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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1974

Identification of phenological stages and vegetative types for land use classification

The author has identified the following significant results. Recent signature identification and refinement techniques indicate that with automated classification of MSS CCT data commercial stands of cottonwood and white spruce can be identified with 80% accuracy in the Bonanza Creek experimental forest. Since that forest is representative of the vast interior Alaska forests, this finding has substantial economic importance to public and private forestry interests in Alaska.

Mckendrick, J. D.↗
NASA NTRS1979

Microbial Load Monitor

The Microbial Load Monitor (MLM) is an automated and computerized system for detection and identification of microorganisms. Additionally, the system is designed to enumerate and provide antimicrobic susceptibility profiles for medically significant bacteria. The system is designed to accomplish these tasks in a time of 13 hours or less versus the traditional time of 24 hours for negatives and 72 hours or more for positives usually required for standard microbiological analysis. The MLM concept differs from other methods of microbial detection in that the system is designed to accept raw untreated clinical samples and to selectively identify each group or species that may be present in a polymicrobic sample.

Gibson, S. F.↗
NASA NTRS2004

Microbial Characterization During the Early Habitation of the International Space Station

An evaluation of the microbiota from air, water, and surface samples provided a baseline of microbial characterization onboard the International Space Station (ISS) to gain insight into bacterial and fungal contamination during the initial stages of construction and habitation. Using 16S genetic sequencing and rep-PCR, 63 bacterial strains were isolated for identification and fingerprinted for microbial tracking. Of the bacterial strains that were isolated and fingerprinted, 19 displayed similarity to each other. The use of these molecular tools allowed for the identification of bacteria not previously identified using automated biochemical analysis and provided a clear indication of the source of several ISS contaminants. Strains of Bradyrhizobium and Sphingomonas unable to be identified using sequencing were identified by comparison of rep-PCR DNA fingerprints. Distinct DNA fingerprints for several strains of Methylobacterium provided a clear indication of the source of an ISS water supply contaminant. Fungal and bacterial data acquired during monitoring do not suggest there is a current microbial hazard to the spacecraft, nor does any trend indicate a potential health risk. Previous spacecraft environmental analysis indicated that microbial contamination will increase with time and will require continued surveillance. Copyright 2004 Springer-Verlag.

Fungi/genetics↗
NASA NTRS2006

Rapid Identification of GRB Afterglows with Swift/UVOT

As part of the automated response to a new gamma-ray burst (GRB), the Ultraviolet and Optical Telescope (UVOT) instrument on Swift starts a 200-second exposure with the V filter within approximately 100 seconds of the BAT burst trigger. The instrument searches for sources in a 8' x 8' region, and sends the list of sources and a 160" x 160" sub-image centered on the burst position to the ground via Tracking and Data Relay Satellite System (TDRSS). These raw products and additional products calculated on the ground are then distributed through the GCN within a few minutes of the trigger. We describe the sensitivity of these data for detecting afterglows, summarize current results, and outline plans for rapidly distributing future detections.

Marshall, F. E.↗
NASA NTRS2003

Autonomous landmark tracking orbit determination strategy

In this paper, an orbit determination strategy is described that is fully autonomous and relies on a computer-based crater detection and identification algorithm that is suitable for both automation of the ground based navigation system and autonomous spacecraft based navigation.

landmark tracking orbit determination↗
NASA NTRS2003

Microbial Diversity Aboard Spacecraft: Evaluation of the International Space Station

An evaluation of the microbial flora from air, water, and surface samples provided a baseline of microbial diversity onboard the International Space Station (ISS) to gain insight into bacterial and fungal contamination during the initial stages of construction and habitation. Using 16S genetic sequencing and rep-PeR, 63 bacterial strains were isolated for identification and fingerprinted for microbial tracking. The use of these molecular tools allowed for the identification of bacteria not previously identified using automated biochemical analysis and provided a clear indication of the source of several ISS contaminants. Fungal and bacterial data acquired during monitoring do not suggest there is a current microbial hazard to the spacecraft, nor does any trend indicate a potential health risk. Previous spacecraft environmental analysis indicated that microbial contamination will increase with time and require continued surveillance.

