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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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At least 1,621 records · Page 90

Nuclear Space System Analysis and Modelling (NSSAM): A Software Tool to Efficiently Analyze the Design Space of Space Reactor Systems

Space reactors have the potential to play a key role in future NASA exploration activities due to their capability to enable sustainable power and advanced propulsion systems. To enable assessment of the space reactor design space, the nuclear space system analysis and modelling (NSSAM) software was developed by Analytical Mechanics Associates. NSSAM leverages a scalable and extensible software architecture which automates reactor analysis to perform coupled engine-reactor and reactor physics-thermal hydraulics calculations. This allows space reactor systems to be evaluated by a wider number of users with a consistent analysis approach to compare designs. NSSAM has been developed with multiple use cases to tailor the analysis to the level of detail desired by the user and computing resources. This summary overviews the NSSAM architecture and development approach, current capabilities (including design variants and use cases) and analysis approach for reactor and system component models.

nuclear thermal propulsion↗

Analyzing the Impact of CryoSat-2 Ice Thickness Initialization on Seasonal Arctic Sea Ice Prediction

Twin 5-month seasonal forecast experiments are performed to predict the September 2018 minimum ice extent using the fully coupled Navy Earth System Prediction Capability (ESPC). In the control run, ensemble forecasts are initialized from the operational US Navy Global Ocean Forecasting System (GOFS) 3.1 for the ocean and sea ice but do not assimilate ice thickness data. Another set of forecasts are initialized from the same GOFS 3.1 fields but with sea ice thickness derived from CryoSat-2 (CS2). The Navy ESPC ensemble mean September 2018 minimum sea ice extent initialized with GOFS 3.1 ice thickness was over-predicted by 0.68 M sq.km (5.27 M sq.km) versus the ensemble set of forecasts initialized with CS2 ice thickness that had an error of 0.40 M sq.km (4.99 M sq.km), a 56% reduction in error. The September mean Integrated Ice Edge Error (IIEE) shows a 19% improvement for the entire Arctic with the CS2 data versus the control run. Comparison against Upward Looking Sonar (ULS) ice thickness in the Beaufort Sea reveals a lower bias and RMSE with the CS2 forecasts at all three moorings. Ice concentration at these locations is also improved, but neither set of experiments show ice free conditions as observed at moorings A and D.

time-lagged ensembles↗

Development of Modeling & Simulation Capability to Analyze Supply Chain

Supply chain has brought up many challenges to the current aerospace industry (e.g. limited sources, lack of inventory, and cyber security). The purpose of this research is to develop a web-based modeling and simulation platform for supply chains relating to Advanced Air Mobility and vertical take-off and landing vehicles (VTOLs).

Cybersecurity↗

Development of a Computer Tool to Analyze MISSE Images

The Materials International Space Station Experiment (MISSE) contains individual experiments focused on the investigation of the effects that occur because of the exposure of the material to the space environment. The specimens are mounted on the exterior of the International Space Station (ISS) on the MISSE-Flight Facility (MISSE-FF) and are exposed to the extreme environmental conditions. There have been 14 MISSE missions since the establishment in 2001. This project will evaluate MISSE 9 - MISSE 13 specimens and how they change due to the space environment.

MISSE↗

Bhutan Water Resources III: Analyzing Forest Disturbances and Climate Data in Bhutan to Create a Tool for Assisting the Himalayan Environment Rhythm Observation and Evaluation Systems (HEROES) Project

Forest disturbances from bark beetle outbreaks are a major concern in Bhutan, known to cause extensive tree mortality to pine and spruce forests. The NASA DEVELOP team partnered with the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER), the Bhutan Foundation, and the Karuna Foundation to assess forest changes for the districts of Bumthang and Haa from 2000 to 2018. The project used preprocessed meteorological data from the Climate Hazards Center Infrared Precipitation with Station (CHIRPS) and Famine Early Warning System Network Land Data Assimilation System (FLDAS), along with Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper plus (ETM+), and Landsat 8 Operational Land Imager (OLI) to assess apparent forest disturbance occurrences and observed climate trends. Shuttle Radar Topography Mission (SRTM) was used to resolve variations in elevation and slope for mountainous regions. Using the Google Earth Engine LandTrendr (LT) code algorithm, along with Landsat data, the team developed an app called Forest Disturbances Detection Toolbox (FDDT) to assess forest changes in Bhutan. The app includes climate variables for the focus districts, along with LT variables, which allows the end users to further examine the cause of disturbances. The team compared geocoordinates for known disturbances with LT disturbance detection products. Although additional work is needed in the future to validate the project end products from the FDDT, the tool will be provided to the project partners to aid forest management efforts in Bhutan.

