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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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718 records · Page 40

Recovery of Voyager Plasma Electron Observations at Jupiter

We will present our recovery of Voyager 1 and 2 plasma electron observations during their Jupiter flybys. The analysis is expected to be completed by the time of the Fall AGU 2023 Meeting and stored in Goddard’s Data Center and we will present new results never published before. The original summary data tapes and later data files at first appeared to be permanently lost but eventually located at the Massachusetts Institute of Technology, while data analysis results done at Goddard Space Flight Center, except for that published in journals, were permanently lost such as electron distribution functions, spacecraft trajectory and spacecraft attitude information. In addition to recovering the electron plasma observations (electron intensities and fluid parameters of the thermal and suprathermal electron populations, respectively), we use Spice Kernels for Voyager 1 and 2 trajectory and spacecraft attitude information, fortunately produced by NASA’s Jet Propulsion Laboratory. We will present new results of our work, originally funded under the Planetary Data Archiving, Restoration, and Tools (PDART) program but now being funded by the Internal Scientist Funding Model (ISFM) Exosphere Ionosphere Magnetospheres Modeling (EIMM) program at NASA Goddard Space Flight Center. If time permits, we will also present some of our recovery of the Voyager 2 Uranus plasma electron data and analysis similar to what was done for Jupiter.

E.C. Sittler Jr.↗

Interpretable Machine Learning Models for Autonomous Characterization of Analogue Ocean World Seawater Chemistry and Biosignature Potential Using Isotope Ratio Data

Background: Future missions to ocean worlds, such as Enceladus and Europa, will attempt to characterize the subsurface seawater chemistry and assess the potential for life. Such missions will be equipped with capabilities to precisely measure volatile isotopes in plumes, atmospheres, and exospheres. Motivation: While large isotopic fractionations can indicate a biological source, there are signatures resulting from abiotic geochemical processes that mimic isotopic biosignatures. While machine learning (ML) has the potential to disentangle competing effects and biotic mimicry, high-dimensional isotope ratio mass spectrometry (IRMS) data is likely to contain noise/irrelevant features and involve complex statistical interactions that make human inference and interpretation difficult. Further, ML predictions with as far-reaching implications as an extraterrestrial biosignature on an ocean world requires the use of interpretable models (i.e., not “black box” models) with physically and mathematically meaningful feature spaces along with false positive diagnostics. Methods: We use volatile CO2 IRMS data of analogue ocean world seawaters to validate an ML approach to provide biogeochemical context for biosignature detection. We employ a feature selection method called nearest-neighbor projected distance regression (NPDR) that detects statistical interactions and helps elucidate the mechanisms of the Random Forest classification models. Results: We train and validate predictive ML models on volatile CO2 IRMS data of analogue ocean world seawaters to predict major salt components (e.g., MgSO4, NaHCO3), pH, ionic strength, and the presence of biosignatures. Features derived from IRMS measurements are augmented with extracted time-series features. Our results show high test accuracy and interpretability, which is increased by interaction network visualization, sample-wise variable importance scores, and single-sample class probability estimates. We demonstrate an ML mission software solution that triggers autonomous data transmission and biogeochemical sample prediction.

geochemistry↗

Recovery of Voyager Plasma Electron Observations at Jupiter

We will present our recovery of Voyager 1 and 2 plasma electron observations during their Jupiter flybys. The analysis is expected to be completed by the time of the Fall AGU 2023 Meeting and stored in Goddard’s Data Center and we will present new results never published before. The original summary data tapes and later data files at first appeared to be permanently lost but eventually located at the Massachusetts Institute of Technology, while data analysis results done at Goddard Space Flight Center, except for that published in journals, were permanently lost such as electron distribution functions, spacecraft trajectory and spacecraft attitude information. In addition to recovering the electron plasma observations (electron intensities and fluid parameters of the thermal and suprathermal electron populations, respectively), we use Spice Kernels for Voyager 1 and 2 trajectory and spacecraft attitude information, fortunately produced by NASA’s Jet Propulsion Laboratory. We will present new results of our work, originally funded under the Planetary Data Archiving, Restoration, and Tools (PDART) program but now being funded by the Internal Scientist Funding Model (ISFM) Exosphere Ionosphere Magnetospheres Modeling (EIMM) program at NASA Goddard Space Flight Center. If time permits, we will also present some of our recovery of the Voyager 2 Uranus plasma electron data and analysis similar to what was done for Jupiter.

