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At least 937 records · Page 52

Identifying Solar Wind and Other Volatiles in Space-Weathered Samples From Asteroid Bennu

On September 24, 2023, NASA’s Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer (OSIRIS-REx) mission returned >70 g of material from asteroid Bennu to Earth. The Sample Return Capsule was opened at NASA Johnson Space Center (JSC), and a spillover sample was collected from the avionics deck to perform quick-look (QL) analyses. In addition to providing a reconnaissance investigation of its mineralogy, the sample was also examined for evidence of surface exposure on asteroid Bennu by identifying signatures of space weathering. Space weathering changes the morphology, microstructure, and chemistry of regolith on the surfaces of airless bodies. Driven by micrometeoroid bombardment and solar wind irradiation, our understanding of how space weathering modifies particles on the surfaces of carbonaceous asteroids is still developing. To bolster the interpretation of remote sensing data and to further address driving Hypothesis 10, we must investigate the nanoscale structural and chemical changes in returned samples from Bennu to understand how space weathering affects carbonaceous surface materials. Here we explore evidence for solar wind irradiation in QL samples from asteroid Bennu.

M S Thompson↗

Alaska Ecological Conservation: Using NASA Earth Observations to Identify Recent Changes in River Ice Phenology and Its Impacts on Caribou Migration

Each fall, caribou (Rangifer tarandus) in the Western Arctic Herd migrate hundreds of kilometers across northwestern Alaska to acquire seasonal resources and reach wintering grounds. Various rivers intersect migration paths, and caribou can only cross over open water or high-ice extents but are unable to cross rivers in stages of partial freezing. Recent temperature increases in Alaska can alter the timing and duration of ice formation periods, impeding migratory patterns. The Massachusetts NASA DEVELOP team partnered with the National Park Service in Alaska to detect river ice onset dates and formation periods using Landsat 8 Operational Land Imager and Landsat 9 Operational Land Imager-2, Sentinel-1 C-band Synthetic Aperture Radar and Sentinel-2A/B MultiSpectral Instrument imagery in Google Earth Engine. This feasibility analysis measured ice coverage using the Normalized Difference Infrared Index, Relative Difference River Ice, and Vertical-Vertical/Vertical-Horizontal backscatter values based on the spectral and surface characteristics of rivers. The team produced annual freezing timelines, time series plots, and maps at three river stretches to analyze river ice phenology changes. Radar imagery assessed ice coverage more accurately, while optical imagery better identified ice onset dates. Meanwhile indices were unable to robustly establish ice formation thresholds across the study period. These study results can help the National Park Service to better evaluate spatiotemporal migratory shifts and contextualize recent regional caribou declines.

river phenology↗

Heterogeneous Outgassing Regions Identified on Active Centaur 29P/Schwassmann–Wachmann 1

Centaurs are transitional objects between primitive trans-Neptunian objects and Jupiter-family comets. Their compositions and activities provide fundamental clues regarding the processes affecting the evolution of and interplay between these small bodies. Here we report observations of centaur 29P/Schwassmann–Wachmann 1 (29P) with the James Webb Space Telescope (JWST). We identified localized jets with heterogeneous compositions driving the outgassing activity. We employed the NIRSpec mapping spectrometer to study the fluorescence emissions of CO and obtain a definitive detection of CO 2 for this target. The exquisite sensitivity of the instrument also enabled carbon and oxygen isotopic signatures to be probed. Molecular maps reveal complex outgassing distributions, such as jets and anisotropic morphology, which indicate that 29P’s nucleus is dominated by active regions with heterogeneous compositions. These distributions could reflect that it has a bilobate structure with compositionally distinct components or that strong differential erosion takes place on the nucleus. As there are no missions currently planning to visit a centaur, these observations demonstrate JWST’s unique capabilities in characterizing these objects.

