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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 199 records · Page 11
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NASA NTRS1995

Satellite communications provisions on NASA Ames instrumented aircraft platforms for Earth science research/applications

Earth science activities at NASA Ames are research in atmospheric and ecosystem science, development of remote sensing and in situ sampling instruments, and their integration into scientific research platform aircraft. The use of satellite communications can greatly extend the capability of these agency research platform aircraft. Current projects and plans involve satellite links on the Perseus UAV and the ER-2 via TDRSS and a proposed experiment on the NASA Advanced Communications Technology Satellite. Provisions for data links on the Perseus research platform, via TDRSS S-band multiple access service, have been developed and are being tested. Test flights at Dryden are planned to demonstrate successful end-to-end data transfer. A Unisys Corp. airborne satcom STARLink system is being integrated into an Ames ER-2 aircraft. This equipment will support multiple data rates up to 43 Mb/s each via the TDRS S Ku-band single access service. The first flight mission for this high-rate link is planned for August 1995. Ames and JPL have proposed an ACTS experiment to use real-time satellite communications to improve wildfire research campaigns. Researchers and fire management teams making use of instrumented aircraft platforms at a prescribed burn site will be able to communicate with experts at Ames, the U.S. Forest Service, and emergency response agencies.

Shameson, L.↗
NASA NTRS1975

Water-management models in Florida from ERTS-1 data

The author has identified the following significant results. The usefullness of ERTS 1 to improving the overall effectiveness of collecting and disseminating data was evaluated. ERTS MSS imagery and in situ monitoring by DCS were used to evaluate their separate and combined capabilities. Twenty data collection platforms were established in southern Florida. Water level and rainfall measurements were collected and disseminated to users in less than 2 hours, a significant improvement over conventional techniques requiring 2 months. ERTS imagery was found to significantly enhance the utility of ground measurements. Water stage was correlated with water surface areas from imagery in order to obtain water stage-volume relations. Imagery provided an economical basis for extrapolating water parameters from the point samples to unsampled data and provided a synoptic view of water mass boundaries that no amount of ground sampling or monitoring could provide.

Higer, A. L.↗
NASA NTRSDate not supplied

A PI’s Guide to Analog Research

Congratulation on being awarded a grant to conduct research in a spaceflight analog! NASA funded research in a Human Research Program (HRP) managed analog environment is very different from research in a traditional laboratory. This presentation will provide a guide to help investigators successfully plan studies for integration and implementation in an HRP analog platform. There are many things to consider when planning a study for implementation in an analog facility and campaign or mission. How do you get from grant approval to data analysis? This is where HRP’s Research Operations and Integration (ROI) team comes in. The ROI team works with sponsoring HRP elements and PI teams to capture requirements and help the PI teams through the phases of research complement development, integration and implementation. A complement is comprised of a group of studies requiring a common platform and/or scenario that are able to be integrated on a noninterference basis for implementation. Properly defining and documenting requirements and study needs is crucial in successful integration and implementation. This presentation will outline and provide the information needed for PI teams to understand the integration process and the role of the ROI team in the successful integration and implementation of their study. Topics to be discussed will include but not be limited to science requirement definition and documentation, NASA IRB submissions, subject recruitment, screening and selection, study integration process, efficiency in data collection and data sharing, daily crew schedules, hardware and software shipping, receipt and checkout, biological sample collection, mission support, data management and receipt of data.

B. Caldwell↗
NASA NTRS2009

An Overview of the Microgravity Science Glovebox (MSG) Facility and the Research Performed in the MSG on the International Space Station (ISS)