E.C. Sittler Jr.↗

Autonomous Science: Simulated Solar System Mission to Enceladus, Icy Ocean Moon of Saturn

Future NASA missions to icy ocean worlds such as Europa, Titan, or Enceladus will collect mass spectrometry (MS) data from exospheres, atmospheres, and plume volatiles to assess their geochemistry and potential for microbial life1. These remote missions face challenges related to limited bandwidth, communication, and power, highlighting the need for science autonomy2 to prioritize data for timely downlink. We extend our previous work on machine learning (ML) biosignature detection from isotope ratio mass spectrometry (IRMS) data to distributed systems missions (DSM) by incorporating the ML and autonomous data quality control and prioritization code into an onboard decision-making platform. We use simulated orbital telemetry for eight orbiters around Enceladus with a mothership to illustrate an automated biosignature and novel seawater chemistry detection with data prioritization from MS analyses of volatile CO2.

Conor Williams↗

Soft X-Ray Imaging of Earth's Dayside Magnetosheath and Cusps Using Hybrid Simulations

Interactions between solar wind ions and neutral hydrogen atoms in Earth's exosphere can lead to the emission of soft X-rays. Upcoming missions such as SMILE and LEXI aim to use soft X-ray imaging to study the global structure of the magnetosphere. Although the magnetosheath and dayside magnetopause can often be driven by kinetic physics, it has typically been omitted from fluid simulations used to predict X-ray emissions. We study the possible results of soft X-ray imaging using hybrid simulations under quasi-radial interplanetary magnetic fields, where ion-ion instabilities drive ultra-low frequency foreshock waves, leading to turbulence in the magnetosheath, affecting the dynamics of the cusp and magnetopause. We simulate soft X-ray emission to determine what may be seen by missions such as LEXI, and evaluate the possibility of identifying kinetic structures. While kinetic structures are visible in high-cadence imaging, current instruments may not have the time resolution to discern kinetic signals.

J Ng↗

Finding the magnetopause location using soft X-ray observations and a statistical inverse method

Variability in the location and shape of the dayside magnetopause is attributed to magnetic reconnection, a fundamental process that enables the transfer of mass, energy, and momentum from the solar wind into the magnetosphere. The spatial and temporal properties of the magnetopause, under varying solar and magnetospheric conditions, remain largely unknown because empirical studies using in-situ observations are challenging to interpret. Global wide field-of-view (FOV) imaging is the only means to simultaneously observe the spatial distribution of the plasma properties over the vast dayside magnetospheric region and, subsequently, quantify the energy transport from the interplanetary medium into the terrestrial magnetosphere. Two upcoming missions, ESA/CAS SMILE and NASA’s LEXI will provide wide-field imagery of the dayside magnetosheath in soft X-rays, an emission generated by charge exchange interactions between high charge-state heavy ions of solar wind origin and exospheric neutral atoms. High-cadence two-dimensional observations of the magnetosheath will allow the estimation of dynamic properties of its inner boundary, the magnetopause, and enable studies of its response to changes in the solar wind dynamic pressure and interplanetary magnetic field orientation. This work introduces a statistically-based estimation approach based on inverse theory to estimate the spatial distribution of magnetosheath soft X-ray emissivities and, with this, identify the location of the magnetopause over the Sun−Earth line. To do so, we simulate the magnetosheath structure using the MHD-based OpenGGCM model and generate synthetic soft X-ray images using LEXI’s orbit and attitude information. Our results show that 3-D estimations using the described statistically-based technique are robust against Poisson-distributed shot noise inherent to soft X-ray images. Also, our proposed methodology shows that the accuracy of both three-dimensional (3-D) estimation and the magnetopause standoff distance calculation highly depends on the observational point.

