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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

REVEAL: Software Documentation and Platform Migration

The Research Environment for Vehicle Embedded Analysis on Linux (REVEAL) is reconfigurable data acquisition software designed for network-distributed test and measurement applications. In development since 2001, it has been successfully demonstrated in support of a number of actual missions within NASA's Suborbital Science Program. Improvements to software configuration control were needed to properly support both an ongoing transition to operational status and continued evolution of REVEAL capabilities. For this reason the project described in this report targets REVEAL software source documentation and deployment of the software on a small set of hardware platforms different from what is currently used in the baseline system implementation. This presentation specifically describes the actions taken over a ten week period by two undergraduate student interns and serves as an overview of the content of the final report for that internship.

Wilson, Michael A.↗
NASA NTRS2005

Deployable Wide-Aperture Array Antennas

Inexpensive, lightweight array antennas on flexible substrates are under development to satisfy a need for large-aperture antennas that can be stored compactly during transport and deployed to full size in the field. Conceived for use aboard spacecraft, antennas of this type also have potential terrestrial uses . most likely, as means to extend the ranges of cellular telephones in rural settings. Several simple deployment mechanisms are envisioned. One example is shown in the figure, where the deployment mechanism, a springlike material contained in a sleeve around the perimeter of a flexible membrane, is based on a common automobile window shade. The array can be formed of antenna elements that are printed on small sections of semi-flexible laminates, or preferably, elements that are constructed of conducting fabric. Likewise, a distribution network connecting the elements can be created from conventional technologies such as lightweight, flexible coaxial cable and a surface mount power divider, or preferably, from elements formed from conductive fabrics. Conventional technologies may be stitched onto a supporting flexible membrane or contained within pockets that are stitched onto a flexible membrane. Components created from conductive fabrics may be attached by stitching conductive strips to a nonconductive membrane, embroidering conductive threads into a nonconductive membrane, or weaving predetermined patterns directly into the membrane. The deployable antenna may comprise multiple types of antenna elements. For example, thin profile antenna elements above a ground plane, both attached to the supporting flexible membrane, can be used to create a unidirectional boresight radiation pattern. Or, antenna elements without a ground plane, such as bow-tie dipoles, can be attached to the membrane to create a bidirectional array such as that shown in the figure. For either type of antenna element, the dual configuration, i.e., elements formed of slots in a conductive membrane, can also be used. Finally, wide bandwidth antennas or arrays can be formed in which the principal direction of radiation is in the plane of the membrane. For this embodiment, the set of elements on the membrane is arranged to form one or more traveling wave antennas. In this case, a nonconductive form of the perimeter springlike material is required to provide the deploying force.

Fink, Patrick W.↗
NASA NTRS2014

The Use of Software Agents for Autonomous Control of a DC Space Power System

In order to enable manned deep-space missions, the spacecraft must be controlled autonomously using on-board algorithms. A control architecture is proposed to enable this autonomous operation for an spacecraft electric power system and then implemented using a highly distributed network of software agents. These agents collaborate and compete with each other in order to implement each of the control functions. A subset of this control architecture is tested against a steadystate power system simulation and found to be able to solve a constrained optimization problem with competing objectives using only local information.

autonomous control↗
NASA NTRS2013

DESDynI Quad First Stage Processor - A Four Channel Digitizer and Digital Beam Forming Processor

The proposed Deformation, Eco-Systems, and Dynamics of Ice Radar (DESDynI-R) L-band SAR instrument employs multiple digital channels to optimize resolution while keeping a large swath on a single pass. High-speed digitization with very fine synchronization and digital beam forming are necessary in order to facilitate this new technique. The Quad First Stage Processor (qFSP) was developed to achieve both the processing performance as well as the digitizing fidelity in order to accomplish this sweeping SAR technique. The qFSP utilizes high precision and high-speed analog to digital converters (ADCs), each with a finely adjustable clock distribution network to digitize the channels at the fidelity necessary to allow for digital beam forming. The Xilinx produced FX130T Virtex 5 part handles the processing to digitally calibrate each channel as well as filter and beam form the receive signals. Demonstrating the digital processing required for digital beam forming and digital calibration is instrumental to the viability of the proposed DESDynI instrument. The qFSP development brings this implementation to Technology Readiness Level (TRL) 6. This paper will detail the design and development of the prototype qFSP as well as the preliminary results from hardware tests.