Castro, Victoria A.↗
NASA NTRS2009

Neural Network Target Identification System for False Alarm Reduction

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

ATR↗
NASA NTRS2016

The Caltech-NRAO Stripe 82 Survey (CNSS) Paper. I. The Pilot Radio Transient Survey in 50 Deg.(exp. 2)

We have commenced a multiyear program, the Caltech-NRAO Stripe 82 Survey (CNSS), to search for radio transients with the Jansky VLA in the Sloan Digital Sky Survey Stripe 82 region. The CNSS will deliver five epochs over the entire approx. 270 deg.(exp. 2) of Stripe 82, an eventual deep combined map with an rms noise of approx. 40 proper motion epoch y and catalogs at a frequency of 3 GHz, and having a spatial resolution of 3 inches. This first paper presents the results from an initial pilot survey of a 50 deg.(exp. 2) region of Stripe 82, involving four epochs spanning logarithmic timescales between 1 week and 1.5 yr, with the combined map having a median rms noise of 35 proper motion epoch y. This pilot survey enabled the development of the hardware and software for rapid data processing, as well as transient detection and follow-up, necessary for the full 270 deg.(exp. 2) survey. Data editing, calibration, imaging, source extraction, cataloging, and transient identification were completed in a semi-automated fashion within 6 hr of completion of each epoch of observations, using dedicated computational hardware at the NRAO in Socorro and custom-developed data reduction and transient detection pipelines. Classification of variable and transient sources relied heavily on the wealth of multiwavelength legacy survey data in the Stripe 82 region, supplemented by repeated mapping of the region by the Palomar Transient Factory. A total of 3.9(+0.5%/-0.9%) of the few thousand detected point sources werefound to vary by greater than 30%, consistent with similar studies at 1.4 and 5 GHz. Multiwavelength photometric data and light curves suggest that the variability is mostly due to shock-induced flaring in the jets of active galactic nuclei (AGNs). Although this was only a pilot survey, we detected two bona fide transients, associated with an RS CVn binary and a dKe star. Comparison with existing legacy survey data (FIRST, VLA-Stripe 82) revealed additional highly variable and transient sources on timescales between 5 and 20 yr, largely associated with renewed AGN activity. The rates of such AGNs possibly imply episodes of enhanced accretion and jet activity occurring once every approx. 40,000 yr in these galaxies. We compile the revised radio transient rates and make recommendations for future transient surveys and joint radio-optical experiments.

galaxies: active – radio continuum: galaxies –↗
NASA NTRS2009

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Terrile, Richard J.↗
NASA NTRS1983

Automation concepts for large space power systems

A study was undertaken to develop a methodology for analyzing, selecting, and implementing automation functions for multi-hundred-kW photovoltaic power systems intended for manned space station. The study involved identification of generic power system elements and their potential faults, definition of automation functions and their resulting benefits, and partitioning of automation functions between power subsystem, central spacecraft computer, and ground. Automation to a varying degree was concluded to be mandatory to meet the design and operational requirements of the space station. The key drivers are indefinite lifetime, modular growth, high performance flexibility, a need to accommodate different electrical user load equipment, on-orbit assembly/maintenance/servicing, and potentially large number of power subsystem components. Functions that are good candidates for automation via expert system approach includes battery management and electrical consumables management.

Imamura, M. S.↗
NASA NTRS1978

Recent advances in thermal-structural analysis and design

A continuing effort to develop a comprehensive capability for thermal-structural analysis and automated design (sizing) is reviewed. A principal role in the activity is played by the finite element program SPAR which contains both an efficient structural and thermal analysis capability. The benefit of having thermal and structural analyses in the same finite element program is illustrated by the application of SPAR to design calculations for the National Transonic Facility - a cryogenic wind tunnel under construction at Langley. Some experience with large-scale thermal structural analysis problems, particularly the space shuttle orbiter, has led to the identification of some analysis needs. Those needs include automated model generation and data output for lumped parameter thermal analysis, faster solution methods for nonlinear transient heat transfer, automated interpolation of temperature data from a thermal finite element model to a dissimilar structural finite model, and automated techniques to identify the times at which the critical combinations of transient heating and loads occur on a structure.

