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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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108 records · Page 6
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NASA NTRS2015

Forecasting Space Weather Events for a Neighboring World

Shortly after NASA's Mars Atmosphere and Volatile EvolutioN mission (MAVEN) spacecraft entered Mars' orbit on 21 September 2014, scientists glimpsed the Martian atmosphere's response to a front of solar energetic particles (SEPs) and an associated coronal mass ejection (CME). In response to some solar flares and CMEs, streams of SEPs burst from the solar atmosphere and are further accelerated in the interplanetary medium between the Sun and the planets. These particles deposit their energy and momentum into anything in their path, including the Martian atmosphere and MAVEN particle detectors. MAVEN scientists had been alerted to the likely CME-Mars encounter by a space weather prediction system that had its origins in space weather forecasting for Earth but now forecasts space weather for Earth's neighboring planets. The two Solar Terrestrial Relations Observatory spacecraft and Solar Heliospheric Observatory observed a CME on 26 September, with a trajectory that suggested a Mars intercept. A computer model developed for solar wind prediction, the Wang-Sheeley-Arge-Enlil cone model [e.g., Zheng et al., 2013; Parsons et al., 2011], running in real time at the Community Coordinated Modeling Center (CCMC) located at NASA Goddard since 2006, showed the CME propagating in the direction of Mars (Figure 1). According to MAVEN particle detectors, the disturbance and accompanying SEP enhancement at the leading edge of the CME reached Mars at approximately 17 hours Universal Time on 29 September 2014. Such SEPs may have a profound effect on atmospheric escape - they are believed to be a possible means for driving atmospheric loss. SEPs can cause loss of Mars' upper atmosphere through several loss mechanisms including sputtering of the atmosphere. Sputtering occurs when atoms are ejected from the atmosphere due to impacts with energetic particles.

space weather↗
NASA NTRS2018

The SPASE Data Model: A Metadata Standard for Registering, Finding, Accessing, and Using Heliophysics Data Obtained from Observations and Modeling

The Space Physics Archive Search and Extract Consortium has developed and implemented the SPASE Data Model that provides a common language for registering a wide range of Heliophysics data and other products. The Data Model enables discovery and access tools such that any researcher can obtain data easily, thereby facilitating research, including on space weather. The Data Model includes descriptions of Simulation Models and Numerical Output, pioneered by the Integrated Medium for Planetary Exploration (IMPEx) group in Europe, and subsequently adopted by the Community Coordinated Modeling Center (CCMC). The SPASE group intends to register all relevant Heliophysics data resources, including space-, ground-, and model-based. Substantial progress has been made, especially for space-based observational data and associated observatories, instruments, and display data. Legacy product registrations and access go back more than 50 years. Real-time data will be included. The National Aeronautics and Space Administration (NASA) portion of the SPASE group has funding that assures continuity in the upkeep of the Data Model and aids with adding new products. Tools are being developed for making and editing data descriptions. Digital Object Identifiers (DOIs) for Data Products can now be included in the descriptions. The data access that SPASE facilitates is becoming more uniform, and work is progressing on Web Service access via a standard Application Programming Interface. The SPASE Data Model is stable; changes over the past 9 years were additions of terms and capabilities that are backward compatible. This paper provides a summary of the history, structure, use, and future of the SPASE Data Model.

Roberts, D. Aaron↗
NASA NTRS2018

Data Mining for Vortices on the Earth's Magnetosphere - Algorithm Application for Detection and Analysis

Unsteady processes in the solar wind– magnetosphere interaction, such as vortices developed at the magnetopause boundary by the Kelvin–Helmholtz instability, may contribute to the process of mass, momentum and energy transfer into the Earth’s magnetosphere. The research described in this paper validates an algorithm to automatically detect and characterize vortices based on velocity data from simulations. The vortex identification algorithm (VIA) systematically searches the 3-D velocity fields to identify critical points where the magnitude of the velocity vector vanishes. The velocity gradient tensor is computed and its invariants are used to assess vortex structure in the flow field. We use the Community Coordinated Modeling Center (CCMC) Runs on Request capability to create a series of model runs initialized from the conditions observed by the Cluster mission in the Hwang et al. (2011) analysis of Kelvin–Helmholtz vortices observed during southward interplanetary magnetic field (IMF) conditions. We analyze further the properties of the vortices found in the runs, including the velocity changes within their motion across the magnetosheath. We also demonstrate the potential of our tool to identify and characterize other transient features (e.g., flux transfer events, FTEs) with vortical internal structures. We find that the vortices are associated with flows on the magnetosheath side of the magnetopause that reach speeds greater than the solar wind speed at the bow shock.