Sara Faggi↗

The Application of Artificial Intelligence and Deep Learning to Visually Identify Micrometeoroid and Orbital Debris Impacts

Recent advancements in Artificial Intelligence (AI) have made Machine Learning (ML) techniques readily available for practical applications while using a fraction of time that was previously required. In particular, the use of Deep Learning (DL) algorithms has advanced the field of image and pattern recognition. With the use of Deep Learning algorithms, Micrometeoroid and Orbital Debris(MMOD) penetrations can be identified with high accuracy and give possibilities to new understandings of hypervelocity impacts.

Deep Learning↗

Nevada Wildland Fires: Mapping Historical Burned Areas and Identifying Drivers of Fuel Load Growth to Inform Desert Tortoise Habitat Management in Southern Nevada

Wildfire frequency and intensity in the Mojave desert are increasing, driven by invasive grasses that outcompete native vegetation not well-adapted to wildfire. These grasses, primarily cheatgrass (Bromus tectorum) and red brome (Bromus rubens), and the wildfires that occur when the grasses ignite, are a serious threat to the critically endangered Mojave desert tortoise (Gopherus agassizii). Declining Mojave desert tortoise populations are of great concern to project partners, the Bureau of Land Management Southern Nevada District Office, the US Forest Service’s Rocky Mountain Research Station, and the US Department of Agriculture Agricultural Research Service’s Arid Lands Ecology Lab, who currently lack the resources for fire recovery studies essential for informed fire and invasive grass management. To address this gap, the team utilized NASA Earth observations including Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), Terra MODIS, Landsat 5 Thematic Mapper (TM), and Landsat 8 Operational Land Imager (OLI), to analyze trends in burned areas over the past 20 years through historic burn maps and to examine fuel load growth drivers, with a focus on invasive vegetation. These historical burn maps revealed a pattern of precipitation anomalies that strongly correlate with higher Normalized Difference Vegetation Index (NDVI) values. Years with significant precipitation and NDVI spikes led to greater fuel load in the dry season and larger burns. Additionally, El Niño years correlated significantly with precipitation anomalies which may provide our partners with insights into burn trends and enable better allocation of fuel load treatment practices. However, while identifying drivers of fuel load growth proved feasible, a lack of in situ data hindered attempts to analyze pre-fire growth of invasive grasses compared with native grasses. Despite this limitation, the project demonstrated the feasibility of using Earth observations for wildfire and habitat management, ultimately benefiting conservation efforts for the Mojave desert tortoise.

fuel load↗

South Africa Ecological Conservation: Identifying and Mapping Riparian Areas in South Africa with Earth Observations

Riparian zones are thin strips of wetland that occur along the edges of rivers, lakes, and other water bodies. They provide many ecosystem and societal benefits such as stream bank stabilization, flood control, and habitat stability, making these zones very important areas to preserve and protect. Recognizing the need to accurately map these ecosystems in a cost-effective way, we partnered with the South African National Biodiversity Institute (SANBI) and the Biodiversity Survey of the Cape(BioSCape) to develop a GI methodology using Esri's ArcGIS Pro and data from Landsat 9 Operational Land Imager-2, Sentinel-2 Multispectral Instrument, and the Shuttle Radar Topography Mission to identify potential riparian zones (PRZ) and observed riparian vegetation(ORV) in the Southern Cape and the North West Province of South Africa to estimate the actual riparian vegetation (ARV) within those areas. Potential riparian ecosystems were calculated by utilizing a Topographic Wetness Index (TWI) and a water feature layer, while observed riparian vegetation were calculated by overlaying a Normalized Difference Vegetation Index (NDVI) and TWI. Actual Riparian Vegetation is determined by the overlap of ORV with PRZ and is done with conditional statements; ORV within PRZ is ARV. This method significantly improved a current riparian land cover classification since it combined high resolution optical imagery and topographic data. We anticipate such maps will be used by conservationists and practitioners interested in riparian monitoring and management.

