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NASA NTRS2008

Halbach Magnetic Rotor Development

The NASA John H. Glenn Research Center has a wealth of experience in Halbach array technology through the Fundamental Aeronautics Program. The goals of the program include improving aircraft efficiency, reliability, and safety. The concept of a Halbach magnetically levitated electric aircraft motor will help reduce harmful emissions, reduce the Nation s dependence on fossil fuels, increase efficiency and reliability, reduce maintenance and decrease operating noise levels. Experimental hardware systems were developed in the GRC Engineering Development Division to validate the basic principles described herein and the theoretical work that was performed. A number of Halbach Magnetic rotors have been developed and tested under this program. A separate test hardware setup was developed to characterize each of the rotors. A second hardware setup was developed to test the levitation characteristics of the rotors. Each system focused around a unique Halbach array rotor. Each rotor required original design and fabrication techniques. A 4 in. diameter rotor was developed to test the radial levitation effects for use as a magnetic bearing. To show scalability from the 4 in. rotor, a 1 in. rotor was developed to also test radial levitation effects. The next rotor to be developed was 20 in. in diameter again to show scalability from the 4 in. rotor. An axial rotor was developed to determine the force that could be generated to position the rotor axially while it is rotating. With both radial and axial magnetic bearings, the rotor would be completely suspended magnetically. The purpose of this report is to document the development of a series of Halbach magnetic rotors to be used in testing. The design, fabrication and assembly of the rotors will be discussed as well as the hardware developed to test the rotors.

Gallo, Christopher A.↗

NASA NTRS2011

Virtual Sensor Test Instrumentation

Virtual Sensor Test Instrumentation is based on the concept of smart sensor technology for testing with intelligence needed to perform sell-diagnosis of health, and to participate in a hierarchy of health determination at sensor, process, and system levels. A virtual sensor test instrumentation consists of five elements: (1) a common sensor interface, (2) microprocessor, (3) wireless interface, (4) signal conditioning and ADC/DAC (analog-to-digital conversion/ digital-to-analog conversion), and (5) onboard EEPROM (electrically erasable programmable read-only memory) for metadata storage and executable software to create powerful, scalable, reconfigurable, and reliable embedded and distributed test instruments. In order to maximize the efficient data conversion through the smart sensor node, plug-and-play functionality is required to interface with traditional sensors to enhance their identity and capabilities for data processing and communications. Virtual sensor test instrumentation can be accessible wirelessly via a Network Capable Application Processor (NCAP) or a Smart Transducer Interlace Module (STIM) that may be managed under real-time rule engines for mission-critical applications. The transducer senses the physical quantity being measured and converts it into an electrical signal. The signal is fed to an A/D converter, and is ready for use by the processor to execute functional transformation based on the sensor characteristics stored in a Transducer Electronic Data Sheet (TEDS). Virtual sensor test instrumentation is built upon an open-system architecture with standardized protocol modules/stacks to interface with industry standards and commonly used software. One major benefit for deploying the virtual sensor test instrumentation is the ability, through a plug-and-play common interface, to convert raw sensor data in either analog or digital form, to an IEEE 1451 standard-based smart sensor, which has instructions to program sensors for a wide variety of functions. The sensor data is processed in a distributed fashion across the network, providing a large pool of resources in real time to meet stringent latency requirements.

Wang, Roy↗

NASA NTRS2003

Scalability of a Low-Cost Multi-Teraflop Linux Cluster for High-End Classical Atomistic and Quantum Mechanical Simulations

Scalability of a low-cost, Intel Xeon-based, multi-Teraflop Linux cluster is tested for two high-end scientific applications: Classical atomistic simulation based on the molecular dynamics method and quantum mechanical calculation based on the density functional theory. These scalable parallel applications use space-time multiresolution algorithms and feature computational-space decomposition, wavelet-based adaptive load balancing, and spacefilling-curve-based data compression for scalable I/O. Comparative performance tests are performed on a 1,024-processor Linux cluster and a conventional higher-end parallel supercomputer, 1,184-processor IBM SP4. The results show that the performance of the Linux cluster is comparable to that of the SP4. We also study various effects, such as the sharing of memory and L2 cache among processors, on the performance.

