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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 289 records · Page 16
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NASA NTRS2015

Measuring and Modeling Shared Visual Attention

Multi-person teams are sometimes responsible for critical tasks, such as flying an airliner. Here we present a method using gaze tracking data to assess shared visual attention, a term we use to describe the situation where team members are attending to a common set of elements in the environment. Gaze data are quantized with respect to a set of N areas of interest (AOIs); these are then used to construct a time series of N dimensional vectors, with each vector component representing one of the AOIs, all set to 0 except for the component corresponding to the currently fixated AOI, which is set to 1. The resulting sequence of vectors can be averaged in time, with the result that each vector component represents the proportion of time that the corresponding AOI was fixated within the given time interval.We present two methods for comparing sequences of this sort, one based on computing the time varying correlation of the averaged vectors, and another based on a chi-square test testing the hypothesis that the observed gaze proportions are drawn from identical probability distributions.We have evaluated the method using synthetic data sets, in which the behavior was modeled as a series of activities, each of which was modeled as a first-order Markov process. By tabulating distributions for pairs of identical and disparate activities, we are able to perform a receiver operating characteristic (ROC) analysis, allowing us to choose appropriate criteria and estimate error rates. Using these criteria, we have applied the methods to data from airline crews, collected in a high-fidelity flight simulator (Gontar Hoermann, 2014). We conclude by considering the problem of automatic (blind) discovery of activities, using methods developed for text analysis.

Mulligan, Jeffrey B.↗
NASA NTRS2019

Cumulus Lessons Learned: Building, Testing, and Sharing a Cloud Archive

Cumulus is a scalable, extensible cloud-based archive system which is capable of ingesting, archiving, and distributing data from both existing on-prem sources and new cloud-native missions. As we have built and evolved the system with contributions from seven NASA EOSDIS organizations, we have learned several lessons about how to build a robust, broadly-applicable, microservices-based cloud system for geospatial data which we will share in this talk.

Quinn, Patrick↗
NASA NTRSDate not supplied

NASA Institutional Scientific Collection and Biospecimen Sharing Program at Ames Research Center

For decades, NASA and their international partners have flown and conducted non-human biological experiments in space to understand the effects of spaceflight and address potential biological hazards. It is imperative to understand the basic science and health risks associated with spaceflight, along with developing countermeasures, as humanity ventures back to the Moon, and then to Mars and beyond. Sending organisms into space is a costly endeavor which makes space-flown biological specimens a valuable resource. To enable maximum scientific return, samples not required by the Principal Investigators are harvested, preserved and archived in NASA’s Institutional Scientific Collection (ISC) at Ames Research Center (ARC). These specimens are collected according to well-established SOPs that maintain their quality and integrity. To enable new discoveries, the samples are then made available to the international scientific community through NASA’s Biospecimen Sharing Program (BSP). The NASA ISC currently stores over 32,000 specimens from Shuttle, International Space Station and ground-based investigations. Tissues are predominantly from mice and rats, though samples are also available from bacteria and quail. The specimens include tissues from all biological systems including musculoskeletal, neurosensory, reproductive, respiratory, circulatory, and digestive and are stored at -80°C, -20°C, +4°C, or ambient. Descriptive metadata is available for all samples. Historically, these tissues have been used for a wide range of analyses, including histology, genomics, and transcriptomics. Also available through the ISC are tissue from NASA’s Space Radiation Laboratory. To study the effects of space radiation, researchers irradiate biological specimens and unused samples are made available through the LSDA. These biospecimens and data are made available through the public Life Sciences Data Archive (LSDA) website to promote basic discovery, pre-clinical and clinical science. Visit the NASA ISC-BSP website for more information.

Space Flown Biospecimens↗
NASA NTRS2018

Dynamic Shared Computing Resources for Multi-Robot Mars Exploration

The NASA roadmap for 2020 and beyond includes several key technologies which will have a game-changing impact on planetary exploration. The first of these is High Performance Spaceflight Computing (HPSC), which will provide orders of magnitude increases in processing power for next-generation rovers and orbiters (Doyle et al. 2013). The second is Delay Tolerant Networking, which overlays the Deep Space Network, providing internet-like abstractions and store-forward to route data through intermittent delays in connectivity. The third is a trend toward small, co-dependent robots included in flagship missions (MarCO, PUFFER, and Mars Heli). Taken together, these imply an increasing amount of communication and computing heterogeneity on Mars in coming decades. Motivated by these technological trends, we study the concept of Mars on-site shared analysis, information, and communication (MOSAIC) for Mars exploration. The key algorithmic problem associated with MOSAIC networks is simultaneous scheduling of computation, communication, and caching of data, which we illustrate using the three scenarios. We present models, preliminary solutions, and simulation results for two scenarios, showing how mission efficiency relates to communication bandwidth, processing power, geography of the environment, and optimal scheduling of computation, communication, and data caching. The third scenario illustrates future directions of this work.

