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A Data & Reasoning Fabric shall provide a set of secured software infrastructure, tools, protocols, governance and policies to implement, administer, manage and operate data sharing and reasoning services across the entire span of air mobility and other ”smart” edge nodes.
The smalltooth sawfish Pristis pectinata is an endangered species endemic to the Atlantic Ocean. The only known viable populations occur in the USA along both coasts of Florida and in the western Bahamas. Little is known about habitat use and movement ecology of large juvenile and adult smalltooth sawfish. Although Critical Habitat — a management designation in the USA — has been identified for small juveniles, it has yet to be identified for these life stages. Between May 2016 and April 2019, we used passive acoustic telemetry and 3 large data sharing networks of receivers to track movements of 43 large juvenile and adult smalltooth sawfish. During this study, 24 females and 19 males were implanted with transmitters with estimated 4 or 10 yr battery lives. These tagged individuals were detected off the southeastern USA on 461 receivers ranging from off the coast of Brunswick, Georgia, to the lower Florida Keys, and along the Gulf coast to Apalachee Bay, Florida. Seasonal migrations were undertaken by 58% (43% mature; 57% immature) of the tagged individuals, with the remainder being apparent residents of their tagging locations. Tagged sawfish from both size classes and of both sexes migrated, which indicates that neither sex nor length is a predictor of whether a sawfish will migrate or not. Although both coasts of Florida were used for migration, most individuals consistently used the same coast when they migrated. The areas surrounding Boca Grande, Cape Canaveral, and the lower Florida Keys were heavily visited sites that could be further evaluated as potential Critical Habitat for these life stages. Understanding the movement patterns of this Critically Endangered species is essential for creating policies to protect areas important for promoting growth of the population.
At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to develop and share best practices and methodologies across NASA. One such cutting edge methodology is Physics of Failure. Therefore NASA OSMA's R&M office is developing a Reliability Physics of Failure Handbook in order to keep our engineers current and on the cutting edge of anlayis methodologies to help ensure NASA’s optimize and achieve continued success.
China's fossil-fuel CO2 (FFCO2) emissions accounted for approximately 28 % of the global total FFCO2 in 2016. An accurate estimate of China's FFCO2 emissions is a prerequisite for global and regional carbon budget analyses and the monitoring of carbon emission reduction efforts. However, significant uncertainties and discrepancies exist in estimations of China's FFCO2 emissions due to a lack of detailed traceable emission factors (EFs) and multiple statistical data sources. Here, we evaluated China's FFCO2 emissions from nine published global and regional emission datasets. These datasets show that the total emissions increased from 3.4 (3.0–3.7) in 2000 to 9.8 (9.2–10.4) Gt CO2 per yr in 2016. The variations in these estimates were largely due to the different EF (0.491–0.746 t C per t of coal) and activity data. The large-scale patterns of gridded emissions showed a reasonable agreement, with high emissions being concentrated in major city clusters, and the standard deviation mostly ranged from 10 % to 40 % at the provincial level. However, patterns beyond the provincial scale varied significantly, with the top 5 % of the grid level accounting for 50 %–90 % of total emissions in these datasets. Our findings highlight the significance of using locally measured EF for Chinese coal. To reduce uncertainty, we recommend using physical CO2 measurements and use these values for dataset validation, key input data sharing (e.g., point sources), and finer-resolution validations at various levels.
Space exploration on planetary surfaces will require the use of various surface systems which will likely need to interface with one another. These systems must communicate and share data, as well as distribute power and transfer fluids for sustainable surface operations. Such systems can range from landers, surface habitats, mobility systems, cargo, and In-Situ Resource Utilizations (ISRUs). Previous and current programs have developed space interoperability standards that help aid in reducing potential risks of interface integration. One example of this is the International Deep Space Interoperability Standards (IDSIS) which focuses on deep space exploration. A goal of the Artemis program is to develop a sustained human presence on the lunar surface that would be a training ground for future Mars exploration. Therefore, it will be beneficial to identify interface standards between the surface assets which will help mitigate risk and reduce complexity in the harsh environments of space exploration. A key contribution to sustainability is commonality between hardware and software interfaces. Generic interfaces for data, power, and fluids will reduce risk, promote interoperability, and define standard interfaces across surface exploration projects and programs. Standardized interfaces would be advantageous for improving efficiency and reducing overall complexity, which are critical considerations for future space exploration. Furthermore, it will provide cost reductions to the Artemis programs over their life cycle (in Operations & Maintenance (O&M) and Logistics). Unique proprietary interfaces if considered or allowed would not only increase complexity but also add cost to the programs. Of course, understanding what will work and not work effectively in these unique environments such as the lunar surface is important. These unique environments require much needed intelligent design, prototyping, comprehensive testing, and field experience, utilizing consensus on common interface solutions.