Kikuchi, Hideaki↗

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 NTRS2017

Launch Control System Software Development System Automation Testing

The Spaceport Command and Control System (SCCS) is the National Aeronautics and Space Administration's (NASA) launch control system for the Orion capsule and Space Launch System, the next generation manned rocket currently in development. This system requires high quality testing that will measure and test the capabilities of the system. For the past two years, the Exploration and Operations Division at Kennedy Space Center (KSC) has assigned a group including interns and full-time engineers to develop automated tests to save the project time and money. The team worked on automating the testing process for the SCCS GUI that would use streamed simulated data from the testing servers to produce data, plots, statuses, etc. to the GUI. The software used to develop automated tests included an automated testing framework and an automation library. The automated testing framework has a tabular-style syntax, which means the functionality of a line of code must have the appropriate number of tabs for the line to function as intended. The header section contains either paths to custom resources or the names of libraries being used. The automation library contains functionality to automate anything that appears on a desired screen with the use of image recognition software to detect and control GUI components. The data section contains any data values strictly created for the current testing file. The body section holds the tests that are being run. The function section can include any number of functions that may be used by the current testing file or any other file that resources it. The resources and body section are required for all test files; the data and function sections can be left empty if the data values and functions being used are from a resourced library or another file. To help equip the automation team with better tools, the Project Lead of the Automated Testing Team, Jason Kapusta, assigned the task to install and train an optical character recognition (OCR) tool to Brandon Echols, a fellow intern, and I. The purpose of the OCR tool is to analyze an image and find the coordinates of any group of text. Some issues that arose while installing the OCR tool included the absence of certain libraries needed to train the tool and an outdated software version. We eventually resolved the issues and successfully installed the OCR tool. Training the tool required many images and different fonts and sizes, but in the end the tool learned to accurately decipher the text in the images and their coordinates. The OCR tool produced a file that contained significant metadata for each section of text, but only the text and coordinates of the text was required for our purpose. The team made a script to parse the information we wanted from the OCR file to a different file that would be used by automation functions within the automated framework. Since a majority of development and testing for the automated test cases for the GUI in question has been done using live simulated data on the workstations at the Launch Control Center (LCC), a large amount of progress has been made. As of this writing, about 60% of all of automated testing has been implemented. Additionally, the OCR tool will help make our automated tests more robust due to the tool's text recognition being highly scalable to different text fonts and text sizes. Soon we will have the whole test system automated, allowing for more full-time engineers working on development projects.

Automation↗

NASA NTRS2014

Evolution of the JPSS Ground Project Calibration and Validation System

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administrations (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAAs mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation’s economy and protection of lives and property. The National Aerospace and Atmospheric Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Data Processing↗

NASA NTRS2016

Evolution of the JPSS Ground Project Calibration and Validation System

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administration's (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAA's mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation's economy and protection of lives and property. The National Aeronautics and Space Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems, on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Next-Generation↗

NASA NTRS1992

Development of a hydrogen external burning flight test experiment on the NASA Dryden SR-71A aircraft

A captive-carry flight test experiment of the transonic external burning concept using gaseous hydrogen fuel has ben proposed for the SR-71A flight research test bed aircraft at the NASA Dryden Flight Research Facility, Edwards, California. This program will be the first large-scale, near-field flight test investigation of this base drag reduction technique at Mach numbers up to 3. Low-speed base drag reduction for supersonic and hypersonic flight vehicles is important in reducing vehicle drag and improving nozzle efficiency. Flight data will be correlated with a concurrent wind tunnel ground test of a similar test apparatus to confirm geometry and component performance scalability predictions and to investigate design parametrics under actual flight conditions. This paper describes the problem of transonic base drag for supersonic and hypersonic aircraft, a planned flight research program to address this problem, the test bed aircraft, and the flight experiment apparatus.

Hicks, John W.↗

NASA NTRS2015

Adaptive Stress Testing of Airborne Collision Avoidance Systems

This paper presents a scalable method to efficiently search for the most likely state trajectory leading to an event given only a simulator of a system. Our approach uses a reinforcement learning formulation and solves it using Monte Carlo Tree Search (MCTS). The approach places very few requirements on the underlying system, requiring only that the simulator provide some basic controls, the ability to evaluate certain conditions, and a mechanism to control the stochasticity in the system. Access to the system state is not required, allowing the method to support systems with hidden state. The method is applied to stress test a prototype aircraft collision avoidance system to identify trajectories that are likely to lead to near mid-air collisions. We present results for both single and multi-threat encounters and discuss their relevance. Compared with direct Monte Carlo search, this MCTS method performs significantly better both in finding events and in maximizing their likelihood.