Collado-Vega, Yaireska M.↗
NASA NTRSDate not supplied

Building Collaborative Proving Grounds for R2O2R – NASA/CCMC - NOAA/Space Weather Prediction Testbed (SWPT) Partnership

In 2016 and 2019, Executive Orders were signed by the President to prepare the Nation for Space Weather Events. At the forefront of being able to achieve this goal is the necessity to accelerate and enhance R2O2R. To drive this initiative, the Space Weather R2O2R Framework, initially led by NOAA and NASA, was developed. At the very center of the framework is the Space Weather Proving Grounds effort that will allow various institutions to collaborate, share, and advance their space weather modeling and simulation capabilities. The first of these Proving Grounds is the Architecture for Collaborative Evaluation (ACE) environment shared between the Community Coordinated Modeling Center (CCMC) at NASA and the Space Weather Prediction Testbed (SWPT) at NOAA. Since 2019, the ACE environment has been set up on the AWS cloud where it utilizes AWS cloud services and Docker containerization technology.

T. Tsui↗
NASA NTRSDate not supplied

Kamodo’s Satellite Constellation Mission Planning Tool

Kamodo provides a functional model-agnostic interface to a growing collection of Heliophysics model outputs. The CCMC, in collaboration with the Geospace Dynamics Constellation Science Team, has recently developed Kamodo’s satellite constellation mission planning tool to perform reconstructions in any pair of dimensions, including time. The ‘reconstruction’ tool enables users to fly any 4-dimensional grid of satellites through a given model data set, reconstructing what the given constellation would observe during the mission. This capability facilitates determination of what satellite configuration is best for a given science question, even allowing comparison across multiple models. This tool, written in Python, is built upon Kamodo’s flythrough tool, which in turn depends on a growing network of model-specific interfaces. Since each model interface is designed with model-agnostic syntax, the flythrough tool and the satellite constellation mission planning tool also feature model-agnostic syntax. In this work, we will describe the basic analysis choices available in the tool and provide a variety of sample workflows. The tool is freely available at https://github.com/nasa/Kamodo for the public. We invite the community to use the reconstruction tool and adapt the provided workflows for their mission planning, and to contribute their own workflows to share with others.

software↗
NASA NTRSDate not supplied

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

software↗
NASA NTRSDate not supplied

SM25C-2002: Kamodo’s Satellite Constellation Mission Planning Tool

Kamodo provides a functional model-agnostic interface to a growing collection of Heliophysics model outputs. The CCMC, in collaboration with the Geospace Dynamics Constellation Science Team, has recently developed Kamodo’s satellite constellation mission planning tool to perform reconstructions in any pair of dimensions, including time. The ‘reconstruction’ tool enables users to fly any 4-dimensional grid of satellites through a given model data set, reconstructing what the given constellation would observe during the mission. This capability facilitates determination of what satellite configuration is best for a given science question, even allowing comparison across multiple models. This tool, written in Python, is built upon Kamodo’s flythrough tool, which in turn depends on a growing network of model-specific interfaces. Since each model interface is designed with model-agnostic syntax, the flythrough tool and the satellite constellation mission planning tool also feature model-agnostic syntax. In this work, we will describe the basic analysis choices available in the tool and provide a variety of sample workflows. The tool is freely available at https://github.com/nasa/Kamodo for the public. We invite the community to use the reconstruction tool and adapt the provided workflows for their mission planning, and to contribute their own workflows to share with others.

python↗
NASA NTRSDate not supplied

Science Workflows using Kamodo

Kamodo is a powerful python software package based on data functionalization. Once a given data set is functionalized, a large variety of capabilities are easily accessible in Kamodo, including unit conversions, custom analysis via function composition, interactive publication quality visualizations, and LaTeX encoding. The entirety of capabilities available in Kamodo are easily applied to both simulated and observed data across the multiple domains of Heliophysics and even in other disciplines. This work includes a variety of science workflows using Kamodo in combination with other resources, including with other python software packages, that expand the utility of Kamodo even further. These workflows include model-data comparisons, ensemble modeling examples, satellite mission planning examples, and other applications, all of which are freely available on CCMC’s Kamodo Github page for the community to adapt to their own uses (https://github.com/nasa/Kamodo). We invite the community to use these workflows and to contribute their own to share.