At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to develop and share best practices and methodologies across NASA. One such cutting edge methodology is Physics of Failure. Therefore NASA OSMA's R&M office is developing a Reliability Physics of Failure Handbook in order to keep our engineers current and on the cutting edge of analysis methodologies to help ensure NASA’s optimize and achieve continued success. "
We are proposing a technology demonstration mission for JPL’s Inter-Satellite Optical Communicator (ISOC). The ISOC has the potential to enable up to 1 Gbps data rates over a distance up to 200 km in free space. Key features of the ISOC include full sky coverage and the ability to maintain multiple links simultaneously. The Q4 mission consists of (4) 6U CubeSats furnished with ISOCs to demonstrate high data rate communications among the spacecraft. More specifically, we seek to demonstrate the omnidirectionality of the ISOC by providing simultaneous optical links between one spacecraft and the other three. Q4 will be a demonstrator for small spacecraft swarm capabilities. Following a proposed deployment from the ISS, the CubeSats will utilize their onboard thrusters to enter their desired orbit. The orbit consists of one “leader” spacecraft in a circular orbit with a 400 km LEO altitude and three “follower” spacecraft in slightly elliptical orbits rotating azimuthally about the leader. The main mission will consist of three consecutive phases: First, the spacecraft will demonstrate pointing, acquisition, and tracking using newly developed protocols. Next, link establishment and different channel access methods (CDMA and TDMA) will be tested. Finally, Delay Tolerant Network protocols will be implemented to allow fast data sharing among the spacecraft. The distance between the communicating spacecraft will be increased as the mission progresses to characterize the link quality as a function of distance. All communications over the course of the mission will be recorded and analyzed on the ground using bit error rate as a metric for success. The current design for each the four Q4 CubeSats contains an XACT advanced ADCS system for precision beam pointing. Other components currently under consideration include MiPS cold gas thrusters for orbital maneuvering and gimbaled eHaWK 84W solar arrays. In this paper we present design considerations for the Q4 CubeSats, link budget calculations, results from preliminary mission analysis, and expected results.
The purpose of this abstract is to share data from preliminary modeling of meteor dynamics of the 08 Jan 2014 bolide which occurred north of Papua New Guinea as reported by US Department of Defense (DoD) sensors. A hypothesis has been proposed that this event was of interstellar origin. DoD data indicate that this bolide was produced by a meteor moving 44.8 km/s at only 18.7 km altitude, which describes a velocity profile that is exceptional in velocity, much less at such a low altitude. The Jörmungandr model developed by the author for dark flight modeling was adapted to estimate the luminous flight profile of this body. While this model has significant limits in use for luminous flight and all results must be viewed as preliminary, analysis indicates there is a compelling need for further investigation. Calculation of ram pressure by this object indicate that an iron or iron-rich meteorite 0.5m in diameter is a possible explanation for the reported DoD data.
