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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 109 records · Page 6

Object-Oriented Bayesian Networks (OOBN) for Aviation Accident Modeling and Technology Portfolio Impact Assessment

The concern for reducing aviation safety risk is rising as the National Airspace System in the United States transforms to the Next Generation Air Transportation System (NextGen). The NASA Aviation Safety Program is committed to developing an effective aviation safety technology portfolio to meet the challenges of this transformation and to mitigate relevant safety risks. The paper focuses on the reasoning of selecting Object-Oriented Bayesian Networks (OOBN) as the technique and commercial software for the accident modeling and portfolio assessment. To illustrate the benefits of OOBN in a large and complex aviation accident model, the in-flight Loss-of-Control Accident Framework (LOCAF) constructed as an influence diagram is presented. An OOBN approach not only simplifies construction and maintenance of complex causal networks for the modelers, but also offers a well-organized hierarchical network that is easier for decision makers to exploit the model examining the effectiveness of risk mitigation strategies through technology insertions.

Shih, Ann T.↗

Florida Transportation and Infrastructure: Monitoring Water Quality Along Southern Florida Seaports to Assess Impact on Coral Reef Tracts from Harbor Deepening Projects

The U.S. Army Corps of Engineers (USACE) and National Oceanic and Atmospheric Administration (NOAA) National Marine Fisheries Service (NMFS) will be supervising a harbor deepening project in Port Everglades, Florida. The project raises concerns about potential impacts on the nearby Florida reef tract through increased turbidity and sediment from the dredging. To better understand these potential impacts, the NASA DEVELOP team created an interactive Google Earth Engine tool to help establish a historical baseline of water quality parameters and assist monitoring these parameters more frequently than traditional sampling. This Seaport & Harbor Area Resource Quality (SHARQ) tool incorporates remotely sensed data from Sentinel-2 Multispectral Instrument, Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper+, Landsat 8 Operational Land Imager, and Aqua Moderate Resolution Imaging Spectroradiometer. It allows users to view true color images and calculate water quality parameters, like turbidity and chlorophyll-a, for any given study area and time period from 1984 onward. The SHARQ tool also generate time series charts, allowing users to interpret changes in water quality over a given time range. The accuracy of the remotely sensed water quality parameter algorithms was determined using in situ data to calculate percent difference and root mean square error values (RMSE), which ranged from 0.32 to 0.58 error between sites. Using the SHARQ tool’s time series analysis feature, a baseline average turbidity metric of ~6.8 FNUs provides a historical baseline average for turbidity between September 2000 and 2020 and can assist in future decision-making for determining thresholds for turbidity.

Benjamin Rocha↗

Assessing Impact of Joint Actuator Failure on Lunar Rover Mobility

Wheeled rovers are critical to exploration of the lunar surface, and loss of mobility actuators can have mission-ending consequences. NASA’s upcoming Volatiles Investigating Polar Exploration Rover (VIPER) has a four-wheeled active suspension, which gives it flexible extreme terrain mobility at the cost of an increased number of mobility actuators and potentially a higher mobility cost due to actuator loss than might occur on a similar six-wheeled rover. Impact varies greatly by both the affected joint and its failure state, and that in some cases modification of driving strategy may be able to partially mitigate mobility impact.

rover↗

Present-Day and Future PM 2.5 and O 3 -Related Global and Regional Premature Mortality in the EVAv6.0 Health Impact Assessment Model

We used the EVAv6.0 system to estimate the present (2015) and future (2015–2050) global PM 2.5 and O 3 -related premature mortalities, using simulated surface concentrations from the GISS-E2.1-G Earth system model. The PM 2.5 -related global premature mortality is estimated to be 4.3 and 4.4 million by the non-linear and linear models, respectively. Ischemic heart diseases are found to be the leading cause of PM 2.5 -related premature deaths, contributing by 35% globally. Both long-term and short-term O 3 -related premature deaths are estimated to be around 1 million, globally. Overall, PM 2.5 and O 3 -related premature mortality leads to 5.3–5.4 million premature deaths, globally. The global burden of premature deaths is mainly driven by the Asian region, which in 2015 contributes by 75% of the total global premature deaths. An increase from 6.2% to 8% in the PM 2.5 relative risk as recommended by the WHO leads to an increase of PM 2.5 -related premature mortality by 28%, to 5.7 million. Finally, bias correcting the simulated PM 2.5 concentrations in 2015 leads to an increase of up to 73% in the global PM 2.5 -related premature mortality, leading to a total number of global premature deaths of up to 7.7 million, implying the necessity of bias correction to get more robust health burden estimates. PM 2.5 and O 3 -related premature mortality in 2050 decreases by up to 57% and 18%, respectively, due to emission reductions alone. However, the projected increase and aging of the population leads to increases of premature mortality by up to a factor of 2, showing that the population exposed to air pollution is more important than the level of air pollutants, highlighting that the population dynamics should be considered when setting up health assessment systems.