Remote Sensing↗

Identifying Cognitive Capabilities Required for Optimal Exploration EVA Performance: A Cognitive Task Analysis

BACKGROUND Extravehicular activity (EVA) is one of the most dangerous and cognitively demanding actions that astronauts can execute, and the cognitive demands associated with future exploration EVA on the Moon and Mars are expected to be higher compared to EVA currently conducted from the International Space Station (ISS). Decrements in cognitive performance present an important risk to crew safety during exploration mission class EVA. Yet there is currently insufficient characterization of the cognitive capabilities required prior to, during, and following EVA. Furthermore, it is unclear which cognitive domains are most important for conducting mission critical decisions with crew safety implications. To address this gap, we conducted a cognitive task analysis of exploration EVA to characterize the cognitive capabilities, critical safety decisions, and contributing factors (e.g., lunar communications delay) important to monitor for optimal performance in future exploration EVA. This cognitive task analysis was conducted through interviews with astronauts and subject matter experts in EVA research and operations. Interviews focused on exploration EVA and elicited feedback on the cognitive capabilities required for specific EVA tasks and subtasks. The information from this cognitive task analysis will help close the gap in our understanding of the key cognitive capabilities required for safe decision-making during exploration mission class EVA on the Moon and Mars. METHOD We used an applied cognitive task analysis method1 over the course of interviews with a total of 15 NASA astronauts and subject matter experts in EVA. Each interview was led by a scientist with expertise in cognitive neuroscience from the Behavioral Health & Performance (BHP) Laboratory at NASA Johnson Space Center. Notes were taken by a research coordinator in the BHP Laboratory and interviews were recorded on Microsoft Teams to ensure the accuracy of notetaking. In the first interview protocol, participants were asked about the specific tasks and cognitive demands associated with EVA. This provided a high-level overview of the steps involved in the major tasks conducted during exploration EVA, as well as which of the steps require the most cognitive skill. Next, participants completed a knowledge audit, which employs a set of probes designed to describe types of domain knowledge of skill and elicit appropriate examples. In the second interview protocol, completed with a separate set of subject matter experts, interviewees were asked to complete a simulated incapacitated crew rescue (ICR) scenario2, which provided specific context that allowed probing around relevant issues such as situational awareness and potential errors. Experts were then asked to identify the knowledge, skills, and abilities (KSAs) underlying each EVA task and to provide ratings on the importance and cognitive demand of each KSA. Finally, participants also described the most likely and consequential critical safety incidents related to decrements in cognitive performance during exploration EVA and assessed the impact of lunar communication delay on cognitive performance. RESULTS & DISCUSSION Interviews for this cognitive task analysis are nearly complete and results will be presented in full at IWS 2025. Results will include a summary of all expert ratings of EVA tasks and subtasks, qualitative summaries of content from each interview part, and a discussion of future directions for products addressing cognitive performance monitoring and cognitive domain mapping in exploration EVA.

S R Anderson↗

Monitoring and Assessing Heat Vulnerability to Identify Locations for Heat Mitigation Efforts in Sarasota, Florida

Located in the coastal subtropical region, Florida’s Sarasota County receives plenty of sunlight for more than half of the year. However, the ongoing rise in summer temperatures attributed to climate change poses an increasing vulnerability to extreme heat for the residents. Moreover, the area's high relative humidity exacerbates the discomfort of high temperatures, thereby intensifying the severity of heat events and elevating the risks of heat-related illnesses. Our collaborations with Sarasota County Sustainability underscore shared concerns about the impact of urban heat island (UHI) on the community. We utilized Earth observation data from NASA Landsat 8 and Landsat 9’s Thermal Infrared Sensors (TIRS) and the International Space Station’s Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) to model UHI effects within the county during the summer from 2019 to 2023. By implementing the open-source Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling software model, ArcGIS ModelBuilder, and principal component analysis, we identified the land surface temperature variance within the county and areas that are least capable of mitigating the effects of UHI. In addition, we use socioeconomic and demographic data as indicators to quantify vulnerability at the census tract level. The results revealed that heat intensity varies significantly across Sarasota County, with the highest temperatures being in the more developed western part of the region. We pinpointed that at least three vulnerable communities reside in high-heat regions: North Sarasota, Venice, and North Port. These areas demonstrate a confluence between socioeconomic sensitivity and environmental hazard, indicating a high priority in future heat mitigation efforts.

