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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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NASA NTRS2019

Risk of Increased Fragmentation Events Due to Low Altitude Large Constellation Spacecraft

Orbital debris experts and industry leaders are concerned about the added hazard that thousands of additional spacecraft would have on the future orbital debris environment. Large constellations proposals plan to deploy spacecraft at altitudes from 1100 km to 1300 km, where fragmentation debris can take thousands of years or longer to decay naturally, while other proposals include deploying spacecraft at station-keeping altitudes from 300 km to 600 km. Although these lower altitude spacecraft are compliant with the 25-year rule, there is still an increased risk of accidental explosions generating high velocity fragments that could damage international spacecraft assets. The NASA Orbital Debris Program Office (ODPO) has conducted several parametric studies that examine the potential negative environmental impacts of large constellation deployments. This study addresses the lower altitude constellations and the potential risk that they impose on the future environment during mission operations. The projected future environment is generated as the average of 100 LEGEND Monte Carlo (MC) simulation runs while adjusting parameters such as average probability of explosion and operational lifetime per constellation. Results of the effect of accidental explosions of large constellation spacecraft on the environment below 600 km altitude are analyzed.

Vavrin, A.↗
NASA NTRS2019

The NASA Orbital Debris Engineering Model 3.1: Development, Verification, and Validation

The NASA Orbital Debris Program Office has developed the Orbital Debris Engineering Model (ORDEM) primarily as a tool for spacecraft designers and other users to understand the long-term risk of collisions with orbital debris. The newest version, ORDEM 3.1, incorporates the latest and highest fidelity datasets available to build and validate representative orbital debris populations encompassing low Earth orbit (LEO) to geosynchronous orbit (GEO) altitudes for the years 2016-2050. ORDEM 3.1 models fluxes for object sizes > 10 μm within or transiting LEO and > 10 cm in GEO. The deterministic portion of the populations in ORDEM 3.1 is based on the U.S. Space Surveillance Network (SSN) catalog, which provides coverage down to approximately 10 cm in LEO and 1 m in GEO. Observational datasets from radar, in situ, and optical sources provide a foundation from which the model populations are statistically extrapolated to smaller sizes and orbit regions that are not well-covered by the SSN catalog, yet may pose the greatest threat to operational spacecraft. Objects in LEO ranging from approximately 5 mm to 10 cm are modeled using observational data from ground-based radar, namely the Haystack Ultrawideband Satellite Imaging Radar (HUSIR – formerly known as Haystack). The LEO population smaller than approximately 3 mm in size is characterized based on a reanalysis of in situ data from impacts to the windows and radiators of the U.S. Space Transportation System orbiter vehicle, i.e., the Space Shuttle. Data from impacts on the Hubble Space Telescope are also used to validate the sub-millimeter model populations in LEO. Debris in GEO with sizes ranging from 10 cm to 1 m is modeled using optical measurement data from the Michigan Orbital DEbris Survey Telescope (MODEST). Specific, major debris-producing events, including the Fengyun-1C, Iridium 33, and Cosmos 2251 debris clouds, and unique populations, such as sodium-potassium droplets, have been re-examined and are modeled and added to the ORDEM environment separately. The debris environment greater than 1 mm is forecast using NASA’s LEO-to- GEO ENvironment Debris model (LEGEND). Future explosions of intact objects and collisions involving objects greater than 10 cm are assessed statistically, and the NASA Standard Satellite Breakup Model is used to generate fragments from these events. Fragments smaller than 10 cm are further differentiated based on material density categories, i.e., high-, medium-, and low-density, to better characterize the potential debris risk posed to spacecraft. The future projection of the sub-millimeter environment is computed using a special small-particle degradation model where small particles are created from intact spacecraft and rocket bodies. This work discusses the development, features, and capabilities of the ORDEM 3.1 model; the ne new data analyses used to build the model populations; and sample verification and validation results.