Gonzalo Cucho-Padin↗

A Feasibility Study of 4-D Tomography of Soft X-ray Magnetosheath Emissivities Using Multi-Spacecraft Measurements

Upcoming heliophysics missions utilize state-of-the-art wide field-of-view (FOV) imaging technology to measure and investigate the space plasma environment on a global scale. At Earth, remote sensing of soft X-ray emissions, which are generated via the charge exchange interaction between heavy solar wind ions and exospheric neutral atoms, is a promising means to investigate the global magnetosheath structure, its response to varying solar wind conditions, and the spatiotemporal properties of the dayside magnetic reconnection. Data analysis techniques such as optical tomography can provide additional structural and time-varying information from the observed target and thus enhance the mission’s scientific return. In this work, we simulate multiple and simultaneous observations of the dayside magnetosphere using soft X-ray imagers located at long-distance vantage points to reconstruct the time-dependent, three-dimensional (3-D) structure of the magnetosheath using a dynamic tomographic approach. The OpenGCCM MHD model is used to simulate the time-varying response of the magnetosheath to solar wind conditions and, subsequently, generate synthetic soft X-ray images from multiple spacecraft vantage points separated along a common orbit. A detailed analysis is then performed to identify the nominal set of spacecraft that produces the highest fidelity tomographic reconstruction of the magnetopause. This work aims to (i) demonstrate, for the first time, the use of dynamic tomography to retrieve the time-varying magnetosheath structure and (ii) identify a nominal mission design for multi-spacecraft configurations aiming for optical tomography.

3-D/4_d tomography↗

Materials for Power Transmission in Extreme Environments

NASA’s goal for a sustained human presence on the Moon and a future Lunar economy requires the development of novel power transmission materials for extreme environments. As an increasing number of public and private entities set their sights towards a future on the Moon, the demand for surface power will dramatically increase – potentially up to megawatt levels. A Lunar economy is envisioned to include a human habitat, manned and unmanned science exploration assets, excavation rovers and systems, and large-scale infrastructure construction such as solar arrays and power grids. A NASA trade study estimated that 1 to 3 km of power transmission lines (1 to 3 KV ac and dc) will be needed over time. Current high power and voltage SOA cables/wire can easily exceed 1 kg/m where mass is not as critical. Connectors, deployment spools and robots further increase the subsystem mass significantly increasing costs. On the other hand, advances in aeronautics provides path towards space missions. The operating environment on the Moon presents substantial risk to safe and reliable power transmission due to space weathering and degradation. These challenges include cosmic and UV radiation, extreme temperatures swings, the electrostatic Lunar exosphere, and the electrostatic and abrasive lunar regolith. The critical need for lightweight, safe and reliable power cables/wires materials is evident. In this presentation, the extreme high altitude and lunar environments and recent materials development from NASA Glenn Research Center’s High Voltage Materials team towards meeting NASA’s objectives and goals for aeronautics and space missions.

Cu/CNT conductors↗

The Lunar Environment Heliophysics X-Ray Imager (LEXI) Mission

The Lunar Environment heliospheric X-ray Imager (LEXI) is a wide field-of-view soft Xray telescope developed to study solar wind-magnetosphere coupling. LEXI is part of the Blue Ghost 1 mission comprised of 10 payloads to be deployed on the lunar surface. LEXI monitors the dayside magnetopause position and shape as a function of time by observing soft X-rays (0.1–2 keV) emitted from solar wind charge-exchange between exospheric neutrals and high charge-state solar wind plasma in the dayside magnetosheath. Measurements of the shape and position of the magnetopause are used to test temporal models of mesoand macro-scale magnetic reconnection. To image the boundary, LEXI employs lobster-eye optics to focus X-rays to a microchannel plate detector with a 9.1◦ × 9.1◦ field of view.

Lunar↗