Theresia Phoa↗

Identifying Trends in Landing Profiles After Long Duration Spaceflight

BACKGROUND As NASA’s mission programs begin to shift from Low Earth Orbit (LEO) to planetary mission profiles, the importance of understanding the phenomena a human experience when returning from spaceflight is of increased importance. The purpose of this study was to assess trends across individuals in the symptoms experienced during the landing process of long duration ISS missions. METHODS Data for this study is an aggregation of mission level data from forms used by crew surgeons at R+0, electronic medical records, notes from weekly Space Medicine Operation Team meetings, records in the Shuttle Mission Data Archive, and data collected by research teams in the Human Research Program (HRP). Aggregated data was used in descriptive analysis of the trends in medical events and countermeasure use. The data was also used to identify high value targets for emphasis in on going surveillance efforts. RESULTS Completeness of reporting varied greatly over time and across missions dependent on information sources available for data extraction. Landing forms provided the most complete data but still missed or left unconfirmed, several, common symptoms, and countermeasures. Data aggregation did show to cover gaps within individual data sources. Commonly reported symptoms included nystagmus, vertigo, and nausea. Common protocols for fluid loading and meclizine are reflected within the data set. DISCUSSION The data set generated in this project provides a foundation that show how symptoms of astronauts as they return to Earth varies across the long duration ISS missions. While there is an abundance of information provided within the data set, there are still inconsistencies in reporting especially in the absence of the landing day form. Further data collection practices should be standardized to ease the burden on crew surgeons during R+0 exams and better collect high value variables.

Sam Jacobs↗

San José Urban Development: Quantifying Canopy Cover and Land Surface Temperature in San José to Identify Future Tree Planting Sites

The urban heat island effect refers to the phenomenon of substantially increased temperatures in urban areas compared to their surrounding suburban or rural counterparts. The City of San José’s Department of Parks, Recreation and Neighborhood Services (PRNS) and Department of Transportation (DOT) work to mitigate the UHI effect through urban forestry initiatives. The PRNS and DOT partnered with NASA DEVELOP to identify areas in need of tree plantings. We examined land surface temperature (LST) throughout the city using data from the Thermal Infrared Sensor (TIRS) and TIRS-2 on NASA’s Landsat 8 and 9 satellites from 2013 to 2024. We also assessed canopy cover in parks using LiDAR data collected in 2020 for the United States Geological Survey’s 3D Elevation Program, and measured vegetation greenness using the Normalized Difference Vegetation Index (NDVI) with PlanetScope imagery from 2018 to 2024. We evaluated social and environmental factors that influence the distribution of heat event impacts by creating a heat vulnerability index. We found that heat is concentrated in urban areas and that poor vegetation health is associated with high LST. We also found that socially vulnerable communities are disproportionately located in areas of high environmental risk. These analyses allow the partners to prioritize tree plantings in parks near areas of high social and environmental risk. We determined that Earth observations can be used to inform urban forestry decision making, but because methodologies for using LiDAR to assess canopy cover vary greatly, it is difficult to make comparisons across different canopy cover assessments.

land surface temperature↗

Systems and methods for automatically identifying and linking names in digital resources

The present invention provides systems and methods for automatically identifying name-like-strings in digital resources, matching these name-like-string against a set of names held in an expertly curated database, and for those name-like-strings found in said database, enhancing the content by associating additional matter with the name, wherein said matter includes information about the names that is held within said database and pointers to other digital resources which include the same name and it synonyms.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Potential economic values of minerals in brines of identified hydrothermal systems in the US