The Microgravity Science Glovebox (MSG) is a double rack facility aboard the International Space Station (ISS) designed for investigation handling. The MSG has been operating on the ISS since July 2002 and is currently located in the Columbus Laboratory Module. The unique design of the facility allows it to accommodate science and technology investigations in a workbench type environment. The facility has an enclosed working volume that is held at a negative pressure with respect to the crew living area. This allows the facility to provide two levels of containment for small parts, particulates, fluids, and gases. This containment approach protects the crew from possible hazardous operations that take place inside the MSG work volume. Research investigations operating inside the MSG are provided a large 255 liter enclosed work space, 1000 watts of dc power via a versatile supply interface (120, 28, +/- 12, and 5 Vdc), 1000 watts of cooling capability, video and data recording and real time downlink, ground commanding capabilities, access to ISS Vacuum Exhaust and Vacuum Resource Systems, and gaseous nitrogen supply. These capabilities make the MSG one of the most utilized facilities on ISS. In fact, the MSG has been used for over 5000 hours of scientific payload operations. MSG investigations involve research in cryogenic fluid management, fluid physics, spacecraft fire safety, materials science, combustion, plant growth, and life support technologies. MSG is an ideal platform for science investigations and research required to advance the technology readiness levels (TRLs) applicable to the Constellation Program. This paper will provide an overview of the MSG facility, a synopsis of the research that has already been accomplished in the MSG, an overview of future investigations currently planned for operation in the MSG, and potential applications of MSG investigations that can provide useful data to the Constellation Program. In addition, this paper will address the role of the MSG facility in the ISS National Lab.

Spivey, Reggie↗
NASA NTRS1991

Using C to build a satellite scheduling expert system: Examples from the Explorer Platform planning system

A C-based artificial intelligence (AI) development effort which is based on a software tools approach is discussed with emphasis on reusability and maintainability of code. The discussion starts with simple examples of how list processing can easily be implemented in C and then proceeds to the implementations of frames and objects which use dynamic memory allocation. The implementation of procedures which use depth first search, constraint propagation, context switching, and blackboard-like simulation environment are described. Techniques for managing the complexity of C-based AI software are noted, especially the object-oriented techniques of data encapsulation and incremental development. Finally, all these concepts are put together by describing the components of planning software called the Planning And Resource Reasoning (PARR) Shell. This shell was successfully utilized for scheduling services of the Tracking and Data Relay Satellite System for the Earth Radiation Budget Satellite since May of 1987 and will be used for operations scheduling of the Explorer Platform in Nov. of 1991.

Mclean, David R.↗
NASA NTRS1977

Operational utilization of remotely sensed data

The use of data from environmental satellites and other remote sensing platforms in some of NOAA's operational services are described. Topics discussed include: hurricanes; severe local storms and tornadoes; forest guidance; weather forecasting; hydrology; space program support; oceanography; search and rescue; and wildlife management. Applications which have become routine, and those which are in advanced field test are included. Some applications yield a clear cut economic benefit. In other cases, benefits -- if any -- are obscure. In yet other cases, benefits in one sector may be offset by detriments in another. Illustrative examples are given.

Jones, J. B.↗
NASA NTRS2017

SO-QT: Collaborative Tool to Project the Future Space Object Population

Earth orbit gets increasingly congested, a challenge to space operators, both in governments and industry. We present a web tool that provides: 1) data on todays and the historic space object environments, by aggregating object-specific tracking data; and 2) future trends through a collaboration platform to collect information on planed launches. The collaborative platform enables experts to pool and compare their data in order to generate future launch scenarios. The tool is intended to support decision makers and mission designers while they investigate future missions and scholars as they develop strategies for space traffic management.

space debris↗
NASA NTRS2022

Air Traffic Management TestBed: Messaging Performance

The Air Traffic Management (ATM) TestBed is an air traffic management modeling and simulation platform and framework developed by the National Aeronautics and Space Administration (NASA) to help design, configure, integrate, run, and monitor air traffic simulations. The communication middleware, implemented in the TestBed framework layer, is a core feature for data message exchange. The feature provides an abstraction layer called Messaging Support to allow switching one middleware to another without a need to rebuild the simulation components. Messaging performance such as latencies, run durations, and throughputs are important factors. Low latencies can produce accurate results in high-fidelity and visualization models. Short run durations are preferred because better run efficiency can be achieved. High throughputs allow more runs to be executed concurrently. This technical memorandum studies and compares the messaging performance by running a full-day, fast-time simulation using three communication middleware as well as tweaking the default communication middleware settings used by the TestBed. Results indicate that the messaging performance could be improved by disabling either compression or persistence settings, while the run duration and throughput could be further improved by disabling both settings with a tradeoff of the message latencies increased by a factor of ten.