Matney, M.↗
NASA NTRS2019

NASA GIBS and Worldview: Visualizing NASA's Earth Science Data for All to Explore

For more than 20 years, the NASA Earth Observing System (EOS) has operated dozens of remote sensing satellites collecting nearly 15 Petabytes of data that span thousands of science parameters. Within these observations are keys the Earth Scientists have used to unlock many discoveries that we now understand about our planet. Also contained within these observations are a myriad of opportunities for learning and education. The challenge is making them accessible to educators and students in intuitive and simple ways so that effort can be spent on lesson enrichment and not overcoming technical hurdles.The NASA Global Imagery Browse Services (GIBS) system and NASA Worldview interactive mapping site provide a unique view into EOS data through daily full resolution visualizations of hundreds of Earth science parameters. For many of these parameters, visualizations are available within hours of acquisition from the satellite. For others, visualizations are available for the entire mission of the satellite. Accompanying the visualizations are visual aids such as color legends, place names, and orbit tracks. By using these visualizations, educators and students can observe natural phenomena that enrich a scientific education.This presentation will provide an overview of the visualizations available in NASA GIBS and Worldview and how they are accessed. Specific attention will be given to the newer capabilities and accomplishments, including: Support for geostationary sub-daily visualizations, Enhanced support for vector-based visualizations, Improved Worldview tour and snapshot capabilities, New imagery products across a growing set of scientific areas.

Cechini, Matthew↗
NASA NTRSDate not supplied

Increasing Engagement Through Storytelling

For years, storytelling has been used to pass down history, customs, rituals, and legends. Because a good narrative can tap into our emotions, we’re more likely to remember the story. By weaving narrative and curriculum together, we can provide our learners with an experience that can not only entertain them, but improve retention. Learn how to: • Start with a character your audience can relate to • Use emotion to better help information stick in their brains • Let your audience become part of the narrative

Sharon Goza↗
NASA NTRSDate not supplied

Utilizing Open-Source Earth Observations to Inform the Toa Baja Municipality’s Flood Risk Mitigation Efforts and Educate the Public

Global climate changes contribute to more intense and frequent tropical storms, subjecting places like Toa Baja, Puerto Rico to critical damage. Known as “the underwater city” due to its propensity to flood, residents of Toa Baja face constant flood risk. During extreme tropical storm events, such as Hurricane Maria in 2017, residents experienced up to 20 feet of inundation. The NASA DEVELOP National Program collaborated with the Municipio Autónomo de Toa Baja, ResilientSEE-PR, and the MIT Urban Risk Lab to supplement 2018 FEMA HEC-RAS flood maps that designate 63% of Toa Baja as a flood plain. This analysis provides a high-resolution interpretation of flood risk through two lenses; susceptibility and vulnerability. For this analysis, susceptibility consists of nine weighted layers: NDVI, landcover, slope, elevation, topographic wetness index, height above nearest drainage, saturated hydraulic conductivity, distance to water, and storm surge. These factors are consistently used to evaluate susceptibility to flood, but their weights vary by analysis. Vulnerability consists of population, informal settlements, and building density, which were given equal weight. Susceptibility and vulnerability were combined to map flood risk. This analysis used a bivariate legend to understand the different levels of risk along a spectrum from low susceptibility and low vulnerability (low risk) to high susceptibility and high vulnerability (high risk). Data processed in Google Earth Engine, which identified historical inundation on various occasions, were used to validate the flood susceptibility layers. Results showed 89% of areas designated as high susceptibility are located within the floodway designated by the FEMA HEC-RAS maps. The eastern region of Toa Baja is most at risk for flooding due to high susceptibility to flooding along with a high density of population, buildings, and informal settlements. The resulting map also reveals the presence of smaller high-risk areas all around the municipality. This analysis provides scientific evidence for flood risk mitigation in Toa Baja by highlighting areas that might be impacted by strong floods in the future. Additionally, these results are communicated in an Esri ArcGIS StoryMap, an accessible platform that can easily inform the public about the flood risk in their neighborhood.