Geothermal resources have been used as a clean and sustainable baseload power for a long time. However, the upfront deployment costs of geothermal technologies are high. Various approaches are considered to make geothermal energy more economically attractive for developers. One potential approach is to have an additional revenue stream through recovery minerals from the large volume of brine that is used to generate power at geothermal sites. Geothermal brines interact with rocks for a long time at high temperature and pick up minute levels of various minerals, such as SiO2, Li, Mn, Cs, etc. In this paper, we assess the mineral contents in brines of several identified hydrothermal resource areas in the US. The compositions of geothermal brines were assembled from various sources whereas the brine mass flow rates of the potential power plants in those hydrothermal areas were obtained from GETEM simulations. Our study shows that several value-adding minerals could be available for recovery from the geothermal brines in the US. Specially, potential revenues from recovery of Au, Cs, Rb, Li, and SiO2 look very promising for several hydrothermal systems. However, several outstanding technological, financial, and market challenges as well as site-specific challenges (e.g., chemistry, sustainability, etc.) need to be evaluated for economic recovery of targeted minerals.

15 GEOTHERMAL ENERGY↗

Thin-Film Module Reverse-Bias Breakdown Sites Identified by Thermal Imaging: Preprint

Thin-film module sections are stressed under reverse bias to simulate partial shading conditions. Such stresses can cause permanent damage in the form of 'wormlike' defects due to thermal runaway. When large reverse biases with limited current are applied to the cells, dark lock-in thermography (DLIT) can detect where spatially-localized breakdown initiates before thermal runaway leads to permanent damage. Predicted breakdown defect sites have been identified in both CIGS and CdTe modules using DLIT. These defects include small pinholes, craters, or voids in the absorber layer of the film that lead to built-in areas of weakness where high current densities may cause thermal damage in a partial-shading event.

14 SOLAR ENERGY↗

Thin-Film Module Reverse-Bias Breakdown Sites Identified by Thermal Imaging

Thin-film module sections are stressed under reverse bias to simulate partial shading conditions. Such stresses can cause permanent damage in the form of 'wormlike' defects due to thermal runaway. When large reverse biases with limited current are applied to the cells, dark lock-in thermography (DLIT) can detect where spatially-localized breakdown initiates before thermal runaway leads to permanent damage. Predicted breakdown defect sites have been identified in both CIGS and CdTe modules using DLIT. These defects include small pinholes, craters, or voids in the absorber layer of the film that lead to built-in areas of weakness where high current densities may cause thermal damage in a partial-shading event.

14 SOLAR ENERGY↗

Identifying an arc-fault type in photovoltaic arrays

An apparatus, method, and system for detecting arc-faults in a photovoltaic array are disclosed. Further, the detection not only identifies that an arc-fault is present in the array, but also classifies whether the arc-fault is a series type arc-fault or a parallel type arc-fault. Upon determination of the specific type of arc-fault that is at issue, de-energizing the arc-fault specific to the type is selected and carried out.

42 ENGINEERING↗

Rheological evaluation of high temperature polymers to identify successful extrusion parameters

With the advancements in additive manufacturing (AM), several high temperature thermoplastics are being explored as potential AM feedstocks. Some of these high-performance thermoplastics include; polyetherimides (PEI), polyphenylsulfones (PPSU/F), poly(ether ketone ketone)s (PEKK) and polyphenylene sulfide (PPS) as well as their reinforced composites. Most of these advanced resins tend to be more expensive than commodity plastics such as acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA), and their processing parameters have not been determined for most AM systems. This paper demonstrates a method for identifying the appropriate processing conditions for extrusion-based AM deposition systems, in which a material is forced through an orifice at a given flow rate. The pressure required to extrude a shear-thinning thermoplastic at a given shear rate is calculated based on viscoelastic properties of the polymer melt and compared against maximum system pressure to predict successful extrusion. An evaluation of several candidate materials is presented on the Big Area Additive Manufacturing extrusion-based platform.

Ajinjeru, Christine↗

Systems and methods for automatically identifying and linking names in digital resources

The present invention provides systems and methods for automatically identifying name-like-strings in digital resources, matching these name-like-string against a set of names held in an expertly curated database, and for those name-like-strings found in said database, enhancing the content by associating additional matter with the name, wherein said matter includes information about the names that is held within said database and pointers to other digital resources which include the same name and it synonyms.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