Verification and Validation↗

NASA NTRS2020

Detector Channel Combining Results from a High Photon Efficiency Optical Communications Link Test Bed

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is developing a low cost, scalable, photon counting receiver prototype for space-to-ground optical communications links. The receiver is being tested in a test bed that emulates photon-starved space-to-ground optical communication links. The receiver uses an array of single-pixel fiber-coupled superconducting nanowire single-photon detectors. The receiver is designed to receive the high photon efficiency serially concatenated pulse position modulation (SCPPM) waveform specified in the Consultative Committee for Space Data Systems (CCSDS) Optical Communications Coding and Synchronization Blue Book Standard. The optical receiver consists of an array of single-pixel superconducting nanowire detectors, analog phase shifters for channel alignment, digitizers for each detector channel, and digital processing of the received signal. An overview of the test bed and arrayed receiver system is given. Simulation and system characterization results are presented. The data rate increase of using a four-channel arrayed detector system over using one single pixel nanowire detector is characterized. Results indicate that a single-pixel detector is capable of receiving data at a rate of 40 Mbps and a four-channel arrayed detector system is capable of receiving data at a rate of 130 Mbps.

Downey, Jennifer N.↗

NASA NTRS2000

An Architecture for Real-Time Interpretation and Visualization of Structural Sensor Data in a Laboratory Environment

A visualization system is being developed out of the need to monitor, interpret, and make decisions based on the information from several thousand sensors during experimental testing to facilitate development and validation of structural health monitoring algorithms. As an added benefit the system will enable complete real-time sensor assessment of complex test specimens. Complex structural specimens are routinely tested that have hundreds or thousands of sensors. During a test, it is impossible for a single researcher to effectively monitor all the sensors and subsequently interesting phenomena occur that are not recognized until post-test analysis. The ability to detect and alert the researcher to these unexpected phenomena as the test progresses will significantly enhance the understanding and utilization of complex test articles. Utilization is increased by the ability to halt a test when the health monitoring algorithm response is not satisfactory or when an unexpected phenomenon occurs, enabling focused investigation potentially through the installation of additional sensors. Often if the test continues, structural changes make it impossible to reproduce the conditions that exhibited the phenomena. The prohibitive time and costs associated with fabrication, sensoring, and subsequent testing of additional test articles generally makes it impossible to further investigate the phenomena. A scalable architecture is described to address the complex computational demands of structural health monitoring algorithm development and laboratory experimental test monitoring. The researcher monitors the test using a photographic quality 3D graphical model with actual sensor locations identified. In addition, researchers can quickly activate plots displaying time or load versus selected sensor response along with the expected values and predefined limits. The architecture has several key features. First, distributed dissimilar computers may be seamlessly integrated into the information flow. Second, virtual sensors may be defined that are complex functions of existing sensors or other virtual sensors. Virtual sensors represent a calculated value not directly measured by particular physical instrument. They can be used, for example, to represent the maximum difference in a range of sensors or the calculated buckling load based on the current strains. Third, the architecture enables autonomous response to preconceived events, where by the system can be configured to suspend or abort a test if a failure is detected in the load introduction system. Fourth, the architecture is designed to allow cooperative monitoring and control of the test progression from multiple stations both remote and local to the test system. To illustrate the architecture, a preliminary implementation is described monitoring the Stitched Composite Wing recently tested at LaRC.

Doggett, William↗

NASA NTRS2020

Detector Channel Combining Results from a High Photon Efficiency Optical Communications Link Test Bed

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is developing a low cost, scalable, photon-counting receiver prototype for space-to-ground optical communications links. The receiver is being tested in a test bed that emulates photon-starved space-to-ground optical communication links. The receiver uses an array of single-pixel fiber-coupled superconducting nanowire single-photon detectors. The receiver is designed to receive the high photon efficiency serially concatenated pulse position modulation (SCPPM) waveform specified in the Consultative Committee for Space Data Systems (CCSDS) Optical Communications Coding and Synchronization Blue Book Standard. The optical receiver consists of an array of single-pixel superconducting nanowire detectors, analog phase shifters for channel alignment, digitizers for each detector channel, and digital processing of the received signal. An overview of the test bed and arrayed receiver system is given. Simulation and system characterization results are presented. The data rate increase of using a four-channel arrayed detector system over using one single pixel nanowire detector is characterized. Results indicate that a single-pixel detector is capable of receiving data at a rate of 40 Mbps and a four-channel arrayed detector system is capable of receiving data at a rate of 130 Mbps.