In the last three years, several advancements have been made to produce a new state-of-the-art capability in the field of Aerosciences. NASA’s Aerosciences Evaluations and Test Capabilities (AETC) Portfolio Office has funded a multi-year project to produce the unsteady Pressure-Sensitive Paint (uPSP) technology as an operational capability in key ground test facilities at NASA. The research and development has primarily been conducted at NASA Ames Research Center’s (ARC) Unitary Plan Wind Tunnel (UPWT) 11-by 11-ft Transonic Wind Tunnel (TWT). The NASA ARC UPWT is one of the ground test facilities under NASA AETC’s Portfolio Office. AETC’s goals are to provide the tools to deliver the technology innovations and breakthroughs necessary to address increasingly complex research and development challenges. AETC’s integrated approach will consider the complimentary high-end compute capabilities necessary to advance analysis in conjunction with ground experimental capabilities. The uPSP Capability Challenge Project is a demonstration of several different technologies: 1) the unsteady Pressure-Sensitive Paint (uPSP) technology, and 2) Project: Red Rover, establishing a secure, reliable, fast connection between experimental and computation facilities, leveraging NASA’s computational resources within the High-End Compute Capability (HECC) Project for processing, storing, and sharing data efficiently. This project demonstrates the technical diversity and technical inclusion need to advance the field of Aerosciences. The approach to combine subject matter experts in experimental methods, optical methods, production wind tunnel testing, network engineering, high-end computing, signal processing, grid generation, and visualization while establishing the required infrastructure for subject matter experts to have access to the data while the wind tunnel test is being conducted. The most recent advancements for the uPSP technology have focused on three key areas: development of data products, robust processing pipeline, operational efficiencies and uncertainty quantification.
At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to develop and share best practices and methodologies across NASA. One such cutting edge methodology is Physics of Failure. Therefore NASA OSMA's R&M office is developing a Reliability Physics of Failure Handbook in order to keep our engineers current and on the cutting edge of analysis methodologies to help ensure NASA’s optimize and achieve continued success.
Synthetic Aperture Radar (SAR) Earth observation data are becoming increasingly ubiquitous as new spaceborne systems become operational and their data are made available to scientists and applications users. The characteristic of active sensors like SAR to be able to observe Earth independent of weather or solar illumination, coupled with regular data acquisition, fosters reliability and encourages the investment in algorithm and product development toward a beneficial result. As SAR systems typically contain proprietary or nationally important technologies, civilian SAR systems are typically developed with a national focus, or in the case of the European Union, with the Union’s focus. As a result, when viewed from a global perspective, SAR programs can be generally viewed as independent developments, each with their own requirements, schedules, development approaches, and data policies. At the same time, these systems can be expensive, and particularly in an era of increasingly open data policies, coordination of programs could reduce redundancy in observations, increase sampling density and measurement diversity, and improve dependability of data streams in the long term. Since 2018, agency representatives from NASA, ESA, DLR, JAXA, ISRO, ASI, and CONAE have been evaluating the possibilities for programmatic and technical coordination of future SAR systems, data sharing, and scientific exploitation. In this paper, we describe the work in discovering trends and possibilities associated with flight systems, by evaluating current and future plans for SAR systems around the world, and identifying opportunities for coordination.
Several NASA centers have developed independent flight mechanics tools to meet the science needs of missions. This NASA Engineering and Safety Center (NESC) assessment sought to explore the ways to increase the interoperability of three specific tools: Copernicus from Johnson Space Center (JSC), the General Mission Analysis Tool (GMAT) from Goddard Spaceflight Flight Center (GSFC), and the Mission-Analysis Operations Navigation Toolkit Environment (MONTE) from the Jet Propulsion Laboratory (JPL). Before this assessment, these tools were not integrated and could not easily share data, models, or components. This report contains the outcome of the NESC assessment.