Chien, Steve↗
NASA NTRSDate not supplied

Spaceflight Biospecimen Sharing in Support of Science Discovery and Exploration

For decades, NASA and international partners have flown non-human biological experiments in space to understand the effects of spaceflight and address potential biological hazards. Sending organisms into space is a costly endeavor which makes space-flown biological specimens a valuable resource. To enable maximum scientific return, samples not required by the Principal Investigators are harvested and collected mostly by NASA’s Space Biology Biospecimen Sharing Program. These specimens are collected according to well-established SOPs that maintain quality and integrity. The specimens are then preserved, archived, and made available to the international scientific community through NASA’s Institutional Scientific Collection (ISC) at Ames Research Center (ARC). The ISC-ARC biospecimens and descriptive metadata are findable and accessible for request through the Life Sciences Data Archive (LSDA). The NASA ISC-ARC currently stores over 32,000 specimens from Shuttle, International Space Station, and ground-based investigations (spaceflight analog experiments involving either hindlimb unloading, centrifugation, or partial weight-bearing study designs). Tissues are predominantly from mice and rats, though samples are also available from bacteria and quail. The specimens include tissues from many physiological systems including musculoskeletal, neurosensory, reproductive, respiratory, circulatory, and digestive. Tissues are stored at -80°C, -20°C, +4°C, or ambient and preserved in various fixatives. Descriptive metadata is available for all samples. Historically, these tissues have been used for a wide range of analyses, including histology, genomics, and transcriptomics. Plans are underway to expand the ISC-ARC beyond the mostly-rodent contents, to include a space-relevant microbial culture collection including bacteria, fungi, and yeast. This expansion of the ISC-ARC will now involve identifying and standardizing best practices for microbial curations. To ensure safe long-term storage of microbial isolates, a microbiology laboratory will be dedicated for identification, cell culture, and lyophilization. Awarding of tissue to public science investigators has resulted in 33 publications since 2011, with 48 requests being submitted since 2016. Of note, NASA GeneLab has been awarded ISC-ARC biospecimens in the past few years. GeneLab processes the biospecimens to generate various levels of ‘omics’ data, which are published on GeneLab’s open access online platform for bioinformatics analysis and visualization. This has helped a systems biology community grow around the processed-biospecimens’ datasets, resulting in many new publications and insights. Websites: https://www.nasa.gov/ames/research/space-biosciences/isc-bsp ; https://lsda.jsc.nasa.gov/Biospecimen

Ryan T. Scott↗
NASA NTRS2022

Sharing Operational Intent with Containment Confidence Level for Negotiating Deconfliction in Upper Class E Airspace

Community-based Cooperative Separation Management (CSM) is expected to provide separation services in Upper Class E airspace (near and above FL600). Under CSM, operators are responsible for maintaining separation. The CSM concept is enabled by sharing Operational Intent (OI) among the operators to ensure common situation awareness. The OI is represented as four-dimensional (time and space) information that indicates where an aircraft would be contained within the space and time, with a known level of confidence. However, each vehicle’s ability to stay within its region of OI may differ based on each vehicle’s performance characteristics, resulting in varying OI sizes among the vehicles. Such varying OI size could adversely affect efficient and fair access to the airspace. In this paper, an OI-generation algorithm under varying OI size restriction with Containment Confidence Level (CCL) is presented. High-Altitude Long Endurance (HALE) balloon operations are used as an example application. A framework is presented by which CCL information is used in the deconfliction process. A fast-time simulation experiment is conducted to evaluate the feasibility of the proposed framework. The simulation results show a reduced number of unnecessary deconfliction actions.