python↗
NASA NTRS2023

NAIRAS Ionizing Radiation Model: Extension from Atmosphere to Space

The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS) model is a real-time, global, physics-based model originally developed to predict exposure from cosmic radiation to air travelers from both galactic and solar sources. A prototype operational NAIRAS model has provided tabular and graphical data products via its public web site for about ten years. A new version of the NAIRAS model has been developed that incorporates an extension of the model domain from the atmospheric ionizing radiation environment to the space radiation environment, with the addition of the trapped inner belt proton source and altitude-dependent and rigidity-dependent geomagnetic shielding of the galactic cosmic rays (GCR) and solar energetic particle (SEP) protons. New output products of differential and integral particle flux have been developed for the characterization of single-event effects (SEE), expanding the application of NAIRAS from human radiation exposure assessment to allowing end-users to quantify radiation environment risks to aviation and spacecraft microelectronic systems. The NAIRAS model has transitioned to prototype operations at the Community Coordinated Modeling Center (CCMC) where the model now operates in two modes: (1) real-time global predictions of the atmospheric radiation environment and (2) a run-on-request (RoR) service allowing the user to select a specific time period for the global dosimetric calculations, or to upload an aircraft, balloon, or spaceflight trajectory file to provide predictions of the dosimetric and particle flux quantities along the flight path. The new features of NAIRAS version 3.0 are described in this paper and example results of the new output products for low-Earth orbit (LEO), medium-Earth orbit (MEO), and free-space radiation environments are presented

Christopher J. Mertens↗
NASA NTRSDate not supplied

Kamodo – An Adaptable Tool to Obtain and Compare Observations and Modeling Results

What is Kamodo? -Official NASA open-source project written in Python. -Building upon the functionalization of datasets. -It is a CCMC developed and maintained software tool for access, interpolation, and visualization of space weather models and data. -It allows model developers to represent simulation results as mathematical functions which may be manipulated directly by end users. -It handles unit conversion transparency and supports interactive science discovery through jupyter notebooks with minimal coding. -All Kamodo tools are accessible through Python, and all source code is publicly available on the Kamodo NASA GitHub repositories. -Kamodo does not generate model outputs. Users need to acquire the desired model outputs before they can be functionalized by Kamodo.

Kamodo↗
NASA NTRSDate not supplied

SPHINX: An SEP Model Validation Infrastructure developed through Community Challenges and the SEP Scoreboards

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars (Whitman et al 2022). For these reasons, SEP modelers have developed a rich and diverse set of models with a wide variety of aims. Some models probe the basic physics at the heart of particle acceleration and transport. Others produce fast statistical forecasts or employ disruptive new techniques like Machine Learning with the goal to assist end users in making operational decisions. To enable a consistent and quantitative understanding of SEP model performance, a generalized, automated validation infrastructure, called SPHINX, is being developed at NASA SRAG in close collaboration with NASA CCMC, NASA M2M, NOAA SWPC, and BIRA-IASB. This infrastructure has been built up through a multi-year community challenge. Starting in 2018 at the SHINE workshop, an effort was launched through SHINE, ISWAT, and ESWW to encourage quantitative, comprehensive, and consistent validation of SEP models. This effort has defined a set of challenge SEP events with the aim of generating quantitative comparisons between forecasts and observations and a set of challenge “non-events” to assess false alarms. In 2023, these challenge lists have been extended to statistically significant numbers with a prescribed set of rules for producing forecasts and supported through the dedicated SEPVAL working meetings. The participation of the research community has allowed the infrastructure to validate all the types of outputs being produced by SEP models. In parallel, the SPHINX code is being applied to real time forecasts submitted to the SEP Scoreboards, ensuring that the validation infrastructure can interpret forecasts produced in an operational scenario and provide metrics meaningful for operations. Upon completion, SPHINX and its interactive user interface, SPHINX-Web, will be made available for public use.

space weather↗
NASA NTRSDate not supplied

Comparison of the Nowcast of Aerospace Ionizing Radiation System (NAIRAS) With ISS Measurements