Many technological and environmental challenges must be resolved to enable successful lunar habitation and exploration, and to maximize scientific return. This presentation is intended as a preliminary discussion on three such areas of interest with the intent to identify likely areas of mutual benefit for collaboration and data sharing between the space nuclear and radiological disciplines with the planetary cave community. First is the previously identified and studied possible application of lunar lava tubes or pits to reduce the solar and cosmic radiation environment burden on crew health and hardware reliability. This is an area of continued interest, and should be kept in the forefront of discussion during the selection of sites for potential exploration or long-term habitation. In theory, the prospect of using existing morphology presents an enticing opportunity to reduce the requirements on landed mass or construction while also reducing dose or fluence of harmful natural radiation. However, such discussions should also include the practical implications of relocating habitation hardware and personnel from a landing site to a subsurface location. Inherent risks associated with landing in proximity to the relevant terrain must also be considered and weighed against those imposed by the natural radiation environment. Second is a discussion on the means by which a long-term habitation module or base of operations may be powered throughout the lunar day-night cycle. Fission surface power presents an opportunity to establish round-the-clock power in any lunar surface environment, including permanently shadowed regions where solar panels cannot operate, or in any other non-polar region where solar radiation is available for no more than two weeks per four-week cycle. Among the drawbacks of fission surface power is the need to either land and co-locate a heavy shield to minimize radiological consequences to personnel or equipment, land and operate construction equipment capable of restructuring the in-situ regolith to provide appropriate shielding, or to make use of existing topology features (e.g. craters or pits) to serve as pre-formed radiation barriers. A realistic assessment of the practicality of this third option should involve the selection of candidate features from existing surveys, and assess the effectiveness of the approach using modern radiation transport methodologies. Consideration must be made for the needs to reject waste heat in the thermal power conversion process, which typically requires the use of large area radiators. Energy must be exchanged from the reactor and power conversion system to such radiators, and the impacts on thermal efficiency and secondary scatter of nuclear radiation must be considered. Further consideration should be made for the implications of placement of a power source such that it does not sacrifice valuable scientific opportunity. Placement of a reactor is likely to thereafter prevent personnel access within that feature. Third is a discussion on the use of portable radioisotope power systems (RPS) within confined spaces, both with respect to the dose effects of emitted nuclear radiation and also performance associated with emitted thermal radiation. Radioisotope power systems provide a unique capability to power objects with no reliance upon solar radiance. However, their useable power production relies upon the flow of heat from ‘hot side’ (decaying radioisotope) to ‘cold side’ (radiators emitting heat to space). In the case of a confined volume in vacuum such as a lunar lava tube, that radiated energy will absorb into the wall, which is already above the ‘cold background’ temperature of dark space, and then gradually rises in temperature. That temperature rise, and its implications on availability of useable electrical power, will depend upon factors such as enclosure volume, thermal emissivity/absorptivity, and thermal conductivity through the depth of absorbing media. The advantages of nuclear technology may prove to enable unique scientific exploration opportunities, both above the lunar surface and below. In turn, the unique advantages of lunar lava tubes or pits may present unique opportunities to enhance the application of these technologies and to mitigate the effects of radiation from both natural and technological sources. A discussion on these pairings may prove to be valuable to all, in our endeavor to explore our neighboring worlds.
The accurate identification of biosignatures (indications of life) from data taken from remote or in situ planetary exploration is one of the most important challenges in astrobiology, the interdisciplinary field examining habitability and the potential for extraterrestrial life. This study employs machine learning algorithms to optimize the identification of biosignatures, with an emphasis on those which are agnostic to a specific biochemical basis. We exploit the wealth of terrestrial data available from biogenic and abiogenic systems to enhance efficient feature prioritization. Our dataset, pulled from public databases and laboratory recorded measurements, includes elemental abundance, isotopic fractionation, and VNIR/Raman spectra The data curation process included standardization for detection limits and ranges. Subsequent feature extraction yielded detailed inputs for machine learning, including combinations of elemental content, isotopic ratios, and parameters of spectral peaks and troughs. Feature significance was evaluated across diverse machine learning methodologies, such as k-nearest neighbors, logistic regression, Random Forest, support vector machines, and Gaussian Naïve Bayes, along with a combined voting classifier. We utilized Receiver Operating Characteristic Area Under the Curve (ROC AUC) across 2,000 50% test-train splits as a robust metric of model performance. Results revealed a promising ROC AUC of 0.853 for the combined voting classifier. Removing elemental abundance data notably reduced model accuracy (13% decrease in AUC), highlighting its critical role in biosignature detection. Several other individual data features exhibited significance within their respective data types, offering additional granularity. This research fortifies the relevance of machine learning to astrobiology, potentially enhancing life detection missions by allowing algorithmic prioritization of high-interest samples for further investigation. Future work will refine data standardization, expand the dataset to include more terrestrial systems, and incorporate convolutional neural networks for spectral feature extraction. The potential for public data sharing is also under exploration, reinforcing our commitment to collective scientific advancement.