Chuang, Chung-Lun↗
NASA NTRS2016

Solar vs. Fission Surface Power for Mars

A multi-discipline team of experts from the National Aeronautics and Space Administration (NASA) developed Mars surface power system point design solutions for two conceptual missions. The primary goal of this study was to compare the relative merits of solar- versus fission-powered versions of each surface mission. First, the team compared three different solar power options against a fission power system concept for a sub-scale, uncrewed demonstration mission. The 4.5 meter (m) diameter pathfinder lander's primary mission would be to demonstrate Mars entry, descent, and landing techniques. Once on the Martian surface, the lander's In Situ Resource Utilization (ISRU) payload would demonstrate liquid oxygen propellant production using atmospheric resources. For the purpose of this exercise, location was assumed to be at the Martian equator. The three solar concepts considered included a system that only operated during daylight hours (at roughly half the daily propellant production rate of a round-the-clock fission design), a battery-augmented system that operated through the night (matching the fission concept's propellant production rate), and a system that operated only during daylight, but at a higher rate (again, matching the fission concept's propellant production rate). Including 30% mass growth allowance, total payload masses for the three solar concepts ranged from 1,116 to 2,396 kg, versus the 2,686 kg fission power scheme. However, solar power masses are expected to approach or exceed the fission payload mass at landing sites further from the equator, making landing site selection a key driver in the final power system decision. The team also noted that detailed reliability analysis should be performed on daytime-only solar power schemes to assess potential issues with frequent ISRU system on/off cycling. Next, the team developed a solar-powered point design solution for a conceptual four-crew, 500-day surface mission consisting of up to four landers per crewed expedition mission. Unlike the demonstration mission, a lengthy power outage due to the global dust storms that are known to occur on Mars would pose a safety hazard to a crewed mission. A similar fission versus solar power trade study performed by NASA in 2007 concluded that fission power was more reliable-with a much lower mass penalty-than solar power for this application. However, recent advances in solar cell and energy storage technologies and changes in operational assumptions prompted NASA to revisit the analysis. For the purpose of this exercise a particular landing site at Jezero Crater, located at 18o north latitude, was assumed. A fission power system consisting of four each 10 kW Kilopower fission reactors was compared to a distributed network of Orion-derived Ultraflex solar arrays and Lithium ion batteries mounted on every lander. The team found that a solar power system mass of about 9,800 kg would provide the 22 kilowatts (kW) keep-alive power needed to survive a dust storm lasting up to 120-days at average optical depth of 5, and 35 kW peak power for normal operations under clear skies. Although this is less than half the mass estimated during the 2007 work (which assumed latitudes up to 30o) it is still more than the 7,000 kg mass of the fission system which provides full power regardless of dust storm conditions.

Rucker, Michelle A.↗
NASA NTRS2016

An Integrated Gate Turnaround Management Concept Leveraging Big Data/Analytics for NAS Performance Improvements

The Integrated Gate Turnaround Management (IGTM) concept was developed to improve the gate turnaround performance at the airport by leveraging relevant historical data to support optimization of airport gate operations, which include: taxi to the gate, gate services, push back, taxi to the runway, and takeoff, based on available resources, constraints, and uncertainties. By analyzing events of gate operations, primary performance dependent attributes of these events were identified for the historical data analysis such that performance models can be developed based on uncertainties to support descriptive, predictive, and prescriptive functions. A system architecture was developed to examine system requirements in support of such a concept. An IGTM prototype was developed to demonstrate the concept using a distributed network and collaborative decision tools for stakeholders to meet on time pushback performance under uncertainties.

Big Data and Net-enabled ATM↗
NASA NTRS2016

A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Agricultural↗
NASA NTRS2018

Sensor Arrays for Aerospace Vehicles

Advances in highly scalable sensors, wireless networks, distributed computing and data fusion algorithms enable significant improvements in high-level information-centric state determination for adaptable and autonomous aerospace vehicles. The objective is to increase insight into structural response of space vehicles and insight into the aerodynamics of new aircraft.

Alena, Richard↗
NASA NTRS2018

Status of Aquarius and Salinity Continuity

Aquarius is an L-band radar/radiometer instrument combination that has been designed to measure ocean salinity. It was launched on 10 June 2011 as part of the Aquarius/SAC-D observatory. The observatory is a partnership between the United States National Aeronautics and Space Agency (NASA), which provided Aquarius, and the Argentinian space agency, Comisin Nacional de Actividades Espaciales (CONAE), which provided the spacecraft bus, Satelite de Aplicaciones Cientificas (SAC-D). The observatory was lost four years later on 7 June 2015 when a failure in the power distribution network resulted in the loss of control of the spacecraft. The Aquarius Mission formally ended on 31 December 2017. The last major milestone was the release of the final version of the salinity retrieval (Version 5). Version 5 meets the mission requirements for accuracy, and reflects the continuing progress and understanding developed by the science team over the lifetime of the mission. Further progress is possible, and several issues remained unresolved at the end of the mission that are relevant to future salinity retrievals. The understanding developed with Aquarius is being transferred to radiometer observations over the ocean from NASA's Soil Moisture Active Passive (SMAP) satellite, and salinity from SMAP with accuracy approaching that of Aquarius are already being produced.

microwave remote sensing↗
NASA NTRSDate not supplied

Signal and Power Integrity Design Methodology for High-Performance Flight Computing Systems