Tashi Choden↗

Analyzing the Subjectivity of Hole-Type Image Quality Indicators for Radiography

Hole-type penetrameters used as image quality indicators (IQIs) for radiography have an inherent degree of subjectivity to their interpretation. The 1T (one times the thickness of the penetrameter) hole is so small, it can be difficult to distinguish from noise. It is suspected that an operator’s knowledge of the true location of the 1T hole may subconsciously influence a false positive identification of the 1T hole when in fact it cannot be discerned. In the case of computed radiography (CR), the size of the phosphor particles may lead to a noise pattern with features on the scale of the 1T hole. Per NASA-STD-5009, the 1T hole must be detected in order to achieve adequate sensitivity. This is based on the historical understanding that this sensitivity will enable detection of the minimum detectable flaw sizes listed in the standard. It’s important to understand if 1T sensitivity is being achieved, and the associated risk if not. This study sought to determine the true detectability of 1T-sized holes in aluminum and Inconel by creating and inspecting a set of penetrameters with randomly placed holes. Enough holes and vacant zones were created to enable a full probability of detection study with 90% detectability, 95% confidence. Testing is ongoing, but preliminary results have shown poor detectability. The detection rate is slightly better for Inconel than aluminum, slightly better using a micro-focus vs. mini-focus tube, and definitively better for film than CR. One of the key questions of this study is whether historical requirements for film are applicable for CR, and these initial findings suggest they may not be. There is also a requirement in the NASA standard for the minimum contrast-to-noise ratio of the hole. The results have shown that this numerical threshold does not correlate well with visual detection. This raises questions about the true nature of detection, in an age of image processing vs. human judgement. As the results indicate that the detection of 1T holes is unreliable, the next challenge will be determining what sensitivity is really achieved, and what is needed.

Erin Lanigan↗

Using Earth Observations to Analyze Shoreline Changes and Understand the Effects of Sea Level Rise in Southern Puerto Rico

This summer, the Jobos Bay National Estuarine Research Reserve (JBNERR) partnered with NASA DEVELOP to evaluate water quality, mangrove forest extent, sea level rise, and land cover changes in Jobos Bay. DEVELOP is a national capacity building program that connects satellite data with early career scientists and decision makers. Through ten-week feasibility studies, DEVELOP partners with organizations that have the power to enact policy within their communities. Jobos Bay, in the southeast coast of Puerto Rico, has experienced intense hurricane seasons with increased seasonal storm surge, near-shore land use changes, and strong variations in precipitation and runoff. Through proposals, bi-weekly meetings, and frequent email communication, this cross-sector initiative provided valuable results for management decisions within the reserve. Using satellite observations to measure land use change, the team found that 17% of the reserve has shifted from land to water along the coast since 1997. Using Sentinel-2 the team was able to visualize turbidity, chlorophyll-a, and colored dissolved organic matter (CDOM) for Jobos Bay. While some large events such as Hurricane Maria were reflected in the turbidity analysis, chlorophyll-a and CDOM visualizations were limited by the influence of shallow-water bottom reflectance, particularly around reefs and within the Bay. The team also found that Jobos Bay lost 4.9 square kilometers of mangrove habitat over the past decade, calculated using Landsat 7 and 8 within Google Earth Engine. The results from this study will inform JBNERR and its community members on the regional impacts of sea level rise as well as serve as a baseline for future conservation efforts and research in the estuary.

Olivia Spencer↗

Detecting Hail from Space: Using a Multi-Frequency Passive-Microwave Retrieval to Analyze the Global Climatology and Diurnal Cycle of Severe Hail

Severe hail poses myriad threats to society, causing extensive damage to infrastructure and agriculture. As hail is severe, relatively infrequent, and highly localized, it is difficult to measure in-situ and if left unresolved in models and precipitation retrievals, hail can cause large errors and uncertainties. The difficulty in measuring hail in situ and the inconsistency of surface-based hail reporting drive the motivation to use spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We leverage the scattering signatures of severe hail in spaceborne passive-microwave datasets paired with surface hail reports to construct a multi-frequency hail retrieval using Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We use this retrieval to construct global passive-microwave climatologies of severe hail using the TRMM, GPM, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. We also leverage the sensors in inclined orbits to assess the diurnal variability of severe hail globally and the effect the diurnal cycle has on the detection of hail by sensors in sun-synchronous orbit. The goal is to construct a robust, multi-decade multi-satellite climatology of hail. As part of the NASA Disasters Applied Sciences program, we assess these climatologies against other satellite severe weather datasets and use these climatologies in collaboration with stakeholders and end-users to help them assess risk, and improve the prediction, preparation, and response to severe storms around the world.

Sarah D Bang↗