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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 1,135 records · Page 63

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NASA NTRS2004

NASA Tech Briefs, August 2004

Topics covered include: Data Relay Board with Protocol for High-Speed, Free-Space Optical Communications; Software and Algorithms for Biomedical Image Data Processing and Visualization; Rapid Chemometric Filtering of Spectral Data; Prioritizing Scientific Data for Transmission; Determining Sizes of Particles in a Flow from DPIV Data; Faster Processing for Inverting GPS Occultation Data; FPGA-Based, Self-Checking, Fault-Tolerant Computers; Ultralow-Power Digital Correlator for Microwave Polarimetry; Grounding Headphones for Protection Against ESD; Lightweight Stacks of Direct Methanol Fuel Cells; Highly Efficient Vector-Inversion Pulse Generators; Estimating Basic Preliminary Design Performances of Aerospace Vehicles; Framework for Development of Object-Oriented Software; Analyzing Spacecraft Telecommunication Systems; Collaborative Planning of Robotic Exploration; Tools for Administration of a UNIX-Based Network; Preparing and Analyzing Iced Airfoils; Evaluating Performance of Components; Fuels Containing Methane of Natural Gas in Solution; Direct Electrolytic Deposition of Mats of MnxOy Nanowires; Bubble Eliminator Based on Centrifugal Flow; Inflatable Emergency Atmospheric-Entry Vehicles; Lightweight Deployable Mirrors with Tensegrity Supports; Centrifugal Adsorption Cartridge System; Ultrasonic Apparatus for Pulverizing Brittle Material; Transplanting Retinal Cells using Bucky Paper for Support; Using an Ultrasonic Instrument to Size Extravascular Bubbles; Coronagraphic Notch Filter for Raman Spectroscopy; On-the-Fly Mapping for Calibrating Directional Antennas; Working Fluids for Increasing Capacities of Heat Pipes; Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds; Liquid-Metal-Fed Pulsed Plasma Thrusters; Personal Radiation Protection System; and Attitude Control for a Solar-Sail Spacecraft.

Source record↗

NASA NTRS2005

Gas Concentration Mapping of Arenal Volcano Using AVEMS

The Airborne Volcanic Emissions Mass Spectrometer (AVEMS) System developed by NASA-Kennedy Space Center and deployed in collaboration with the National Center for Advanced Technology (CENAT) and the University of Costa Rica was used for mapping the volcanic plume of Arenal Volcano, the most active volcano in Costa Rica. The measurements were conducted as part of the second CARTA (Costa Rica Airborne Research and Technology Application) mission conducted in March 2005. The CARTA 2005 mission, involving multiple sensors and agencies, consisted of three different planes collecting data over all of Costa Rica. The WB-57F from NASA collected ground data with a digital camera, an analog photogrametric camera (RC-30), a multispectral scanner (MASTER) and a hyperspectral sensor (HYMAP). The second aircraft, a King Air 200 from DoE, mounted with a LIDAR based instrument, targeted topography mapping and forest density measurements. A smaller third aircraft, a Navajo from Costa Rica, integrated with the AVEMS instrument and designed for real-time measurements of air pollutants from both natural and anthropogenic sources, was flown over the volcanoes. The improved AVEMS system is designed for deployment via aircraft, car or hand-transport. The 85 pound system employs a 200 Da quadrupole mass analyzer, has a volume of 92,000 cubic cm, requires 350 W of power at steady state, can operate up to an altitude of 41,000 feet above sea level (-65 C; 50 torr). The system uses on-board gas bottles on-site calibration and is capable of monitoring and quantifying up to 16 gases simultaneously. The in-situ gas data in this work, consisting of helium, carbon dioxide, sulfur dioxide and acetone, was acquired in conjunction of GPS data which was plotted with the ground imagery, topography and remote sensing data collected by the other instruments, allowing the 3 dimensional visualization of the volcanic plume at Arenal Volcano. The modeling of possible scenarios of Arenal s activity and its direct impact on the surrounding populated areas in now possible with the combined set of data, linking in-situ data with remote sensing data. The study also helps in the understanding of pyroclastic flow behavior in case of a major eruption.

