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At least 145 records · Page 8

Emissions Characterization and Smoke Transport of A Prescribed Fire

Under the background of climate change, vast regions of the world will face a hotter and probably drier future that favors ignition and spread of wildfires. This poses additional challenges to the communities who are fighting the ever-larger wildfires. Fire and smoke models are valuable tools to fire managers and decision-makers to mitigate the impact of fires. Existing fire modeling systems bear large uncertainties due to the difficulty in collecting data to characterize fire behavior and smoke transport. More observations are urgently needed for improvement of fire modeling and reduction in model uncertainty. The coordinated prescribed burn experiment, such as the Fire and Smoke Model and Measurement Evaluation Experiment (FSMMEE), will allow the concurrent collection of critical measurements of fuel, fire behavior, smoke, and meteorology to better understand and model fires. In this preliminary investigation, we employed the data from the prescribed burn experiment at Langdon Mountain, Utah, in November 2019, to reconstruct the fire emissions and characterize the smoke transport. The NASA Unified Weather Research and Forecasting Model (NU-WRF) was utilized to assist in identifying the potential pre-fire remote sensing capabilities, such as fuel load, moisture, and fire radiative power, which are helpful to model development and advancement. Along the way, two sets of NU-WRF experiments would be done by applying either a default fire emissions inventory (i.e., NASA’s Quick Fire Emissions Dataset, QFED) or reconstructed fire emissions using the data collected from the prescribed fire. The results would help answer the questions such as “How do reconstructed emissions compare to QFED emissions and their impact on plume transport”.

NU-WRF↗

Coordinating an Autonomous Earth-Observing Sensorweb

A system of software has been developed to coordinate the operation of an autonomous Earth-observing sensorweb. Sensorwebs are collections of sensor units scattered over large regions to gather data on spatial and temporal patterns of physical, chemical, or biological phenomena in those regions. Each sensor unit is a node in a data-gathering/ data-communication network that spans a region of interest. In this case, the region is the entire Earth, and the sensorweb includes multiple terrestrial and spaceborne sensor units. In addition to acquiring data for scientific study, the sensorweb is required to give timely notice of volcanic eruptions, floods, and other hazardous natural events. In keeping with the inherently modular nature of the sensory, communication, and data-processing hardware, the software features a flexible, modular architecture that facilitates expansion of the network, customization of conditions that trigger alarms of hazardous natural events, and customization of responses to alarms. The soft8 NASA Tech Briefs, July 2006 ware facilitates access to multiple sources of data on an event of scientific interest, enables coordinated use of multiple sensors in rapid reaction to detection of an event, and facilitates the tracking of spacecraft operations, including tracking of the acquisition, processing, and downlinking of requested data.

Sherwood, Robert↗

CRRES experiments, data collection, analysis and publication

The tasks undertaken to be performed under this contract included the continued coordination and documentation of the CRRES program and the development of an archive that details the experimental results obtained by the CRRES Program. Details of the work undertaken and results achieved are summarized in the following sections.

Miller, George P.↗

The NASA Biological Institutional Scientific Collection (NBISC): Tissue and Microbe Biospecimens to Advance Space Research

The NASA Biological Institutional Scientific Collection (NBISC) is a biorepository of non-human biospecimens from NASA-funded spaceflight investigations and correlative ground studies. The collection has its roots in the 1960s through collaborations by NASA Ames Research Center with other NASA centers, universities, and international space agencies by sharing non-human biospecimens from spaceflight and space-relevant ground experiments. These collaborations have advanced the field of space exploration by helping to maximize the data gained from spaceflight and other NASA-funded experiments. NBISC coordinates closely with the Biospecimen Sharing Program (BSP) which is responsible for organized sample collection from spaceflight and ground rodent experiments. In 2022 NBISC partnered with HRP’s Biospecimen and Tissue Sharing Collection (BTSC) Program to also archive samples from HRP’s Space Radiation Element-funded studies which primarily involve rodents exposed to various radiation protocols at the NASA Space Radiation Laboratory (NSRL) and other analog facilities. To date, more than fifty thousand biospecimens from BTSC have been transferred to NBISC for distribution to the community. In 2023, NBISC embarked on a new Space Biology funded endeavor to create the Space Microbial Culture Collection (SMCC) which will serve as a central repository for microbial isolates associated with space flight, gravitational, and space radiation research. This presentation will highlight several success stories of analyses carried out using archived NBISC samples received by researchers in recent years and will detail the process for proposing and receiving samples from NBISC, BTSC and SMCC. Making available these 150,000+ unique biospecimens to the scientific research community, NBISC not only serves as a repository for storing and distributing non-human biospecimens, but also acts as a resource to enable new discoveries that will benefit NASA and humankind.