Upper Class E Traffic Management↗
NASA NTRS2022

Sharing Operational Intent with Containment Confidence Level for Negotiating Deconfliction in Upper Class E Airspace

Community-based Cooperative Separation Management (CSM) is expected to provide separation services in Upper Class E airspace (near and above FL600). Under CSM, operators are responsible for maintaining separation. The CSM concept is enabled by sharing Operational Intent (OI) among the operators to ensure common situation awareness. The OI is represented as four-dimensional (time and space) information that indicates where an aircraft would be contained within the space and time, with a known level of confidence. However, each vehicle’s ability to stay within its region of OI may differ based on each vehicle’s performance characteristics, resulting in varying OI sizes among the vehicles. Such varying OI size could adversely affect efficient and fair access to the airspace. In this paper, an OI-generation algorithm under varying OI size restriction with Containment Confidence Level (CCL) is presented. High-Altitude Long Endurance (HALE) balloon operations are used as an example application. A framework is presented by which CCL information is used in the deconfliction process. A fast-time simulation experiment is conducted to evaluate the feasibility of the proposed framework. The simulation results show a reduced number of unnecessary deconfliction actions.

Upper Class E Traffic Management, ETM, Cooperative↗
NASA NTRSDate not supplied

A Structurally-Adaptive Framework for Distributed Airborne Sensing over Real-time Collaborative Information Sharing Networks

The emergence and maturation of wireless communication technologies continue to transform the aviation industry and are enabling new solutions to challenges faced by NASA’s Advanced Air Mobility (AAM) initiative. AAM is leading towards high-density autonomous aircraft operations in areas underserved by traditional aviation, such as over densely populated urban centers. In this paper, we build on concepts from Smart Spaces - where sensing, processing, and communication are embedded in an environment, and agents are operating within the space can exploit these capabilities in real-time through collaborative information sharing networks. Building from these concepts, we propose a framework to enable a dynamic, topologically-adaptive, and distributed estimation system for man-rated aviation to address challenges faced by autonomous AAM operations. This paper presents the initial concept of operations and system design for this framework, presents a mathematical formulation for abstraction of the problem, identifies requirements and constraints for operation, and presents algorithmic constructs and mathematical formalisms to demonstrate operation. The proposed framework will be evaluated on a regional AAM flight scenario and will focus on two initial applications: (1) GPS-free navigation supporting precision approach and landing (PAL), and (2) surveillance and conformance monitoring of aircraft in vertiport airspaces. Such approaches show promise in addressing gaps in current technologies needed to enable future AAM concepts, while promising greater capabilities, performance, robustness, and safety over current aviation systems and operations.

Structurally-Adaptive↗
NASA NTRSDate not supplied

A Structurally-Adaptive Framework for Distributed Airborne Sensing over Real-time Collaborative Information Sharing Networks

The emergence and maturation of wireless communication technologies continue to transform the aviation industry and are enabling new solutions to challenges faced by NASA’s Advanced Air Mobility (AAM) initiative. AAM is leading towards high-density autonomous aircraft operations in areas underserved by traditional aviation, such as over densely populated urban centers. In this paper, we build on concepts from distributed sensing and smart spaces - where sensing, processing, and communication are embedded in an environment, and agents are operating within the space can exploit these capabilities in real-time through collaborative information sharing networks. Building from these concepts, we propose a framework to enable a dynamic, topologically-adaptive, and distributed estimation system for man-rated aviation to address challenges faced by autonomous AAM operations. This paper presents the initial concept of operations and system design for this framework, presents a mathematical formulation for abstraction of the problem, identifies requirements and constraints for operation, and presents algorithmic constructs to demonstrate operation. The initial framework design will focus on supporting precision navigation and independent surveillance supporting conformance monitoring of aircraft in airspace corridors and vertiport airspaces. Preliminary results from this framework shows promise in addressing gaps in current technologies needed to enable future AAM concepts, while promising greater capabilities, performance, robustness, and safety over current aviation systems and operations.

Distributed sensing↗
NASA NTRSDate not supplied

Enabling Space Biological Knowledge Discovery Through Image and Video Data Sharing

Increased biomedical risks associated with deep space crewed missions (cis-Lunar, Mars transit/surface) require development of health countermeasures, novel ecosystem support, risk modeling, and fundamental space biological knowledge discovery. Molecular-omics, physiological-phenotypic-behavioral, and environmental-radiation telemetry data from space biological and health studies are needed for reuse by scientists to address these tasks. The data as well as space-relevant biospecimens are being made more findable, accessible, interoperable, and reusable through NASA’s Open Science Data Repository (OSDR). This new OSDR umbrella grouping includes NASA GeneLab, the NASA Ames Life Sciences Data Archive (ALSDA), and the NASA Biological Institutional Scientific Collection. The OSDR system design appropriately handles metadata and processed-tabular results from ALSDA studies collected from space experiments. But raw and processed ALSDA bioimage and video datasets require an expansion of OSDR’s data architecture to handle ingestion, curation, and egress. The academic-industry bioimaging field saw a scientific renaissance in the past several years through leveraging open-source software, international collaborations, machine learning, and other open science/programming approaches. As crewed missions and more biological experiments are on the deep space horizon, OSDR is embracing data stewardship through listening to feedback from subject matter experts and designing an expanded architecture which is appropriate for NASA’s goals to enable analysis and reuse of bioimaging and video data for the public science community.Discovery Through Image and Video Data Sharing

space biology↗
NASA NTRS2023

Flight Mechanics Analysis Tools Interoperability and Component Sharing

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.