The Nowcast of Aerospace Ionizing Radiation System (NAIRAS) is a sophisticated physics-based model that has been providing real-time global predictions of cosmic radiation exposure, pertinent to both galactic and solar sources, to air travelers for a decade. The utility of NAIRAS, however, extends beyond the atmospheric ionizing radiation environment. The recently developed NAIRAS 3.0 version demonstrates an expansion of its domain to the space radiation environment. This extension incorporates an additional trapped inner belt proton source, coupled with altitude-dependent and rigidity-dependent geomagnetic shielding for galactic cosmic rays (GCR) and solar energetic particle (SEP) protons. The latest version of NAIRAS operates in two modes: real-time global predictions of the atmospheric radiation environment and a user-specified run-on-request service for global dosimetric calculations or predictions of dosimetric and particle flux quantities along user-uploaded flight path. It is available to the public at the Community Coordinated Modeling Center (CCMC). In this work, we present the validation exercises that have been conducted using the Automated Radiation Measurements for Aerospace Safety (ARMAS) onboard the International Space Station (ISS), thereby establishing NAIRAS's efficacy in predicting space radiation exposure. As such, NAIRAS 3.0 holds significant potential for human safety and technological advancement in aerospace travel and exploration.

Daniel Phoenix↗
NASA NTRSDate not supplied

Analyzing Space Weather at Mars with MAVEN

To understand the processes driving Martian atmospheric escape to space, the MAVEN mission has been monitoring solar inputs at Mars since the spacecraft went into orbit in September 2014. MAVEN’s payload provides in situ measurements of solar wind ions and electrons, solar energetic particles, extreme ultraviolet radiation, and magnetic fields. With this comprehensive suite of instruments, the MAVEN team has monitored space weather at Mars for nearly a decade, over various parts of Solar Cycles 24 and 25. MAVEN observations have determined that space weather activity can deposit enough energy into the Martian system to enhance atmospheric escape by an order of magnitude. As the mission continues, monitoring space weather at Mars has become increasingly important to understand the Sun’s influence on the Martian environment. The MAVEN team provides regular reports of space weather activity, such as the occurrence and arrival time of coronal mass ejections as well as flare magnitude and peak times, to the Mars community when predictions suggest that a space weather-impacting event may be directed towards Mars. MAVEN provides observations of solar activity on the ‘far side’ of the Sun when Earth and Mars are near solar conjunction to augment measurements of solar observatories (e.g., SDO, STEREO, GOES, PSP, Solar Orbiter), providing a more global coverage of solar activity. Additionally, MAVEN is working closely with the Community Coordinated Modeling Center (CCMC) and the Moon to Mars (M2M) Space Weather Analysis Office, both located at NASA GSFC, to form the Mars Space Weather Collaboration. This collaboration utilizes MAVEN observations of space weather activity to facilitate model and prediction validation while creating tools that are available to the science community. These activities are in support of future human and robotic exploration as we identify needs to enhance current capabilities for analyzing space weather at Mars.

Gina A DiBraccio↗
NASA NTRSDate not supplied

The Effect of a SEP Event on Astronauts Doing a Spacewalk As Computed By the Nowcast of Aerospace Ionizing Radiation System (NAIRAS)

The Nowcast of Aerospace Ionizing Radiation System (NAIRAS) is a sophisticated physics-based model that has been providing real-time global predictions of cosmic radiation exposure, pertinent to both galactic and solar sources, to air travelers for a decade. The utility of NAIRAS, however, extends beyond the atmospheric ionizing radiation environment. The recently developed NAIRAS 3.0 version demonstrates an expansion of its domain to the space radiation environment. This extension incorporates an additional trapped inner belt proton source, coupled with altitude-dependent and rigidity-dependent geomagnetic shielding for galactic cosmic rays (GCR) and solar energetic particle (SEP) protons. The latest version of NAIRAS operates in two modes: real-time global predictions of the atmospheric radiation environment and a user-specified run-on-request service for global dosimetric calculations or predictions of dosimetric and particle flux quantities along user-uploaded flight path. It is available to the public at the Community Coordinated Modeling Center (CCMC). In this work, we present the computations of the dose in the ISS vicinity during the SEP event of August 8, 2023; which happened a day before a scheduled spacewalk. We demonstrate that astronauts would not have suffered a dose equivalent in excess of 1 mSv if the event happened a day later. As such, NAIRAS 3.0 holds significant potential for human safety and technological advancement in aerospace travel and exploration.