Premature mortality↗

Utilizing Earth Observations to Model Probable Coastal Wetland Extent, Sea-Level Rise Inundation Risk, and Assess Impacts on Historic Hawaiian Lands

Climate induced sea-level rise poses a risk to coastal areas on the Island of Hawai’i, and many of the island’s historic cultural lands are in danger of becoming overtaken by wetlands or inundation. In partnership with the County of Hawai’i, State of Hawai’i Department of Land and Natural Resources, and Arizona State University, NASA DEVELOP mapped wetland extent and short-term sea-level rise inundation risk. We utilized Earth observations over a 10-year span (2013 – 2022) that included the NASA MEaSUREs Gridded Sea Surface Height Anomalies and MEaSUREs Group for High Resolution Sea Surface Temperature datasets, United States Geological Survey (USGS) Hawaii Digital Elevation Models (DEM), and in situ tidal gauge data. Flood risk index values were acquired for 5 known Hawai’i flood events between 2019 – 2021 from the Global Flood Mapper tool on Google Earth Engine. We used a random forest model to predict short-term sea-level rise inundation risk along the entire coast of Hawai’i. Current wetland extents and probabilistic locations of new wetlands were modeled with the most recently available data from PlanetScope Surface Reflectance optical imagery (2022), USGS 3D Elevation Program (3DEP) 10m DEM (2020), temperature and precipitation data from the Hawai’i Climate Atlas, and soils data from the Hawai’i Soil Atlas (2014) using the Wetland Intrinsic Potential tool. Results indicated locations that had the highest probability of wetland creation. The end products aimed to help the partners prioritize efforts to meeting regulation requirements for wetlands protection, evaluate the inundation risk to historical features, and support decision-making for their Shoreline Setback and Climate Adaption plans.

Lisa Tanh↗

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗

Hypervelocity impact damage assessment for Space Station

To inhibit damage and limit the probability of penetration of the Space Station pressure wall by micrometeoroids and orbital debris, a shield placed away from the wall is used to form a double wall. To determine shield effectiveness and assess impact damage, existing test data were reviewed and additional testing was performed for Space Station double wall designs. Empirical spallation and penetration functions derived from the data show that shield thickness and impact angle affect the damage to the wall. Thick shields reduce wall damage for low angle impacts but increase damage for oblique impacts. Multilayer insulation between the shield and wall reduces impact damage to the wall. A relationship between impact velocity and spall damage to the wall is demonstrated. Preliminary test results on Li-Al shield material indicate possible improved effectiveness over Al shields.

Coronado, Alex R.↗

Efficient Hybrid Attack Graph Generation for Cyber-Physical System Resilience Experimentation (Final Project Report)

HAGEN project has developed theory, algorithms, and capabilities to assist cyber physical system modelers and operators to perform system and device-level vulnerability assessment, risk assessment, impact assessment, and mitigation planning. The project generates hybrid attack graphs for Cyber-Physical System (CPS) resilience experimentation at desired scale and speed. The project will produce composite attack datasets, algorithms, and demonstrable prototypical tools, and a library of high-impact attack sequences for a given CPS of interest. This report provided overall summary of research and development performed between FY22-24.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

A review of future weather data for assessing climate change impacts on buildings and energy systems

The effectiveness of climate change impact assessments and the development of adaptation strategies depend on the availability of high-quality future weather data. However, significant gaps exist between the needs of the energy research community and the focus of the climate modeling community, primarily due to a historical lack of communication and collaboration between the two groups. Here, to address this issue, this work provides a comprehensive overview of the critical aspects involved in creating future weather data for building and energy system modeling, including emissions scenarios, general circulation models, downscaling methods, categories of future weather data, and uncertainties in climate simulations. Moreover, it critically evaluates the applicability and suitability of various types of future weather data in five key application scenarios: energy use analysis, resilience analysis, HVAC design, utility-scale analysis, and renewable energy analysis. Finally, this work presents recommendations for high-level actions and research directions to foster collaboration between the energy research and climate modeling communities and to promote the integration of future weather data into energy codes and the design practices of buildings and energy systems.

Climate change↗