Chok Fung Lai↗
NASA NTRS2019

Image Labeler: Label Earth Science Images for Machine Learning

The application of machine learning for image-based classification of earth science phenomena, such as hurricanes, is relatively new. While extremely useful, the techniques used for image-based phenomena classification require storing and managing an abundant supply of labeled images in order to produce meaningful results. Existing methods for dataset management and labeling include maintaining categorized folders on a local machine, a process that can be cumbersome and not scalable. Image Labeler is a fast and scalable web-based tool that facilitates the rapid development of image-based earth science phenomena datasets, in order to aid deep learning application and automated image classification/detection. Image Labeler is built with modern web technologies to maximize the scalability and availability of the platform. It has a user-friendly interface that allows tagging multiple images relatively quickly. Essentially, Image Labeler improves upon existing techniques by providing researchers with a shareable source of tagged earth science images for all their machine learning needs. Here, we demonstrate Image Labeler’s current image extraction and labeling capabilities including supported data sources, spatiotemporal subsetting capabilities, individual project management and team collaboration for large scale projects.

Acharya, Ashish↗
NASA NTRS2023

Exploration Medical Capability Clinical Decision Support System Architecture Recommendation

A new era in space exploration has arrived with the goal of establishing a long-term presence on the Moon and using those learning to take the next giant leap: sending the first astronauts to Mars. These ambitious goals will require significant changes in in-flight medical care due to constraints on mass, volume, power, crew time, and medical evacuation capabilities. Furthermore, while crews currently rely on real-time communications with ground-based medical providers, as distance from Earth increases, so do communication delays and disruptions. The crew will need to autonomously detect, diagnose, treat, and prevent medical events. These constraints require development of transformative solutions and new technologies. Through participation in the Human Research Program’s (HRP) Exploration Medical Capability (ExMC) research, NASA has developed and demonstrated a Medical Data Architecture (MDA), a platform upon which a robust capability of Clinical Decision Support (CDS) can be built. As a result, NASA is now positioned to build an advanced autonomous CDS System (CDSS) which will aid in crew health decision-making. The CDSS combines data management aspects of a system that would lead to the autonomy required by NASA-STD-3001, Section 3, Health and Medical Care Standards. The project addresses the ExMC gap Medical-701: We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources. This architecture recommendation document introduces an integrated data architecture that provides self-sufficient medical care for crews on long-duration spaceflight missions.

ExMC↗
NASA NTRSDate not supplied

Summary of Technical Interchange Meetings (TIMs) Designed to Enable Earth Independent Medical Operations (EIMO)

The Exploration Medical Capability Element (ExMC) in NASA’s Human Research Program hosted a series of TIMs in 2023-2024 designed to stimulate discussion around specific topics with the goal of enabling EIMO. In context of the thematic constituent elements of EIMO, namely pre-mission planning, acute/emergent/prolonged medical decision making, supply/resource management and task load management, subject matter experts from industry, academia and government (NASA and other Agencies) provided valuable and actionable guidance and recommendations. Earth-based medical experts will remain indispensable for pre-mission planning, however, management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets to enable support of astronaut health and performance and reduce overall mission risk. Key to achieving these enhancements is providing an integrated data system platform capable of utilizing multiple data streams in concert with a variety of on-board databases and passive monitoring of video and wearable sensors to enable a multi-modal, agentic AI-based clinical decision support system (CDSS) to support crew medical officer (CMO) medical decision-making. The EIMO series of TIMs (I-V) have proven to be instructive and portend a significant paradigm shift will be necessary to maintain crew health and performance on exploration class missions. Importantly, since the expected paradigm shift will be significantly different from the methods of operation that have been employed for the majority of missions from the inception of human spaceflight to date, any proposed methods must be deployed in the setting of ongoing operations early and be “tested, reviewed and practiced” while reliable back-up is available to facilitate an Enterprise-wide level of comfort and acceptance. Serious constraints on data transmission coupled with a large and expanding universe of on-board medical informatics data streams will necessitate implementation of a CDSS to supplant the current reliance on support provided by ground-based SMEs. Establishment of trust in the system by CMO/crew and the ground-based medical support team will be essential. Co-development of a CDSS with industry partners will assure that state of the art tools can be employed, and industry efficiencies can be leveraged. Training regimens, materials and tools must evolve to be responsive (just-in-time training) and facilitate autonomous execution of procedures. Proficiency metrics should be established and be based on validated competencies or milestones as opposed to a prescribed number of training hours. Training should be prioritized for broad, translatable skills that have universal application across a variety of medical conditions. Repetition was deemed to be the key to achieving proficiency and emphasis should lie in procedural training which is known to extinguish more rapidly than diagnostic skills. Advanced tools, e.g., extended reality, can provide more realistic and effective training. Use of advanced probabilistic risk assessment tools will be essential to optimize the medical system capability while carefully balancing risk relative to mass/power/volume limitations. Importance of factoring use-life of medical supplies and maintaining awareness of redundancy and opportunity to re-purpose under off nominal situations was emphasized. Consideration of adopting optimized performance standards vs. “good-enough” performance thresholds is warranted. The use of legacy systems as opposed to creating new systems may be preferable. Managing task load and associated cognitive load will be essential to maintain operational safety and behavioral health. ExMC aspires to create a shared EIMO paradigm and strategic vision for advancing medical system design through novel technologies, training, protocols, and support capabilities, built upon the spirit of successful strategies and innovations over the past six decades of space medicine operations.

