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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1983

Performance evaluation of the JPL interim digital SAR processor

The performance of the Interim Digital SAR Processor (IDP) was evaluated. The IDP processor was originally developed for experimental processing of digital SEASAT SAR data. One phase of the system upgrade which features parallel processing in three peripheral array processors, automated estimation for Doppler parameters, and unsupervised image pixel location determination and registration was executed. The method to compensate for the target range curvature effect was improved. A four point interpolation scheme is implemented to replace the nearest neighbor scheme used in the original IDP. The processor still maintains its fast throughput speed. The current performance and capability of the processing modes now available on the IDP system are updated.

Wu, C.↗
NASA NTRS1990

Status report on a real time Engine Diagnostics Console for rocket engine exhaust plume monitoring

This paper describes the work done on the Engine Diagnostics Console during the past year of development at Stennis Space Center. The Engine Diagnostics Console (EDC) is a hardware and software package which provides near real time monitoring of rocket engine exhaust plume emissions during ground testing. The long range goal of the EDC development program is to develop an instrument that can detect engine degradation leading to catastrophic failure, and respond by taking preventative measures. The immediate goal for the past year's effort is the ability to process spectral data, taken from a rocket engine's exhaust plume, and to identify in an automated and high speed manner, the elemental species and multielemental materials that are present in the exhaust plume.

Bircher, F. E.↗
NASA NTRS1992

Learning class descriptions from a data base of spectral reflectance with multiple view angles

A learning program has been developed which combines 'learning by example' with the generate-and-test paradigm to furnish a robust learning environment capable of handling error-prone data. The problem is shown to be capable of learning class descriptions from positive and negative training examples of spectral and directional reflectance data taken from soil and vegetation. The program, which used AI techniques to automate very tedious processes, found the sequence of relationships that contained the most important information which could distinguish the classes.

Kimes, Daniel S.↗
NASA NTRS1993

Operation of the helicopter antenna radiation prediction code

HARP is a front end as well as a back end for the AMC and NEWAIR computer codes. These codes use the Method of Moments (MM) and the Uniform Geometrical Theory of Diffraction (UTD), respectively, to calculate the electromagnetic radiation patterns for antennas on aircraft. The major difficulty in using these codes is in the creation of proper input files for particular aircraft and in verifying that these files are, in fact, what is intended. HARP creates these input files in a consistent manner and allows the user to verify them for correctness using sophisticated 2 and 3D graphics. After antenna field patterns are calculated using either MM or UTD, HARP can display the results on the user's screen or provide hardcopy output. Because the process of collecting data, building the 3D models, and obtaining the calculated field patterns was completely automated by HARP, the researcher's productivity can be many times what it could be if these operations had to be done by hand. A complete, step by step, guide is provided so that the researcher can quickly learn to make use of all the capabilities of HARP.

Braeden, E. W.↗
NASA NTRS1994

Development and application of structural dynamics analysis capabilities

Extensive research activities were performed in the area of multidisciplinary modeling and simulation of aerospace vehicles that are relevant to NASA Dryden Flight Research Facility. The efforts involved theoretical development, computer coding, and debugging of the STARS code. New solution procedures were developed in such areas as structures, CFD, and graphics, among others. Furthermore, systems-oriented codes were developed for rendering the code truly multidisciplinary and rather automated in nature. Also, work was performed in pre- and post-processing of engineering analysis data.

Heinemann, Klaus W.↗
NASA NTRS1996

CROSS: A GDSS for the Evaluation and Prioritization of Engineering Support Requests and Advanced Technology Projects at NASA

Objective evaluation and prioritization of engineering support requests (ESRs) is a difficult task at the Kennedy Space Center (KSC) Shuttle Project Engineering Office. The difficulty arises from the complexities inherent in the evaluation process and the lack of structured information. The purpose of this project is to implement the consensus ranking organizational support system (CROSS), a multiple criteria decision support system (DSS) developed at KSC that captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. CROSS utilizes the analytic hierarchy process (AHP), subjective probabilities, entropy concept, and maximize agreement heuristic (MAH) to enhance the decision maker's intuition in evaluation ESRs. Some of the preliminary goals of the project are to: (1) revisit the structure of the ground systems working team (GWST) steering committee, (2) develop a template for ESR originators to provide more comple and consistent information to the GSWT steering committee members to eliminate the need for a facilitator, (3) develop an objective and structured process for the initial screening of ESRs, (4) extensive training of the stakeholders and the GWST steering committee to eliminate the need for a facilitator, (5) automate the process as much as possible, (6) create an environment to compile project success factor data on ESRs and move towards a disciplined system that could be used to address supportability threshold issues at the KSC, and (7) investigate the possibility of an organization-wide implementation of CROSS.