Computing capabilities of space systems have in-creased onboard performance by orders of magnitude with the use of radiation-tolerant field-programmable gate arrays (FPGA)and processors. The incorporation of signal and power integrity analysis with printed circuit board (PCB) design in reliable computing architectures for space systems has become critical to enable future mission capabilities. Developers launch high-performance processors into a breadth of orbits and missions, running varying applications that create challenges for designing reliable computing hardware. Specifically, for these designs, academic and industry research has focused on component radiation performance, fault mitigation, and reliable architectures. How-ever, other design parameters including electromagnetic interference (EMI), PCB stackup, signal integrity (SI), voltage regulator module (VRM) design, and power distribution network (PDN)are often deprioritized or disregarded as the design matures. Since these characteristics are becoming more significant in high-performance processor designs, this research presents a hardware design and analysis methodology for high-performance, space-computing systems that focuses on a holistic design approach and PDN reliability. While these challenges exist across all space hardware, the reduced PCB dimensions imposed by SmallSats and CubeSats introduce additional hurdles, specifically to VRM and decoupling design. By examining the relationship between the PDN and radiation performance, an analytical relationship is developed that incorporates Total Ionizing Dose and Single-Event Transients to ensure reliability throughout the mission duration. The presented design methodology is applied to the SpaceCube v3.0 Mini, an FPGA-based on-board science data processing system developed at NASA Goddard Space Flight Center.

Advanced avionics↗
NASA NTRSDate not supplied

Reasoning Service Exemplars for NASA’s Data and Reasoning Fabric

Future operations for Urban and Advanced Air Mobility are enabled by a distributed network of reliable and secured data and reasoning services referred to here as a fabric. In the aggregate, such a system must be all encompassing and mission agnostic, but specific use-cases are still needed to improve understanding and drive design paradigms. For this purpose, three reasoning service exemplars for Target Selection and Routing, Trajectory Generation, and Battery Health Management were developed and integrated into a specific NASA proposed data and reasoning fabric. These services were then used to build a mission reasoning application for lightning strike reconnaissance developed in collaboration with the Civil Air Patrol. Autonomous mission execution was then demonstrated using a multivehicle simulation platform with a full envelope 6 Degree-of-Freedom dynamics model for a concept electric Vertical Takeoff and Landing aircraft.

Autonomy↗
NASA NTRSDate not supplied

Experimental Testing of Data Fusion in A Distributed Ground-Based Sensing Network for Advanced Air Mobility

Advanced Air Mobility (AAM) is an active area of development which foresees the integration of autonomous uncrewed aircraft into the civil airspace for air transportation of people and cargo. Safe integration requires significant technological developments and extensive testing phases of sensing and surveillance strategies in dense airspace. Compared to well-assessed manned aviation systems scenarios, surveillance strategies in the AAM and small Uncrewed Aircraft Vehicles(UAVs) context need to detect smaller platforms flying at lower altitude against cluttered backgrounds in dense airspace. Fusion of data provided by a network of distributed sensing nodes is a powerful tool to enable detection and tracking in such complex conditions. This paper contributes to this research direction by proposing a surveillance strategy for the AAM environment based on sensor fusion of data acquired by distributed ground-based radars. Specifically, experimental data collected with two independent radars, observing the flight of two small UAVs, are used. Data fusion at tracking level is based on a leader-helper strategy where the leader radar uses the helper’s measurements to increase the lifespan of its generated tracks. This solution shows promising results with a 10%increase in track coverage with respect to the standalone leader radar tracking solution. The paper also proposes an interference removal processing method which is applied on the data collected by one of the two radars.

Federica Vitiello↗
DOE OSTI2026

Measurement-informed Dynamic Aggregation of Distribution Systems

This paper proposes a measurement-informed dynamic aggregation methodology in order to create equivalent representations of distribution systems that are compatible with large-scale transmission analysis. By optimizing an equivalent feeder parameters using time-series measurements of active power, reactive power, and voltage at the Point of Interconnection (POI), the approach yields simplified yet dynamically accurate equivalents. Implemented in PSCAD with models of photovoltaic–battery systems, three-phase motors, and static loads, the method employs hybrid differential evolution and bounded least-squares optimization laying the foundation for for real-time state estimation and optimized sensor placement in distribution networks.

Ahmed, Kazi Ishrak [University of Tennessee, Knoxv↗
DOE OSTI2025

Network Anomaly Detection in Distributed Edge Computing Infrastructure

As networks continue to grow in complexity and scale, detecting anomalies has become increasingly challenging, particularly in diverse and geographically dispersed environments. Traditional approaches often struggle with managing the computational burden associated with analyzing large-scale network traffic to identify anomalies. This paper introduces a distributed edge computing framework that integrates federated learning with Apache Spark and Kubernetes to address these challenges. We hypothesize that our approach, which enables collaborative model training across distributed nodes, significantly enhances the detection accuracy of network anomalies across different network types. We show that by leveraging distributed computing and containerization technologies, our framework not only improves scalability and fault tolerance but also achieves superior detection performance compared to state-of-the-art methods. Extensive experiments on the UNSW-NB15 and ROAD datasets validate the effectiveness of our approach, demonstrating statistically significant improvements in detection accuracy and training efficiency over baseline models, as confirmed by MannWhitney U and Kolmogorov-Smirnov tests (p<0.05).

Marfo, William [University of Texas at El Paso,Dep↗