NBISC↗

The NASA Biological Institutional Scientific Collection (NBISC): Tissue and Microbe Biospecimens to Advance Space Research

The NASA Biological Institutional Scientific Collection (NBISC) is a biorepository of non-human biospecimens from NASA-funded spaceflight investigations and correlative ground studies. The collection has its roots in the 1960s through collaborations by NASA Ames Research Center with other NASA centers, universities, and international space agencies by sharing non-human biospecimens from spaceflight and space-relevant ground experiments. These collaborations have advanced the field of space exploration by helping to maximize the data gained from spaceflight and other NASA-funded experiments. NBISC coordinates closely with the Biospecimen Sharing Program (BSP) which is responsible for organized sample collection from spaceflight and ground rodent experiments. In 2022 NBISC partnered with HRP’s Biospecimen and Tissue Sharing Collection (BTSC) Program to also archive samples from HRP’s Space Radiation Element-funded studies which primarily involve rodents exposed to various radiation protocols at the NASA Space Radiation Laboratory (NSRL) and other analog facilities. To date, more than fifty thousand biospecimens from BTSC have been transferred to NBISC for distribution to the community. In 2023, NBISC embarked on a new Space Biology funded endeavor to create the Space Microbial Culture Collection (SMCC) which will serve as a central repository for microbial isolates associated with space flight, gravitational, and space radiation research. This presentation will highlight several success stories of analyses carried out using archived NBISC samples received by researchers in recent years and will detail the process for proposing and receiving samples from NBISC, BTSC and SMCC. Making available these 150,000+ unique biospecimens to the scientific research community, NBISC not only serves as a repository for storing and distributing non-human biospecimens, but also acts as a resource to enable new discoveries that will benefit NASA and humankind.

Biospecimen↗

Evolving Multi Rover Systems in Dynamic and Noisy Environments

In this chapter, we address how to evolve control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the performance of the full system. Addressing such problems by directly applying a global evolutionary algorithm to a population of collectives is unworkable because the search space is prohibitively large. Instead, we focus on evolving control policies for each member of the collective, where each member is trying to maximize the fitness of its own population. The main difficulty with this approach is creating fitness evaluation functions for the members of the collective that induce the collective to achieve high performance with respect to the system level goal. To overcome this difficulty, we derive member evaluation functions that are both aligned with the global evaluation function (ensuring that members trying to achieve high fitness results in a collective with high fitness) and sensitive to the fitness of each member (a member's fitness depends more on its own actions than on actions of other members). In a difficult rover coordination problem in dynamic and noisy environments, we show how to construct evaluation functions that lead to good collective behavior. The control policy evolved using aligned and member-sensitive evaluations outperforms global evaluation methods by up to a factor of four. in addition we show that the collective continues to perform well in the presence of high noise levels and when the environment is highly dynamic. More notably, in the presence of a larger number of rovers or rovers with noisy sensors, the improvements due to the proposed method become significantly more pronounced.

Tumer, Kagan↗

BOREAS Level-1B MAS Imagery At-sensor Radiance, Relative X and Y Coordinates

For BOReal Ecosystem-Atmosphere Study (BOREAS), the MODIS Airborne Simulator (MAS) images, along with the other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes detailed land cover and biophysical parameter maps such as fraction of Photosynthetically Active Radiation (fPAR) and Leaf Area Index (LAI). Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-1b MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994, and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C-130 INS data in a MAS scan model. The data are provided in binary image format files.

Strub, Richard↗

Analysis of the profile characteristics of corn and soybeans using field reflectance data

The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to LANDSAT-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.

Crist, E. P.↗

Cultural and environmental effects on crop spectral development patterns as viewed by Landsat

The typical patterns of spectral development (profiles) for corn and soybeans are presented, based on field-collected reflectance data transformed to correspond to Landsat-MSS Tasseled Cap coordinates. Reasonable variations in field conditions and cultural practices are shown to significantly influence profile features. The separability of the two crops is determined to be primarily related to the maximum value of the reflectance equivalent of Greenness, and to the plateau effect seen in corn Greenness profiles. The impact of changes in conditions on separability is described. In addition, association is made between profile features and stages of development for corn and soybeans. Corn is shown to peak at a stage well before tasseling or maximum LAI, while the characteristics of the soybean profile are shown to be unrelated to any particular stage of development.

