCIENCES↗
DOE OSTI2024

Cold Plasma Measurements

We have continued the simulation campaign in support of our ongoing magnetospheric cold plasma research project. This project aims to develop the next-generation particle instruments to measure the properties of the cold particle populations in the Earth’s magnetosphere. For this purpose, simulations have been performed with a Particle-In-Cell (PIC) code called the Curvilinear PIC (CPIC). The code is formulated in curvilinear geometry and couples the standard PIC algorithm with algorithms for the generation and adaptation of the underlaying computational mesh. It conforms to complex objects like spacecraft and it can place more grid points in regions where higher resolution is needed. The code also features a scalable solver based on the multigrid algorithm and it is fully parallelized via domain decomposition and MPI.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Kinetic simulations verifying reconnection rates measured in the laboratory, spanning the ion-coupled to near electron-only regimes

The rate of reconnection characterizes how quickly flux and mass can move into and out of the reconnection region. In the Terrestrial Reconnection EXperiment (TREX), the rate at which the antiparallel asymmetric reconnection occurs is modulated by the presence of a shock and a region of flux pileup in the high-density inflow. Simulations utilizing a generalized Harris-sheet geometry have tentatively shown agreement with TREX's measured reconnection rate scaling relative to system size, which is indicative of the transition from ion-coupled toward electron-only reconnection. Here, in this study, we present simulations tailored to reproduce the specific TREX geometry, which confirm both the reconnection rate scale and the shock jump conditions previously characterized experimentally in TREX. The simulations also establish an interplay between the reconnection layer and the Alfvénic expansions of the background plasma associated with the energization of the TREX drive coils; this interplay has not yet been experimentally observed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Radiation Belt Remediation: A Complex Engineered System (RBR-ACES) (Institutional Computing Report)

We have performed the simulation campaigns in support of LDRD-DR project Radiation Belt Remediation: A Complex Engineered System (RBR-ACES). This project involves modeling wave generation and wave propagation in plasma environment and studying the effect of waves on the distribution of high energy electrons with the focus on electrons appeared after a high-altitude nuclear explosion (HANE). One of the major goal of this research is strong validation of the numerical models with laboratory experiments and space-based experiments and observations.

42 ENGINEERING↗
DOE OSTI2021

Nonlinear coupling of whistler waves to oblique electrostatic turbulence enabled by cold plasma

Kinetic simulations and theory demonstrate that whistler waves can excite oblique, short-wavelength fluctuations through secondary drift instabilities if a population of sufficiently cold plasma is present. The excited modes lead to heating of the cold populations and damping of the primary whistler waves. The instability threshold depends on the density and temperature of the cold population and can be relatively small if the temperature of the cold population is sufficiently low. Furthermore, this mechanism may thus play a significant role in controlling amplitude of whistlers in the regions of the Earth's magnetosphere where cold background plasma of sufficient density is present.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