Diaz, J. Andres↗

NASA NTRS2009

A Renewably Powered Hydrogen Generation and Fueling Station Community Project

The proposed project goal is to encourage the use of renewable energy and clean fuel technologies for transportation and other applications while generating economic development. This can be done by creating an incubator for collaborators, and creating a manufacturing hub for the energy economy of the future by training both white- and blue-collar workers for the new energy economy. Hydrogen electrolyzer fueling stations could be mass-produced, shipped and installed in collaboration with renewable energy power stations, or installed connected to the grid with renewable power added later.

Lyons, Valerie J.↗

NASA NTRS2013

Evaluation of the Terminal Sequencing and Spacing System for Performance Based Navigation Arrivals

NASA has developed the Terminal Sequencing and Spacing (TSS) system, a suite of advanced arrival management technologies combining timebased scheduling and controller precision spacing tools. TSS is a ground-based controller automation tool that facilitates sequencing and merging arrivals that have both current standard ATC routes and terminal Performance-Based Navigation (PBN) routes, especially during highly congested demand periods. In collaboration with the FAA and MITRE's Center for Advanced Aviation System Development (CAASD), TSS system performance was evaluated in human-in-the-loop (HITL) simulations with currently active controllers as participants. Traffic scenarios had mixed Area Navigation (RNAV) and Required Navigation Performance (RNP) equipage, where the more advanced RNP-equipped aircraft had preferential treatment with a shorter approach option. Simulation results indicate the TSS system achieved benefits by enabling PBN, while maintaining high throughput rates-10% above baseline demand levels. Flight path predictability improved, where path deviation was reduced by 2 NM on average and variance in the downwind leg length was 75% less. Arrivals flew more fuel-efficient descents for longer, spending an average of 39 seconds less in step-down level altitude segments. Self-reported controller workload was reduced, with statistically significant differences at the p less than 0.01 level. The RNP-equipped arrivals were also able to more frequently capitalize on the benefits of being "Best-Equipped, Best- Served" (BEBS), where less vectoring was needed and nearly all RNP approaches were conducted without interruption.

terminal sequencing↗

NASA NTRS2014

Propulsion Electric Grid Simulator (PEGS) for Future Turboelectric Distributed Propulsion Aircraft

NASA Glenn Research Center, in collaboration with the aerospace industry and academia, has begun the development of technology for a future hybrid-wing body electric airplane with a turboelectric distributed propulsion (TeDP) system. It is essential to design a subscale system to emulate the TeDP power grid, which would enable rapid analysis and demonstration of the proof-of-concept of the TeDP electrical system. This paper describes how small electrical machines with their controllers can emulate all the components in a TeDP power train. The whole system model in Matlab/Simulink was first developed and tested in simulation, and the simulation results showed that system dynamic characteristics could be implemented by using the closed-loop control of the electric motor drive systems. Then we designed a subscale experimental system to emulate the entire power system from the turbine engine to the propulsive fans. Firstly, we built a system to emulate a gas turbine engine driving a generator, consisting of two permanent magnet (PM) motors with brushless motor drives, coupled by a shaft. We programmed the first motor and its drive to mimic the speed-torque characteristic of the gas turbine engine, while the second motor and drive act as a generator and produce a torque load on the first motor. Secondly, we built another system of two PM motors and drives to emulate a motor driving a propulsive fan. We programmed the first motor and drive to emulate a wound-rotor synchronous motor. The propulsive fan was emulated by implementing fan maps and flight conditions into the fourth motor and drive, which produce a torque load on the driving motor. The stator of each PM motor is designed to travel axially to change the coupling between rotor and stator. This feature allows the PM motor to more closely emulate a wound-rotor synchronous machine. These techniques can convert the plain motor system into a unique TeDP power grid emulator that enables real-time simulation performance using hardware-in-the-loop (HIL).

electric power grid emulator↗

NASA NTRS2010

Evaluating the Performance of Unmanned Ground Vehicle Water Detection

Water detection is a critical perception requirement for unmanned ground vehicle (UGV) autonomous navigation over cross-country terrain. During the Robotics Collaborative Technology Alliances (RCTA) program, the Jet Propulsion Laboratory (JPL) developed a set of water detection algorithms that are used to detect, localize, and avoid water bodies large enough to be a hazard to a UGV. The JPL water detection software performs the detection and localization stages using a forward-looking stereo pair of color cameras. The 3D coordinates of water body surface points are then output to a UGV's autonomous mobility system, which is responsible for planning and executing safe paths. There are three primary methods for evaluating the performance of the water detection software. Evaluations can be performed in image space on the intermediate detection product, in map space on the final localized product, or during autonomous navigation to characterize the avoidance of a variety of water bodies. This paper describes a methodology for performing the first two types of water detection performance evaluations.