Jay Lemery↗
NASA NTRS1975

Design criteria for a multiple input land use system

A design is presented that proposes the use of digital image processing techniques to interface existing geocoded data sets and information management systems with thematic maps and remote sensed imagery. The basic premise is that geocoded data sets can be referenced to a raster scan that is equivalent to a grid cell data set, and that images taken of thematic maps or from remote sensing platforms can be converted to a raster scan. A major advantage of the raster format is that x, y coordinates are implicitly recognized by their position in the scan, and z values can be treated as Boolean layers in a three-dimensional data space. Such a system permits the rapid incorporation of data sets, rapid comparison of data sets, and adaptation to variable scales by resampling the raster scans.

Billingsley, F. C.↗
NASA NTRS2007

Grid Task Execution

IPG Execution Service is a framework that reliably executes complex jobs on a computational grid, and is part of the IPG service architecture designed to support location-independent computing. The new grid service enables users to describe the platform on which they need a job to run, which allows the service to locate the desired platform, configure it for the required application, and execute the job. After a job is submitted, users can monitor it through periodic notifications, or through queries. Each job consists of a set of tasks that performs actions such as executing applications and managing data. Each task is executed based on a starting condition that is an expression of the states of other tasks. This formulation allows tasks to be executed in parallel, and also allows a user to specify tasks to execute when other tasks succeed, fail, or are canceled. The two core components of the Execution Service are the Task Database, which stores tasks that have been submitted for execution, and the Task Manager, which executes tasks in the proper order, based on the user-specified starting conditions, and avoids overloading local and remote resources while executing tasks.

Hu, Chaumin↗
NASA NTRS1988

Knowledge-based assistance in costing the space station DMS

The Software Cost Engineering (SCE) methodology developed over the last two decades at IBM Systems Integration Division (SID) in Houston is utilized to cost the NASA Space Station Data Management System (DMS). An ongoing project to capture this methodology, which is built on a foundation of experiences and lessons learned, has resulted in the development of an internal-use-only, PC-based prototype that integrates algorithmic tools with knowledge-based decision support assistants. This prototype Software Cost Engineering Automation Tool (SCEAT) is being employed to assist in the DMS costing exercises. At the same time, DMS costing serves as a forcing function and provides a platform for the continuing, iterative development, calibration, and validation and verification of SCEAT. The data that forms the cost engineering database is derived from more than 15 years of development of NASA Space Shuttle software, ranging from low criticality, low complexity support tools to highly complex and highly critical onboard software.

Henson, Troy↗
NASA NTRS2004

Transitioning to Intel-based Linux Servers in the Payload Operations Integration Center