Downey, Jennifer N.↗

NASA NTRS2018

Assessing C2 Communications for UAS Traffic Management

The National Aeronautics and Space Administration's (NASA) Unmanned Aircraft Systems (UAS) Traffic Management (UTM) project works to develop tools and technologies essential for safely enabling civilian low-altitude UAS operations. Currently there is no established infrastructure to enable and safely manage the widespread use of low-altitude airspace and UAS operations, regardless of the type of UAS. The UTM technical challenge will develop comprehensive and validated airspace operations and integration requirements to safely enable large-scale persistent access to visual line of sight and autonomous beyond visual line of sight small UAS in low-altitude airspace. Within the UTM project, a number of communications technologies to support UTM command and control (C2) are under investigation. In particular, commercial networked cellular systems are being tested and assessed for their ability to meet the reliability, scalability, cybersecurity and redundancy required. NASA Glenn Research Center is studying some of the aspects of employing such networks for UTM C2 communications. This includes the development of a test platform for sensing and characterizing the airborne C2 communications environment at various altitudes and in various terrains and topologies, measuring such aspects as received signal strength and interference. System performance aspects such as latency in the link, handover performance, packet error loss rate, drop outs, coverage gaps and other aspects impacting UTM operation will also be assessed. In this paper we explore some of the C2 approaches being proposed and demonstrated in the UTM project, the reliability, availability and other general C2 performance requirements, and approaches to evaluating and analyzing UTM C2 links based on commercial cellular networks.

air traffic control↗

NASA NTRS2018

Assessing C2 Communications

aircraft communications↗

NASA NTRS2013

Scale Model Thruster Acoustic Measurement Results

Subscale rocket acoustic data is used to predict acoustic environments for full scale rockets. Over the last several years acoustic data has been collected during horizontal tests of solid rocket motors. Space Launch System (SLS) Scale Model Acoustic Test (SMAT) was designed to evaluate the acoustics of the SLS vehicle including the liquid engines and solid rocket boosters. SMAT is comprised of liquid thrusters scalable to the Space Shuttle Main engines (SSME) and Rocket Assisted Take Off (RATO) motors scalable to the 5-segment Reusable Solid Rocket Motor (RSTMV). Horizontal testing of the liquid thrusters provided an opportunity to collect acoustic data from liquid thrusters to characterize the acoustic environments. Acoustic data was collected during the horizontal firings of a single thruster and a 4-thruster (Quad) configuration. Presentation scope. Discuss the results of the single and 4-thruster acoustic measurements. Compare the measured acoustic levels of the liquid thrusters to the Solid Rocket Test Motor V - Nozzle 2 (SRTMV-N2).

Kenny, R. Jeremy↗

NASA NTRS2016

UTM Safely Enabling UAS Operations in Low-Altitude Airspace

Conduct research, development and testing to identify airspace operations requirements to enable large-scale visual and beyond visual line of sight UAS operations in the low-altitude airspace. Use build-a-little-test-a-little strategy remote areas to urban areas Low density: No traffic management required but understanding of airspace constraints. Cooperative traffic management: Understanding of airspace constraints and other operations. Manned and unmanned traffic management: Scalable and heterogeneous operations. UTM construct consistent with FAAs risk-based strategy. UTM research platform is used for simulations and tests. UTM offers path towards scalability.

UTM low-altitude↗

NASA NTRS2017

Unmanned Aircraft Systems Traffic Management (UTM) Safely Enabling UAS Operations in Low-Altitude Airspace

Low-altitude UTM↗

NASA NTRS1995

Parallel volume ray-casting for unstructured-grid data on distributed-memory architectures

As computing technology continues to advance, computational modeling of scientific and engineering problems produces data of increasing complexity: large in size and unstructured in shape. Volume visualization of such data is a challenging problem. This paper proposes a distributed parallel solution that makes ray-casting volume rendering of unstructured-grid data practical. Both the data and the rendering process are distributed among processors. At each processor, ray-casting of local data is performed independent of the other processors. The global image composing processes, which require inter-processor communication, are overlapped with the local ray-casting processes to achieve maximum parallel efficiency. This algorithm differs from previous ones in four ways: it is completely distributed, less view-dependent, reasonably scalable, and flexible. Without using dynamic load balancing, test results on the Intel Paragon using from two to 128 processors show, on average, about 60% parallel efficiency.

Ma, Kwan-Liu↗