Adelman, H. M.↗
NASA NTRS2005

Advanced Method to Estimate Fuel Slosh Simulation Parameters

The nutation (wobble) of a spinning spacecraft in the presence of energy dissipation is a well-known problem in dynamics and is of particular concern for space missions. The nutation of a spacecraft spinning about its minor axis typically grows exponentially and the rate of growth is characterized by the Nutation Time Constant (NTC). For launch vehicles using spin-stabilized upper stages, fuel slosh in the spacecraft propellant tanks is usually the primary source of energy dissipation. For analytical prediction of the NTC this fuel slosh is commonly modeled using simple mechanical analogies such as pendulums or rigid rotors coupled to the spacecraft. Identifying model parameter values which adequately represent the sloshing dynamics is the most important step in obtaining an accurate NTC estimate. Analytic determination of the slosh model parameters has met with mixed success and is made even more difficult by the introduction of propellant management devices and elastomeric diaphragms. By subjecting full-sized fuel tanks with actual flight fuel loads to motion similar to that experienced in flight and measuring the forces experienced by the tanks these parameters can be determined experimentally. Currently, the identification of the model parameters is a laborious trial-and-error process in which the equations of motion for the mechanical analog are hand-derived, evaluated, and their results are compared with the experimental results. The proposed research is an effort to automate the process of identifying the parameters of the slosh model using a MATLAB/SimMechanics-based computer simulation of the experimental setup. Different parameter estimation and optimization approaches are evaluated and compared in order to arrive at a reliable and effective parameter identification process. To evaluate each parameter identification approach, a simple one-degree-of-freedom pendulum experiment is constructed and motion is induced using an electric motor. By applying the estimation approach to a simple, accurately modeled system, its effectiveness and accuracy can be evaluated. The same experimental setup can then be used with fluid-filled tanks to further evaluate the effectiveness of the process. Ultimately, the proven process can be applied to the full-sized spinning experimental setup to quickly and accurately determine the slosh model parameters for a particular spacecraft mission. Automating the parameter identification process will save time, allow more changes to be made to proposed designs, and lower the cost in the initial design stages.

Schlee, Keith↗
NASA NTRS2004

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Williams-Hayes, Peggy S.↗
NASA NTRS1973

On particle track detectors

Aqueous sodium hydroxide is widely used to develop charged particle tracks in polycarbonate film, particularly Lexan. The chemical nature of the etching process for this system has been determined. A method employing ultra-violet absorbance was developed for monitoring the concentration of the etch products in solution. Using this method it was possible to study the formation of the etching solution saturated in etch products. It was found that the system super-saturates to a significant extent before precipitation occurs. It was also learned that the system approaches its equilibrium state rather slowly. It is felt that both these phenomena may be due to the presence of surfactant in the solution. In light of these findings, suggestions are given regarding the preparation and maintenance of the saturated etch solution. Two additional research projects, involving automated techniques for particle track analysis and particle identification using AgCl crystals, are briefly summarized.

Benton, E. V.↗
NASA NTRS1992

Standards for space automation and robotics

The AIAA's Committee on Standards for Space Automation and Robotics (COS/SAR) is charged with the identification of key functions and critical technologies applicable to multiple missions that reflect fundamental consideration of environmental factors. COS/SAR's standards/practices/guidelines implementation methods will be based on reliability, performance, and operations, as well as economic viability and life-cycle costs, simplicity, and modularity.

Kader, Jac B.↗
NASA NTRS1994

Software For Computer-Security Audits

Information relevant to potential breaches of security gathered efficiently. Automated Auditing Tools for VAX/VMS program includes following automated software tools performing noted tasks: Privileged ID Identification, program identifies users and their privileges to circumvent existing computer security measures; Critical File Protection, critical files not properly protected identified; Inactive ID Identification, identifications of users no longer in use found; Password Lifetime Review, maximum lifetimes of passwords of all identifications determined; and Password Length Review, minimum allowed length of passwords of all identifications determined. Written in DEC VAX DCL language.

Arndt, Kate↗
NASA NTRS1994

Risk reduction methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC)

This paper will discuss proposed Flight Operations methodologies and technologies for the Earth Observing System (EOS) Operations Center (EOC), to reduce risks associated with the operation of complex multi-instrument spacecraft in a multi-spacecraft environment. The EOC goals are to obtain 100 percent science data capture and maintain 100 percent spacecraft health, for each EOS spacecraft. Operations risks to the spacecraft and data loss due to operator command error, mission degradation due to mis-identification of an anomalous trend in component performance or mis-management of resources, and total mission loss due to improper subsystem configuration or mis-identification of an anomalous condition. This paper discusses automation of routine Flight Operations Team (FOT) responsibilities, Expert systems for real-time non-nominal condition decision support, and Telemetry analysis systems for in-depth playback data analysis and trending.

Hudson, Richard K.↗
NASA NTRS1997

Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

Jong, Jen-Yi↗