Guillaume Gronoff↗
NASA NTRSDate not supplied

A Multi-Year Effort to Forward the Validation of Solar Energetic Particle Prediction Models

To enable a consistent and quantitative understanding of solar energetic particle (SEP) model performance, a generalized, automated validation infrastructure, called SPHINX, is being developed by the NASA Space Radiation Analysis Group (SRAG) in close collaboration with the NASA Community Coordinated Modeling Center (CCMC), NASA Moon to Mars Space Weather Analysis Office (M2M), NOAA Space Weather Prediction Center (SWPC), and the Royal Belgian Institute for Space Aeronomy (BIRA-IASB). SPHINX is being developed to evaluate the SEP Scoreboards (https://ccmc.gsfc.nasa.gov/scoreboards/sep/), which are being used by SRAG to support space radiation operations for Mission Control. SPHINX is also being developed through a series of community challenges, which have defined a list of challenge events and a prescribed set of rules of participation. The participation of the research community has enabled the generalization of the infrastructure to validate all the types of outputs being produced by SEP models and fully exercised the framework. The most recent challenge includes 30 SEP events and 33 non-event (quiet) periods and was supported by two dedicated SEPVAL working meetings, one in the US and one in Europe (https://ccmc.gsfc.nasa.gov/community-workshops/ccmc-sepval-2023/). Here, we describe SPHINX and its interactive user interface, SPHINX-VIVID, which will eventually be made available for public use. We present selected results, outcomes, and lessons learned from the SEPVAL working meetings and validation results of the SEP Scoreboards from 2019 to present. These efforts aim to define a set of community standards for SEP model validation and describe the current state-of-the-art of SEP model performance.

Kathryn Whitman↗
NASA NTRSDate not supplied

Impact of the May 2024 Gannon Storm on Low Earth Orbit Dosimetric Quantities: Comparisons of the NAIRAS Model -Real Time and Re-analysis- with ISS Data

The solar storm of May 2024, the Gannon storm, led to a display of aurora over the globe. One of the less known effects of that storm is on the radiation doses in low-Earth orbit: it first led to a Forbush decrease in dose rates and then to a Solar Energetic Particle (SEP) event that increased the total dose suffered near the international space station. The Nowcast of Aerospace Ionizing RAdiation System (NAIRAS) model predicts dosimetric and radiative flux quantities for assessing human radiation exposure levels and radiation effects on flight electronic systems from the surface of the Earth to deep space. It runs in near-real-time at the CCMC, but also has a run-on-request that allows for a more precise computation thanks to carefully processed data. NAIRAS was able to compute the effects of the Gannon storm at the ISS in real-time and provide ideas of the doses encountered by the astronauts and the experiments in and outside of the station. In this work, we show the simulations of the doses encountered during the storm and compare them with several measurements at the ISS. This work shows the capabilities of NAIRAS to address the problem of the SEP events at low Earth orbit and its real-time capabilities.

Guillaume Gronoff↗
NASA NTRSDate not supplied

Model-Specific Metadata for Enhancing Space Science Models

The Space Weather and Heliophysics modeling community, supported by the Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov), provides a collaborative platform for space weather models and data. Flexible metadata is vital for advancing scientific research and fostering collaboration. Our work in expressing complex simulations of the Space Weather Modeling Framework (SWMF), particularly Global Magnetosphere (GM) grid components, in terms of simple metadata records shows great promise in creating searchable and reusable units of knowledge. Such records can be readily utilized to support the process of scientific discovery, closely aligning with the goals outlined in the Open Science initiative. Our primary goal is to show the scalability and benefits of metadata-focused methodologies. This presentation highlights the potential for applying metadata methodologies to other complex models, improving usability, supplying efficient documentation and fostering interdisciplinary research.

space weather↗
NASA NTRSDate not supplied

AMPS and Its Use

Analyze charged particle trajectories moving in plasma. Post processing tool: use pre-calculated plasma and magnetic field. Import of the plasma flow simulations into AMPS. Time-dependent results of the plasma modeling is saved in files. Output: 1) Individual particle trajectories, 2) Samples of the distribution functions. Particle trajectory integration in AMPS. Trajectory affected by the Lorentz force. Particle tracking along a magnetic field line.

AMPS↗