Crist, E. P.↗

International Halley Watch: Discipline specialists for spectroscopy and spectrophotometry

Spectroscopic observations of Comets P/Crommelin, P/Giacobini-Zinner and P/Halley are coordinated, preliminary results are delivered to the astronomical community and the data collected from observers throughout the world are archived. The ASU IHW Center has the additional responsibility of maintaining the IHW Electronic Bulletin Board which reports real-time information on the status of Comet P/Halley. Access to this electronic bulletin board via telephone modem connection is available to any astronomer upon request.

Wyckoff, S.↗

Comparison of Nickel XANES Spectra and Elemental Maps from a Ureilite, a LL3.8 Ordinary Chondrite, Two Carbonaceous Chondrites and Two Large Cluster IDPs

Nickel in the extraterrestrial world is commonly found in both Fe-Ni sulfide and Fe-Ni met-al forms [1] and in the pure metal state in the interior of iron meteorites where it is not easily oxidized. Ni is also found in olivine, pyroxene and glasses and in some melts the partitioning of Ni between the olivines and glass is controlled by the amount of S in the melt [2]. Its most common valence state is Ni(2+) but Ni also occurs as Ni(0), Ni(+), and Ni(3+) and rarely as Ni(2-), Ni(1-) and Ni(4+) [3]. It's valence state in olivines is Ni(2+) in octa-hedral coordination on the M1 site and rarely on the M2 site.[4]. The chemical sensitivity of X-ray absorp-tion near-edge structure (XANES) spectroscopy is well established and can be used to determine not only va-lence states but also coordination sites [5]. We report here Ni XANES spectroscopy and elemental maps collected from 2 carbonaceous chondrites, 2 large clus-ter IDPs, 1 ureilite and 1 LL3 orginary chondrite.Using XANES it may be possible to find a common trait in the large cluster IDPs that will also be found in mete-orite samples.

Wirick, S.↗

Developing a Set of Indicators to Identify, Monitor, and Track Impacts and Change in Forests of the United States

United States forestland is an important ecosystem type, land cover, land use, and economic resource that is facing several drivers of change including climatic. Because of its significance, forestland was identified through the National Climate Assessment(NCA) as a key sector and system of concern to be included in a system of climate indicators as part of a sustained assessment effort. Here, we describe 11 informative core indicators of forests and climate change impacts with metrics available or nearly available for use in the NCA efforts. The recommended indicators are based on a comprehensive conceptual model which recognizes forests as a land use, an ecosystem, and an economic sector. The indicators cover major forest attributes such as extent, structural components such as biomass, functions such as growth and productivity, and ecosystem services such as biodiversity and outdoor recreation. Interactions between humans and forests are represented through indicators focused on the wildland-urban interface, cost to mitigate wildfire risk, and energy produced from forest-based biomass. Selected indicators also include drought and disturbance from both wildfires and biotic agents. The forest indicators presented are an initial set that will need further refinement in coordination with other NCA indicator teams. Our effort ideally will initiate the collection of critical measurements and observations and lead to additional research on forest-climate indicators.

U.S. forests↗

Maximizing the Volume of Collocated Data from Two Coordinated Suborbital Platforms

Suborbital (e.g., airborne) campaigns that carry advanced remote sensing and in situ payloads provide detailed observations of atmospheric processes, but can be challenging to use when it is necessary to geographically collocate data from multiple platforms that make repeated observations of a given geographic location at different altitudes. This study reports on a data collocation algorithm that maximizes the volume of collocated data from two coordinated suborbital platforms and demonstrates its value using data from the NASA Aerosol Cloud Meteorology Interactions Over the western Atlantic Experiment (ACTIVATE) suborbital mission. A robust data collocation algorithm is critical for the success of the ACTIVATE mission goal to develop new and improved remote sensing algorithms, and quantify their performance. We demonstrate the value of these collocated data to quantify the performance of a recently developed vertically resolved lidar + polarimeter–derived aerosol particle number concentration (Na ) product, resulting in a range-normalized mean absolute deviation (NMAD) of 9% compared to in situ measurements. We also show that this collocation algorithm increases the volume of collocated ACTIVATE data by 21% compared to using only nearest-neighbor finding algorithms alone. Additional to the benefits demonstrated within this study, the data files and routines produced by this algorithm have solved both the critical collocation and the collocation application steps for researchers who require collocated data for their own studies. This freely available and open-source collocation algorithm can be applied to future suborbital campaigns that, like ACTIVATE, use multiple platforms to conduct coordinated observations, e.g., a remote sensing aircraft together with in situ data collected from suborbital platforms.