The MSFC Payload Operations Integration Center (POIC) is the focal point for International Space Station (ISS) payload operations. The POIC contains the facilities, hardware, software and communication interface necessary to support payload operations. ISS ground system support for processing and display of real-time spacecraft and telemetry and command data has been operational for several years. The hardware components were reaching end of life and vendor costs were increasing while ISS budgets were becoming severely constrained. Therefore it has been necessary to migrate the Unix portions of our ground systems to commodity priced Intel-based Linux servers. hardware architecture including networks, data storage, and highly available resources. This paper will concentrate on the Linux migration implementation for the software portion of our ground system. The migration began with 3.5 million lines of code running on Unix platforms with separate servers for telemetry, command, Payload information management systems, web, system control, remote server interface and databases. The Intel-based system is scheduled to be available for initial operational use by August 2004 The overall migration to Intel-based Linux servers in the control center involves changes to the This paper will address the Linux migration study approach including the proof of concept, criticality of customer buy-in and importance of beginning with POSlX compliant code. It will focus on the development approach explaining the software lifecycle. Other aspects of development will be covered including phased implementation, interim milestones and metrics measurements and reporting mechanisms. This paper will also address the testing approach covering all levels of testing including development, development integration, IV&V, user beta testing and acceptance testing. Test results including performance numbers compared with Unix servers will be included. need for a smooth transition while maintaining real-time support. An important aspect of the paper will involve challenges and lessons learned. product compatibility, implications of phasing decisions and tracking of dependencies, particularly non- software dependencies. The paper will also discuss scheduling challenges providing real-time flight support during the migration and the requirement to incorporate in the migration changes being made simultaneously for flight support. This paper will also address the deployment approach including user involvement in testing and the , This includes COTS product compatibility, implications of phasing decisions and tracking of dependencies, particularly non- software dependencies. The paper will also discuss scheduling challenges providing real-time flight support during the migration and the requirement to incorporate in the migration changes being made simultaneously for flight support.

Guillebeau, P. L.↗
NASA NTRSDate not supplied

Crew Health and Performance Integrated Data System Platform Project Updates

Future human exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting crew autonomy for future exploration missions. An integrated data system platform is needed to mitigate these risks by supporting a new generation of technologies and employing advanced analytical and predictive modeling techniques to enable crew autonomy for future exploration missions. The Crew Health and Performance Integrated Data System Platform (CHP-IDSP) project is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. This cohesive integration point will streamline the management of CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.) and facilitate situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the ongoing development effort of the path-to-flight CHP-IDSP software and the demonstration of its core capabilities. This includes a brief history of the project, the human-centered process used to identify data needs and workflows feeding the development of scenarios and requirements, and current subsystem development status. Current integrations, including the Chiron exploration electronic health record application, will be discussed. Future work includes collaboration with additional CHP domains and a flight technology demonstration.

Data integration↗
NASA NTRSDate not supplied

Crew Health and Performance Integrated Data Service Platform (CHP-IDSP): Project Updates

Future human exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting crew autonomy for future exploration missions. An integrated data services platform is needed to mitigate these risks by supporting a new generation of technologies and employing advanced analytical and predictive modeling techniques to enable crew autonomy for future exploration missions. The Crew Health and Performance Integrated Data System Platform (CHP-IDSP) project is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. This cohesive integration point will streamline the management of CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.) and facilitate situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the ongoing development effort of the path-to-flight CHP-IDSP software and the demonstration of its core capabilities. This includes a brief history of the project, the human-centered process used to identify data needs and workflows feeding the development of scenarios and requirements, and current subsystem development status. Current integrations, including the Chiron exploration electronic health record application, will be discussed. Future work includes collaboration with additional CHP domains and a flight technology demonstration.

Software↗
NASA NTRS2024

Idaho & Oregon Agriculture: Monitoring Vegetation Impacts of Livestock Management Practices Used to Reduce Predator Conflicts on Idaho and Oregon Grazing Allotments

The practice of night penning, which involves corralling livestock into a fenced, secure area overnight, aims to safeguard animals from predators. Although this method has proven successful in minimizing interactions between livestock and wildlife, the extent of its impact on vegetation communities is still being explored. This project examines the feasibility of using Net Primary Productivity (NPP) values from the Rangeland Analysis Platform (RAP) to quantify the impacts of night penning on rangeland vegetation communities. RAP provides spatially distributed values of vegetation composition, cover, and productivity, and is derived from imagery from Landsat 5, Landsat 7 & Landsat 8 at a 30m resolution for rangelands across the United States. Our DEVELOP team partnered with Alderspring Ranch, Krebs Livestock, and the U.S Department of Agriculture Animal & Plant Health Inspection Service (APHIS) to analyze the impacts of night penning on vegetation communities. We identified control sites that captured the topographic characteristics of night pen sites used by our partners. We then quantified and compared changes in annual NPP between night pen and control sites. Our analysis of RAP NPP data, using a control-treatment design did not find impacts of night penning on vegetation. However, this was a preliminary analysis, and does not conclusively quantify the impacts of night penning on rangeland vegetation. Our analysis indicated that RAP may be a feasible tool to study livestock management impacts on rangeland vegetation; however, future studies could further validate these findings through ground observations.

Rangeland Analysis Platform (RAP)↗