Tavana, Madjid↗
NASA NTRS2000

Design of a K-Band Transmit Phased Array For Low Earth Orbit Satellite Communications

The design of a light weight, low cost phased array antenna is presented. Multilayer printed wiring board (PWB) technology is utilized for Radio Frequencies (RF) and DC/Logic manifold distribution. Transmit modules are soldered on one side and patch antenna elements are on the other, allowing the use of automated assembly processes. The 19 GHz antenna has two independently steerable beams, each capable of transferring data at 622 Mbps. A passive, self-contained phase change thermal management system is also presented.

Watson, Thomas↗
NASA NTRS2005

Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms

To take advantage of the vast amount of GPS data, researchers use a number of techniques to estimate satellite and receiver interfrequency biases and the total electron content (TEC) of the ionosphere. Most techniques estimate vertical ionospheric structure and, simultaneously, hardware-related biases treated as nuisance parameters. These methods often are limited to 200 GPS receivers and use a sequential least squares or Kalman filter approach. The biases are later removed from the measurements to obtain unbiased TEC. In our approach to calibrating GPS receiver and transmitter interfrequency biases we take advantage of all available GPS receivers using a new processing algorithm based on the Global Ionospheric Mapping (GIM) software developed at the Jet Propulsion Laboratory. This new capability is designed to estimate receiver biases for all stations. We solve for the instrumental biases by modeling the ionospheric delay and removing it from the observation equation using precomputed GIM maps. The precomputed GIM maps rely on 200 globally distributed GPS receivers to establish the ''background'' used to model the ionosphere at the remaining 800 GPS sites.

total electron content (TEC)↗
NASA NTRS2009

Detecting Phase Boundaries in Hard-Sphere Suspensions

A special image-data-processing technique has been developed for use in experiments that involve observation, via optical microscopes equipped with electronic cameras, of moving boundaries between the colloidal-solid and colloidal-liquid phases of colloidal suspensions of monodisperse hard spheres. During an experiment, it is necessary to adjust the position of a microscope to keep the phase boundary within view. A boundary typically moves at a speed of the order of microns per hour. Because an experiment can last days or even weeks, it is impractical to require human intervention to keep the phase boundary in view. The present image-data-processing technique yields results within a computation time short enough to enable generation of automated-microscope-positioning commands to track the moving phase boundary

McDowell, Mark↗
NASA NTRS2010

Human Spaceflight Recent Conjunctions of Interest

I. During each nine-hour shift (or upon request), the Orbital Safety Analyst (OSA) at JSpOC updates the entire tracked catalog with the latest tracking data from the SSN and screens this catalog against NASA s assets. a) For ISS operations, a 72-hour advance screening is performed. b) For Shuttle orbit operations, a 36-hour advance screening is performed. c) If a vehicle is performing a maneuver during the screening period, OSA uses post-reboost-trajectory data supplied by Mission Control Center-Houston (MCC-H) for screening. II. An automated process is used to detect any conjunctions within 10 x 40 x 40 km box (centered on the vehicle) using Special Perturbation (SP) processing: a) Box dimensions are Radial x Downtrack x Crosstrack. b) Any object found within this box has the tracking tasking level increased to improve (hopefully) its uncertainty in its current and predicted orbital trajectory. c) OSA informs NASA if any object is found inside a 2 x 25 x 25 km box then creates and sends an Orbital Conjunction Message (OCM) to NASA which contains detailed information about the conjunction. d) For Shuttle, the box size used for screening and reporting is altered for special operations (day of rendezvous, launch screening, etc.).

Browns, Ansley C.↗
NASA NTRS2011

Multidisciplinary Tool for Systems Analysis of Planetary Entry, Descent, and Landing

Systems analysis of a planetary entry (SAPE), descent, and landing (EDL) is a multidisciplinary activity in nature. SAPE improves the performance of the systems analysis team by automating and streamlining the process, and this improvement can reduce the errors that stem from manual data transfer among discipline experts. SAPE is a multidisciplinary tool for systems analysis of planetary EDL for Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Titan. It performs EDL systems analysis for any planet, operates cross-platform (i.e., Windows, Mac, and Linux operating systems), uses existing software components and open-source software to avoid software licensing issues, performs low-fidelity systems analysis in one hour on a computer that is comparable to an average laptop, and keeps discipline experts in the analysis loop. SAPE uses Python, a platform-independent, open-source language, for integration and for the user interface. Development has relied heavily on the object-oriented programming capabilities that are available in Python. Modules are provided to interface with commercial and government off-the-shelf software components (e.g., thermal protection systems and finite-element analysis). SAPE currently includes the following analysis modules: geometry, trajectory, aerodynamics, aerothermal, thermal protection system, and interface for structural sizing.