stereo vision↗

NASA NTRS2016

The Matsu Wheel: A Cloud-Based Framework for Efficient Analysis and Reanalysis of Earth Satellite Imagery

Project Matsu is a collaboration between the Open Commons Consortium and NASA focused on developing open source technology for cloud-based processing of Earth satellite imagery with practical applications to aid in natural disaster detection and relief. Project Matsu has developed an open source cloud-based infrastructure to process, analyze, and reanalyze large collections of hyperspectral satellite image data using OpenStack, Hadoop, MapReduce and related technologies. We describe a framework for efficient analysis of large amounts of data called the Matsu "Wheel." The Matsu Wheel is currently used to process incoming hyperspectral satellite data produced daily by NASA's Earth Observing-1 (EO-1) satellite. The framework allows batches of analytics, scanning for new data, to be applied to data as it flows in. In the Matsu Wheel, the data only need to be accessed and preprocessed once, regardless of the number or types of analytics, which can easily be slotted into the existing framework. The Matsu Wheel system provides a significantly more efficient use of computational resources over alternative methods when the data are large, have high-volume throughput, may require heavy preprocessing, and are typically used for many types of analysis. We also describe our preliminary Wheel analytics, including an anomaly detector for rare spectral signatures or thermal anomalies in hyperspectral data and a land cover classifier that can be used for water and flood detection. Each of these analytics can generate visual reports accessible via the web for the public and interested decision makers. The result products of the analytics are also made accessible through an Open Geospatial Compliant (OGC)-compliant Web Map Service (WMS) for further distribution. The Matsu Wheel allows many shared data services to be performed together to efficiently use resources for processing hyperspectral satellite image data and other, e.g., large environmental datasets that may be analyzed for many purposes.

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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 NTRS2017

Virtualized Multi-Mission Operations Center (vMMOC) and its Cloud Services

His presentation will cover, the current and future, technical and organizational opportunities and challenges with virtualizing a multi-mission operations center. The full deployment of Goddard Space Flight Centers (GSFC) Virtualized Multi-Mission Operations Center (vMMOC) is nearly complete. The Space Science Mission Operations (SSMO) organizations spacecraft ACE, Fermi, LRO, MMS(4), OSIRIS-REx, SDO, SOHO, Swift, and Wind are in the process of being fully migrated to the vMMOC. The benefits of the vMMOC will be the normalization and the standardization of IT services, mission operations, maintenance, and development as well as ancillary services and policies such as collaboration tools, change management systems, and IT Security. The vMMOC will also provide operational efficiencies regarding hardware, IT domain expertise, training, maintenance and support.The presentation will also cover SSMO's secure Situational Awareness Dashboard in an integrated, fleet centric, cloud based web services fashion. Additionally the SSMO Telemetry as a Service (TaaS) will be covered, which allows authorized users and processes to access telemetry for the entire SSMO fleet, and for the entirety of each spacecrafts history. Both services leverage cloud services in a secure FISMA High and FedRamp environment, and also leverage distributed object stores in order to house and provide the telemetry. The services are also in the process of leveraging the cloud computing services elasticity and horizontal scalability. In the design phase is the Navigation as a Service (NaaS) which will provide a standardized, efficient, and normalized service for the fleet's space flight dynamics operations. Additional future services that may be considered are Ground Segment as a Service (GSaaS), Telemetry and Command as a Service (TCaaS), Flight Software Simulation as a Service, etc.

Ido, Haisam Kassim↗

NASA NTRS2017

NASA Advanced Computing Environment for Science and Engineering

Vision: To reach for new heights and reveal the unknown so that what we do and learn will benefit all humankind. Mission: To pioneer the future in space exploration, scientific discovery, and aeronautics research. Aeronautics Research (ARMD): Pioneer and prove new flight technologies for safer, more secure, efficient, and environmental friendly air transportation. Human Exploration and Operations (HEOMD): Focus on ISS operations; and develop new spacecraft and other capabilities for affordable, sustainable exploration beyond low Earth orbit. Science (SCMD): Explore the Earth, solar system, and universe beyond; chart best route for discovery; and reap the benefits of Earth and space exploration for society. Space Technology (STMD): Rapidly develop, demonstrate, and infuse revolutionary, high-payoff technologies through collaborative partnerships, expanding the boundaries of aerospace enterprise.