Atmosphere↗

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

NASA's Small Spacecraft and Distributed Systems: Development and Demonstration of Technologies Enabling Swarms and New Spacecraft Platforms with AI and Edge Computing

NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.

Jan Stupl↗

Coordinated Microanalyses of Seven Particles of Probable Interstellar Origin from the Stardust Mission

Stardust, a NASA Discovery-class mission, was the first sample-return mission to return solid samples from beyond the Moon. Stardust was effectively two missions in one spacecraft: it returned the first materials from a known primitive solar system body, the Jupiter-family comet Wild 2; Stardust also returned a collector that was exposed to the contemporary interstellar dust stream for 200 days during the interplanetary cruise. Both collections present severe technical challenges in sample preparation and in analysis. By far the largest collection is the cometary one: approximately 300 micro g of material was returned from Wild 2, mostly consisting of approx. 1 ng particles embedded in aerogel or captured as residues in craters on aluminum foils. Because of their relatively large size, identification of the impacts of cometary particles in the collection media is straightforward. Reliable techniques have been developed for the extraction of these particles from aerogel. Coordinated analyses are also relatively straightforward, often beginning with synchrotron-based x-ray fluorescence (S-XRF), X-ray Absorption Near-Edge Spectoscopy (XANES) and x-ray diffraction (S-XRD) analyses of particles while still embedded in small extracted wedges of aerogel called ``keystones'', followed by ultramicrotomy and TEM, Scanning Transmission X-ray Microscopy (STXM) and ion microprobe analyses (e.g., Ogliore et al., 2010). Impacts in foils can be readily analyzed by SEM-EDX, and TEM analysis after FIB liftout sample preparation. In contrast, the interstellar dust collection is vastly more challenging. The sample size is approximately six orders of magnitude smaller in total mass. The largest particles are only a few pg in mass, of which there may be only approx.10 in the entire collection. The technical challenges, however, are matched by the scientific importance of the collection. We formed a consortium carry out the Stardust Interstellar Preliminary Examination (ISPE) to carry out an assessment of this collection, partly in order to characterize the collection in sufficient detail so that future investigators could make well-informed sample requests. The ISPE is the sixth PE on extraterrestrial collections carried out with NASA support. Some of the basic questions that we asked were: how many impacts are there in the collector, and what fraction of them have characteristics consistent with extraterrestrial materials? What is the elemental composition of the rock-forming elements? Is there crystalline material? Are there organics? Here we present coordinated microanalyses of particles captured in aerogel, using S-FTIR, S-XRF, STXM, S-XRD; and coordinated microanalyses of residues in aluminum foil, using SEMEDX, Auger spectroscopy, STEM, and ion microprobe. We discuss a novel approach that we employed for identification of tracks in aerogel, and new sample preparation techniques developed during the ISPE. We have identified seven particles - three in aerogel and four in foils - that are most consistent with an interstellar origin. The seven particles exhibit a large diversity in elemental composition. Dynamical evidence, supported supported by laboratory simulations of interstellar dust impacts in aerogel and foils, and numerical modeling of interstellar dust propagation in the heliosphere, suggests that at least some of the particles have high optical cross-section, perhaps due to an aggregate structure. However, the observations are most consistent with a variety of morphologies

Westphal, Andrew J.↗

Investigation of single-event upset (SEU) in an advanced bipolar process

An extensive analytical and experimental study SEU in an advanced silicon bipolar process was made. The modeling used process and device parameters to model the SEU charge, collection, and circuit response derived from a special version of PISCES in cylindrical coordinates and SPICE, respectively. Data are reported for test cells of various sizes.

Zoutendyk, John A.↗

Ames Research Center C-130

The C130 Earth Resources Aircraft provides a platform for a variety of sensors that collect data in support of terrestrial and atmospheric projects sponsored by NASA in coordination with Federal, state, university, and industry investigators. This data is applied to research in the areas of forestry, agriculture, land use and land cover analysis, hydrology, geology, photogrammetry, oceanography, meteorology, and other earth science disciplines. The C130 is a platform aircraft flying up to 25,000 feet above sea level at speeds between 150 and 330 knots True Air Speed. The aircraft is capable of precise flight line navigation by means of an optical borescope from which line guidance is provided to the pilots.

Koozer, Mark A.↗