General Mission Analysis Tool↗
NASA NTRS2023

We Need A Better Way to Share Earth Observations

A more accessible, open data-sharing infrastructure will engage a broader community of contributors, helping to develop satellite data products that benefit Earth science research and applications.

Apps & Software↗
NASA NTRS2024

Optimizing Sample Collection and Accessibility through the Biospecimen and Tissue Sharing Collection (BTSC) Program

The Space Radiation Element (SRE) of the Human Research Program (HRP) is dedicated to establishing a robust biospecimen and tissue sharing collection (BTSC) program that enhances sample collection, tracking, access, distribution, and usability, with the goal of maximizing scientific return. By leveraging biospecimens and tissues from previous experiments, HRP effectively achieves its scientific objectives in characterizing and mitigating the human health impacts of spaceflight while optimizing resource utilization. To further improve the usability and accessibility of the current biospecimen archive, the project aims to expand upon NASA's existing resources and institutional knowledge, ensuring ongoing modernization. To facilitate seamless navigation of the program's workflow, an educational series on the BTSC program is provided to Principal Investigators (PIs). This comprehensive series equips PIs with crucial information on submitting their inventory via the BTSC Metadata Intake Form, ultimately leading to the public availability of their data on NASA's Life Science Portal (NLSP). Covering various aspects such as metadata submission instructions and backend processes for transferring metadata to the Laboratory Information Management System (LIMS), the series incorporates guidance from NASA's Biological Institutional Scientific Collection (NBISC) and Ames Life Sciences Data Archive (ALSDA). The BTSC program represents a significant stride towards enhancing the usability and accessibility of biospecimens for space research. By enabling NASA to deepen its understanding of the health implications of long-term spaceflight, this initiative plays a pivotal role in ensuring the safety and well-being of astronauts.

Shelita Renee Augustus↗
NASA NTRSDate not supplied

The Exploration Crew Health and Performance System of the Future - A Shared Mental Model

The challenges involved in vehicle/habitat design and operation for long-duration deep space missions are complex, and the needs of a human crew must be considered in the context of all the system trades required to enable such missions. An exploration Crew Health and Performance (CHP) system complements all the other vehicle/habitat systems to achieve one specific and critical endpoint – ensuring that the astronauts can perform the job that they were sent into space to do. This includes accounting for all aspects of the physiological, psychological, medical, and environmental realities that the human crew must face in deep space. Along with this system complexity comes the additional need for increased autonomy of the crew due to the immense distance from Earth. The design of future systems must respect the real human capabilities and limitations within the context of a mission to the Moon or Mars. The NASA Moon to Mars Objectives document outlines the need for advanced CHP system designs: • Develop systems that monitor and maintain crew health and performance throughout all mission phases, including during communication delays to Earth, and in an environment that does not allow emergency evacuation or terrestrial medical assistance. • Evaluate and validate progressively Earth-independent crew health & performance systems and operations with mission durations representative of Mars-class missions. • Validate readiness of systems and operations to support crew health and performance for the initial human Mars exploration campaign. This presentation will outline the initial work that Exploration Medical Capability is leading on the development of a prototype design for an exploration Crew Health and Performance (CHP) system for future NASA human deep space long-duration missions. This effort will require commitment from all stakeholders to a shared mental model of what a future exploration CHP system should look like, one that will address the needs, goals, and objectives of the Agency and help to ensure mission success in deep space.

K R Lehnhardt↗
NASA NTRS2004

Data processing pipeline with transaction-oriented data sharing

This paper makes three contributions to the area of modern science data processing systems. First, the paper describes the science data processing pipeline, developed at the Multi-mission Image Processing Lab of JPL, for transforming raw space data into high quality image data and automating the distribution of data using a high-performance file transaction service. File Exchange Interface is the file transaction service developed MIPL. Second, it presents the FEI component architecture in the are of file transaction management, security,a nd file integrity verfication. Finally, the paper presents the federated model for the FEI service to demonstrate how to create a pool of file trasaction services to support load balancing and service fallover, and simplify service management.

science data processing↗