Biswas, Rupak↗

NASA NTRS2018

Operational Impact of the Baseline Integrated Arrival, Departure, and Surface System Field Demonstration

To address the Integrated Arrival, Departure, and Surface (IADS) challenge, NASA is developing and demonstrating trajectory-based departure automation under a collaborative effort with the FAA and industry known as Airspace Technology Demonstration 2 (ATD-2). ATD-2 builds upon and integrates previous NASA research capabilities that include the Spot and Runway Departure Advisor (SARDA), the Precision Departure Release Capability (PDRC), and the Terminal Sequencing and Spacing (TSAS) capability. The ATD-2 field demonstration is organized into three phases. Phase I illustrates a Baseline IADS demonstration and includes all components of ATD-2 running in operational environments. Subsequent phases will fuse together strategic scheduling components as well as take into account metroplex considerations. This paper describes the baseline IADS system that was deployed at the end of 2017 and is continuing to run as part of the ATD-2 demonstration taking place at Charlotte-Douglas International Airport (CLT). The primary areas of deployment and system use are in the CLT Air Traffic Control Tower, CLT TRACON, CLT American Airlines ramp tower, Washington Center facility and American Airlines Integration Operations Center (IOC). In addition to describing the functions and capabilities that are part of the baseline IADS system, this paper also provides metrics regarding operational use as well as initial benefits metrics. Benefit metrics continue to be collected and aggregated across the areas of system delay, throughput, taxi time, fuel burn savings, and emissions savings. Furthermore, benefits as a result of common awareness of delays and the impact of takeoff and departure restrictions stemming from traffic flow management initiatives are described. The overall benefit of improved predictability and efficiency as a result of the baseline IADS system demonstration is also discussed.

operational system↗

NASA NTRS2020

NASA Electronic Parts & Packaging (NEPP) Program

The purpose of this presentation is to familiarize the people attending the JEDEC work meetings about the NEPP Program, and recent tasks we have undertaken. There is a description of the policy and testing guidelines in development and an explanation of the Government Working Group, a collaboration of several US government space agencies that come together to discuss topics relating to the reliable use of electronics. The presentation also includes a brief description of recent NASA accomplishments such as the launching/splash down of the SpaceX Crew Dragon and the launch of the next Mars rover.

reliability↗

NASA NTRS2021

NASA Electronic Parts & Packaging (NEPP) Program

The purpose of this presentation is to familiarize the people attending the JEDEC work meetings about the NEPP Program, and recent tasks we have undertaken. There is a description of the policy and testing guidelines in development and an explanation of the Government Working Group, a collaboration of several US government space agencies that come together to discuss topics relating to the reliable use of electronics. The presentation also includes a brief description of NASA events such as the landing of the next Mars rover in Feb 2021.

reliability↗

NASA NTRS2022

Rainfall-induced Landslide Inventories for Lower Mekong Based on Planet Imagery and a Semi-Automatic Mapping Method

Fatal landslides occur every year during the rainy season (June–November) in the Lower Mekong Region (LMR). There is an urgent need to develop a landslide early warning system in the LMR. In collaboration with the Asian Disasters Preparedness Center and NASA’s SERVIR Programme, we are regionalizing the global Landslide Hazard Assessment System for Situational Awareness model for the LMR (LHASA-Mekong). A robust set of landslide inventories are needed to effectively train the machine learning-based LHASA-Mekong model. In this study, the Semi-Automatic Landslide Detection (SALaD) system was modified by incorporating a change detection module (SALaD-CD) to produce rainfall event-based landslide inventories using pre- and post-imagery from RapidEye and PlanetScope for various locations in the LMR that were identified based on media and government reports. These rainfall-induced landslides are published as initiation points for ease of use. In total, we created 22 inventories: 2 in Laos, 4 in Myanmar, 1 in Thailand and 15 in Vietnam. These inventories are being used to train the LHASA-Mekong model and quantify the effects of Land use/Land cover change on landslide susceptibility. These open data will be a valuable resource for advancing landslide studies in this region.