NASA’s Space Nuclear Propulsion (SNP) program is developing several MagicDraw SysML models to support the development of high performance Nuclear Thermal Rocket Engines (NTRE). Currently, the Demonstration Rocket for Agile Cislunar Operations (DRACO) project is aiming to perform the first ever flight demonstration of an NTRE, and NASA is developing a DRACO Insight Project Model Based Systems Engineering (MBSE) model to capture, define, analyze, and report on the flight and ground test system architecture, functional behavior, requirements, risks, and lessons learned. Additional models are in work for engine component trade trees, fault detection sensor coverage analysis using a Goal Function Tree (GFT) plugin, stakeholder engagement, and technology maturation projects. The GFT plugin is the Galois, Inc. Failure Recovery Instruction Generation using Automata derived from Traditional Engineering models (FRIGATE) tool. A new capability for Jira to MagicDraw data sharing using the OpenPDM collaboration platform is under development with partner Victory Solutions, Inc. to enhance risk impact analysis.
At the intersection of mission, technology, and place is NASA’s need to modernize for a digital-forward future. Therefore, NASA’s Reliability & Maintainability (R&M) Enterprise Data Sharing team is working to leverage both Digitization and Digital Transformation to develop and share best practices and methodologies across NASA. One such cutting edge methodology is Physics of Failure. Therefore NASA OSMA's R&M office is developing a Reliability Physics of Failure Handbook in order to keep our engineers current and on the cutting edge of anlayis methodologies to help ensure NASA’s optimize and achieve continued success.
Biology has developed next-generation data science and alternative analytical approaches with methodologies which require principal investigator (PI) experimental assay data be re-used. This new approach involves mining multiple datasets at once from various hierarchical organizations of biological complexity, while concurrently evaluating how experimental factors affect endpoints of standard assays. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make findable, accessible, interoperable, and reusable (FAIR) all non-human space-relevant biological data. These data include mission metadata, subject metadata, assay metadata (parameters), raw and processed assay data, assay imagery, and subject-experienced telemetry (radiation, temperature, humidity, acoustics, vibrations). ALSDA has transformed to bring current biological repository data and all future collected data into this new scientific data mining reality. It has integrated into the ‘NASA Open Science’ group of projects to facilitate a suite of new tools and workflows to improve data accessibility and reusability by implementing data management plans, automating data submission agreements, and adopting the single-point-of-entry data submission portal, originally developed by NASA GeneLab. These systems required ALSDA to develop science assay configurations for the submission portal, capturing essential assay parameters according to established norms in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. ALSDA datasets are curated to maintain rich metadata, accuracy of datasets, data transparency, provenance, and additionally ensure data are machine-readable (e.g., R and Python languages). ALSDA integration with GeneLab and its analysis portals enable higher-order physiological-level datasets be mined in conjunction with -omics datasets. As ALSDA physiological-level datasets are published (micro-computed tomography, histology, intraocular pressure, hormonal assays, immunostaining, ultrasonography), the merging of hierarchical organizations of biological complexity from spaceflight will enable new knowledge discovery approaches.
The Geospatial Interactive Online Visualization and Analysis Interface (Giovanni) is a popular tool for users of the Goddard Earth Sciences Data and Information Services Center (GES DISC) and has been in use for over a decade. It provides a wide variety of algorithms and visualizations to explore large remote sensing datasets without having to download the data and without having to write readers and visualizers for it. Giovanni is now being extended to enable its capabilities at other data centers within the Earth Observing System Data and Information System (EOSDIS). This Federated Giovanni will allow four other data centers to add and maintain their data within Giovanni on behalf of their user community. Those data centers are the Physical Oceanography Distributed Active Archive Center (PO.DAAC), MODIS Adaptive Processing System (MODAPS), Ocean Biology Processing Group (OBPG), and Land Processes Distributed Active Archive Center (LP DAAC). Three tiers are supported: Tier 1 (GES DISC-hosted) gives the remote data center a data management interface to add and maintain data, which are provided through the Giovanni instance at the GES DISC. Tier 2 packages Giovanni up as a virtual machine for distribution to and deployment by the other data centers. Data variables are shared among data centers by sharing documents from the Solr database that underpins Giovanni's data management capabilities. However, each data center maintains their own instance of Giovanni, exposing the variables of most interest to their user community. Tier 3 is a Shared Source model, in which the data centers cooperate to extend the infrastructure by contributing source code.