Samareh, Jamshid A.↗
NASA NTRS2013

NASA Tech Briefs, July 2013

Dielectrophoresis-Based Particle Sensor Using Nanoelectrode Arrays; Multi-Dimensional Damage Detection for Surfaces and Structures; ULTRA: Underwater Localization for Transit and Reconnaissance Autonomy; Autonomous Cryogenic Leak Detector for Improving Launch Site Operations; Submillimeter Planetary Atmospheric Chemistry Exploration Sounder; Method for Reduction of Silver Biocide Plating on Metal Surfaces; Silicon Micromachined Microlens Array for THz Antennas; Forward-Looking IED Detector Ground Penetrating Radar; Fully Printed, Flexible, Phased Array Antenna for Lunar Surface Communication, Battery Charge Equalizer with Transformer Array; An Efficient, Highly Flexible Multi-Channel Digital Downconverter Architecture; Dimmable Electronic Ballast for a Gas Discharge Lamp; Conductive Carbon Nanotube Inks for Use with Desktop Inkjet Printing Technology; Enhanced Schapery Theory Software Development for Modeling Failure of Fiber-Reinforced Laminates; High-Performance, Low-Temperature-Operating, Long-Lifetime Aerospace Lubricants; Carbon Nanotube Microarrays Grown on Nanoflake Substrates; Differential Muon Tomography to Continuously Monitor Changes in the Composition of Subsurface Fluids; Microgravity Drill and Anchor System; 20 Granular Media-Based Tunable Passive Vibration Suppressor; 21 Miga Aero Actuator and 2D Machined Mechanical Binary Latch; Micro-XRF for In Situ Geological Exploration of Other Planets; Hydrogen-Enhanced Lunar Oxygen Extraction and Storage Using Only Solar Power; Uplift of Ionospheric Oxygen Ions During Extreme Magnetic Storms; Miniaturized, High-Speed, Modulated X-Ray Source; Hollow-Fiber Spacesuit Water Membrane Evaporator 25 High-Power Single-Mode 2.65-micrometers InGaAsSb/AlInGaAsSb Diode Lasers; Optical Device for Converting a Laser Beam Into Two Co-aligned but Oppositely Directed Beams; A Hybrid Fiber/Solid-State Regenerative Amplifier with Tunable Pulse Widths for Satellite Laser Ranging; X-Ray Diffractive Optics; SynGenics Optimization System (SynOptSys); 29 CFD Script for Rapid TPS Damage Assessment; radEq Add-On Module for CFD Solver Loci-CHEM; Science Opportunity Analyzer (SOA) Version 8; 30 Autonomous Byte Stream Randomizer; Distributed Engine Control Empirical/Analytical Verification Tools; Dynamic Server-Based KML Code Generator Method for Level-of-Detail Traversal of Geospatial Data; Automated Planning of Science Products Based on Nadir Overflights and Alerts for Onboard and Ground Processing; Linked Autonomous Interplanetary Satellite Orbit Navigation; Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing; Scheduling Operations for Massive Heterogeneous Clusters; Deepak Condenser Model (DeCoM); Flight Software Math Library; Recirculating 1-K-Pot for Pulse-Tube Cryostats; 35 Method for Processing Lunar Regolith Using Microwaves; Wells for In Situ Extraction of Volatiles from Regolith (WIEVR); and Estimating the Backup Reaction Wheel Orientation Using Reaction Wheel Spin Rates Flight Telemetry from a Spacecraft.

Source record↗
NASA NTRS2017

Fireballs in the Sky: An Augmented Reality Citizen Science Program

Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000 by 36 megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million square kilometers. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.

Day, Brian↗
NASA NTRS2018

Systems and Methods for Advanced Rapid Imaging and Analysis for Earthquakes

Many embodiments provide a hybrid data processing system (HySDS) of an end-to-end geodetic imaging data system enabling near-real-time science, assessment, response, and rapid recovery. The HySDS may be an operation data processing system that integrates data from many different geodetic data sources and/or sensors, including interferometric synthetic aperture radar (InSAR), GPS, pixel tracking, seismology, and/or modeling, and processes the data to generate actionable high quality science data products. The HySDS may provide for an automated imaging and analysis capabilities that is able to handle the imminent increases in raw data from new and existing geodetic monitoring sensor systems.