Adriana Le Compte↗
NASA NTRS2021

SeaDAS Tutorial: Applying Color Ramps to ACOLITE Turbidity Products

This tutorial provides step-by-step instructions for applying color ramps and legends to ACOLITE turbidity products derived from the Dogliotti turbidity equation. The user inputs their own image and the resulting product is a colorized visualization of turbidity. This visualization provides the user with a better understanding of turbidity in their image and can be used to support further analysis of turbidity patterns.

Kelly Young↗
NASA NTRS2024

A Survey of Modeling Activities by NASA’s Orbital Debris Program Office

NASA’s Orbital Debris Program Office (ODPO) develops and maintains a number of modeling tools to analyze and simulate the orbital debris environment. One of the most important products produced by the NASA ODPO is the Orbital Debris Engineering Model (ORDEM). This model can be used by satellite designers and operators to design missions for better protection against the debris environment. The ODPO is currently working on the next generation, designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and the ability to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. A new addition will be a parameterized debris shape model based on laboratory hypervelocity impact tests, including DebriSat. ORDEM is primarily based on dedicated debris measurements, such as by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, and observations of geosynchronous orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). In addition to ORDEM, the ODPO also maintains other models, such as the LEO-to-GEO Environment Debris (LEGEND) model for studies of long-term evolution of Earth’s debris environment, with the ability to study various mitigation and remediation strategies. Another model, the Satellite Breakup Risk Assessment Model (SBRAM), is used to analyze how satellite breakups may affect critical space missions (such as the ISS) on short notice. In addition to these models, the ODPO maintains other secondary models used to model satellite explosions and collisions, analyze radar, optical, and in situ data, and to model such things as solar activity and orbit evolution. In this presentation, a survey of these models will be presented, showing how the different models are used together to create a comprehensive picture of Earth’s debris environment.

Mark Matney↗
NASA NTRSDate not supplied

The Radsetta Stone – Establishing a Common Environment Taxonomy Across Space Nuclear Technologies

Qualitative descriptions, such as “high temperature” or “long exposure” vary substantially according to the context and can obfuscate messaging. A quantitative taxonomy for describing space nuclear environments - encompassing fission, radioisotope, and natural - has been established to enable clear communication across technology applications. Zones have been defined to partition environments with an intent to achieve a useful level of granularity. These zones enable a more detailed assessment than the Technology Readiness Level and can also be used to identify gaps and overlaps spanning space nuclear technologies. This framework has been named the Radsetta Stone – a paronomasia of the Rosetta Stone. There are two directions in which the Radsetta Stone can be used. The user may be a technology developer or a technology customer. The developer would use the Radsetta Stone to communicate the current state of the technology they are developing. The maximum zone for each parameter would then be used to state the current limit of their technology. The customer could use the Radsetta Stone to communicate the environmental conditions of their system. Zones would be associated with different locations within the system. The Radsetta Stone is intended to enable clear communication regarding space nuclear technology. The following legend and tables show the levels of the Radsetta Stone. These levels show success criteria gates in a similar manner as Technology Readiness Levels.

taxonomy↗
DOE OSTI2023

Energy calibration of germanium detectors for the Majorana Demonstrator

The Majorana Demonstrator was a search for neutrinoless double-beta decay (0νββ) in the 76 Ge isotope. It was staged at the 4850-foot level of the Sanford Underground Research Facility (SURF) in Lead, SD. The experiment consisted of 58 germanium detectors housed in a low background shield and was calibrated once per week by deploying a 228 Th line source for 1 to 2 hours. The energy scale calibration determination for the detector array was automated using custom analysis tools. We describe the offline procedure for calibration of the Demonstrator germanium detectors, including the simultaneous fitting of multiple spectral peaks, estimation of energy scale uncertainties, and the automation of the calibration procedure.

47 OTHER INSTRUMENTATION↗