Pukar Amatya↗

NASA NTRS2021

NASA’s Surface Deformation and Change Mission Study

The National Academies of Science, Engineering and Medicine 2017 Decadal Survey of Earth Science and Applications identified geodetic measurements of surface deformation and related change as one of the top five “observables” to be prioritized in NASA’s future program. In response, NASA commissioned a multi-center Surface Deformation and Change(SDC) team to perform a five year study of mission architectures that would support SDC observables and provide the most value to the diverse science and applications communities it serves. The study is being conducted in phases, in which the science and applications capabilities identified in the Decadal Survey are refined, candidate architectures and associated technologies to support these needs are identified, architectures are assessed against a science value framework specific to SDC, and recommendations to NASA are made. Ultimately, NASA will decide which amongst these recommendations will proceed to mission formulation. As synthetic aperture radar (SAR) was identified as the prime sensor technology to satisfy SDC observational needs, a key component of the SDC study is to assess the current state of the art in SAR sensor and supporting technology. The number of SAR systems, both civil and commercial, is growing rapidly, requiring that mission architectures not only consider technology, but availability of data from other missions, possible partnerships or collaborations, and even data purchase. The mechanism for assessment involves development of an end-to-end science performance evaluation tool for multi-satellite con-stellations, which feeds into a science value framework that con-siders science performance, technological programmatic risks, and cost. This paper will present an overview of the ongoing study including the candidate architectures and the technology road map needed to achieve the objectives of the mission.

Stephen Horst↗

NASA NTRS2021

NASA's Surface Deformation and Change Mission Study

The National Academies of Science, Engineering and Medicine 2017 Decadal Survey of Earth Science and Applications identified geodetic measurements of surface deformation and related change as one of the top five "observables" to be prioritized in NASA's program going forward. In response, NASA commissioned a multi-center Surface Deformation and Change (SDC) team to perform a five year study of mission architectures that would support SDC observables and provide the most value to the diverse science and applications communities it serves. The study is being conducted in phases, in which the science and applications capabilities identified in the Decadal Survey are interpreted and refined, candidate mission architectures and associated technologies to support these needs are identified, architectures are assessed against a science value framework specific to SDC, and recommendations to NASA are made. Ultimately, NASA will decide which amongst these recommendations will proceed to mission formulation. As synthetic aperture radar (SAR) was identified as the prime sensor technology to satisfy SDC observational needs, a key component of the SDC study is to assess the current state of the art in SAR sensor and spacecraft systems and components. The number of SAR systems, both civil and commercial, is growing rapidly, requiring that mission architectures not only consider technology, but availability of data from other missions, possible partnerships or collaborations, and even data purchase. The mechanism for assessment involves development of an end-to-end science performance evaluation tool for multi-satellite constellations, which feeds into a science value framework that considers science performance, technological programmatic risks, and cost. This paper will present an overview of the ongoing study including the architectures under consideration and the technology road map needed to achieve the objectives of the mission.

Rosen, Paul↗

NASA NTRSDate not supplied

Kamodo’s Satellite Constellation Mission Planning Tool

Kamodo provides a functional model-agnostic interface to a growing collection of Heliophysics model outputs. The CCMC, in collaboration with the Geospace Dynamics Constellation Science Team, has recently developed Kamodo’s satellite constellation mission planning tool to perform reconstructions in any pair of dimensions, including time. The ‘reconstruction’ tool enables users to fly any 4-dimensional grid of satellites through a given model data set, reconstructing what the given constellation would observe during the mission. This capability facilitates determination of what satellite configuration is best for a given science question, even allowing comparison across multiple models. This tool, written in Python, is built upon Kamodo’s flythrough tool, which in turn depends on a growing network of model-specific interfaces. Since each model interface is designed with model-agnostic syntax, the flythrough tool and the satellite constellation mission planning tool also feature model-agnostic syntax. In this work, we will describe the basic analysis choices available in the tool and provide a variety of sample workflows. The tool is freely available at https://github.com/nasa/Kamodo for the public. We invite the community to use the reconstruction tool and adapt the provided workflows for their mission planning, and to contribute their own workflows to share with others.

software↗

NASA NTRSDate not supplied

SM25C-2002: Kamodo’s Satellite Constellation Mission Planning Tool

python↗