Owen, Susan Ethel↗
NASA NTRS1993

Tensoral: A system for post-processing turbulence simulation data

Many computer simulations in engineering and science -- and especially in computational fluid dynamics (CFD) -- produce huge quantities of numerical data. These data are often so large as to make even relatively simple post-processing of this data unwieldy. The data, once computed and quality-assured, is most likely analyzed by only a few people. As a result, much useful numerical data is under-utilized. Since future state-of-the-art simulations will produce even larger datasets, will use more complex flow geometries, and will be performed on more complex supercomputers, data management issues will become increasingly cumbersome. My goal is to provide software which will automate the present and future task of managing and post-processing large turbulence datasets. My research has focused on the development of these software tools -- specifically, through the development of a very high-level language called 'Tensoral'. The ultimate goal of Tensoral is to convert high-level mathematical expressions (tensor algebra, calculus, and statistics) into efficient low-level programs which numerically calculate these expressions given simulation datasets. This approach to the database and post-processing problem has several advantages. Using Tensoral the numerical and data management details of a simulation are shielded from the concerns of the end user. This shielding is carried out without sacrificing post-processor efficiency and robustness. Another advantage of Tensoral is that its very high-level nature lends itself to portability across a wide variety of computing (and supercomputing) platforms. This is especially important considering the rapidity of changes in supercomputing hardware.

Dresselhaus, Eliot↗
NASA NTRSDate not supplied

Development of Computational Environmental Microbiome Workflows for the Laboratory and the International Space Station

Identification of microorganisms in the spaceflight environment is critical for crew health risk assessment on the International Space Station (ISS). Since 2017, nanopore sequencing technology has been used to support thein situ identification of microbial species during spaceflight. Beginning in 2018, a culture-independent, swab-to-sequencer method was implemented onboard the ISS to provide a more thorough insight of the ISS microbiome. Eliminating microbial culture enables identification of difficult-to-culture organisms, reduces risks associated with potentially pathogenic cultures, and could significantly reduce the time from sample-to-answer. However, this molecular-based approach generates large metagenomic datasets that require substantial computational resources for analysis. To process nanopore-generated sequencing data, the JSC Microbiology Laboratory established a bioinformatics workflow on Amazon EC2 under the security guidance of the NASA Science Managed Cloud Environment (SMCE).This resource allows for the development, testing, and accessing of computational tools for processing large and complex datasets. The work described here will address the downlinking of data from the ISS, the automated pipeline developed to identify targeted bacterial and fungal organisms, and the time from sampling onboard to microbial identification. The pipelines have been enhanced to address high and low biomass samples using optimization based on sample source (air, water, or surface) and type of collection (filter, colony, or swab).The resulting microbiome data can be assessed beyond microbial identifications to gain understanding toward population changes over time, potential selective environmental pressures, and evaluating correlations with a wide range of additional data sets. Metagenome analysis pipelines in development could allow for simultaneous identification of microbial species, gene function, and gene pathways present in the environment. Beyond the ground processing, the developed analysis pipeline is currently deployed onboard the ISS to allow for near real-time assessments of the ISS microbiome. This study serves as a critical foundation for exploration missions, where rapid microbiome analyses will be required.

G. Marie Sharp↗
NASA NTRS1975

Automated space processing payloads study. Volume 2, book 2: Technical report, appendices A through E

Experiment hardware and operational requirements for space shuttle experiments are discussed along with payload and system concepts. Appendixes are included in which experiment data sheets, chamber environmental control and monitoring, method for collection and storage of electrophoretically-separated samples, preliminary thermal evaluation of electromagnetic levitation facilities L1, L2, and L3, and applicable industrial automation equipment are discussed.

Source record↗
NASA NTRS2019

Frequency comparisons via GPS carrier-phase: jump processing, temperature compensation and zero/short-baseline noise-floors

GPS carrier-phase receivers have been used to produce high quality time/frequency comparisons between clocks and frequency standards. Current ways of processing the carrier-phase data, however, result in phase jumps and data gaps that make the data difficult to use effectively and repeatedly for long datasets. In addition, temperature fluctuations generally perturb receiver output detrimentally. We describe the steps of a simple but effective automated algorithm for comparing frequencies that can compensate for data gaps, day boundary jumps, and other phase jumps as well as for temperature disturbances. We describe process features and focus on zero-baseline noise-floors, measuring Allan deviations of the Deep Space Atomic Clock mission’s receiver down to 1x10-17 at 5x105 seconds, with an upper confidence level of 3x10-17. The zero-baseline noise floors we present give confidence in our algorithm and temperature compensation’s robustness.

Diener, William A.↗