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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 307 records · Page 17

Improved Spectrometer for Field Use

Proposed portable spectrometer for analyzing minerals in field generates spectral images like camera and process spectral data for real-time identification of materials. To identify unknown mineral, user locates significant peaks in displayed spectrum and matches them to spectrum in portfolio of reference spectra. Alternatively, user calls up display of prerecorded spectra in same wavelength region for comparison or allows spectrometer to determine best match automatically. New instrument makes it unnecessary to return data to laboratory or equipment trailer for processing.

Goetz, A. F. H.

Physics-Guided Machine Learning (PGML) for Improved Aerostructure Manufacturing

The Physics-Guided Machine Learning (PGML) for Improved Aerostructure Manufacturing project objective is to automatically tune machining parameter predictions from physics-based models using process data and Bayesian machine learning. The intent is to enable a step change in aerospace manufacturing by combining machine learning, physics-based process models, and sensors/data in a comprehensive digital environment that simultaneously considers the computer numerically controlled (CNC) machining center capabilities, the workpiece material and geometry, and the workpiece support (fixturing). The project hypothesis is that this combination will enable improved performance in machining operations.

42 ENGINEERING

The structure and microphysical properties of the clouds of Venus

Results are presented from the processing and interpretation of measurement data in the descent capsules of the automatic stations Venera-9 and Venera-10 for the characteristics of light scattering in the atmosphere of Venus by means of onboard nephelometers. A model for the aerosol component in the planet's atmosphere in the altitude range 62-14 km is proposed.

Marov, M. Y.

Forest fire advanced system technology (FFAST) conceptual design study

The National Aeronautics and Space Administration's Jet Propulsion Laboratory (JPL) and the U.S. Department of Agriculture (USDA) Forest Service completed a conceptual design study that defined an integrated forest fire detection and mapping system that will be based upon technology available in the 1990s. Potential system configuration options in emerging and advanced technologies related to the conceptual design were identified and recommended for inclusion as preferred system components. System component technologies identified for an end-to-end system include airborne mounted, thermal infrared (IR) linear array detectors, automatic onboard georeferencing and signal processing, geosynchronous satellite communications links, and advanced data integration and display. Potential system configuration options were developed and examined for possible inclusion in the preferred system configuration. The preferred system configuration will provide increased performance and be cost effective over the system currently in use. Forest fire management user requirements and the system component emerging technologies were the basis for the system configuration design. The conceptual design study defined the preferred system configuration that warrants continued refinement and development, examined economic aspects of the current and preferred system, and provided preliminary cost estimates for follow-on system prototype development.

Nichols, J. David

The two-way time synchronization system via a satellite voice channel

A newly developed two-way time synchronization system is described in this paper. The system uses one voice channel at a SCPC satellite digital communication earth station, whose bandwidth is only 45 kHz, thus saving satellite resources greatly. The system is composed of one master station and one or several, up to sixty-two, secondary stations. The master and secondary stations are equipped with the same equipment, including a set of timing equipment, a synthetic data terminal for time synchronizing, and a interface unit between the data terminal and the satellite earth station. The synthetic data terminal for time synchronization also has an IRIG-B code generator and a translator. The data terminal of master station is the key part of whole system. The system synchronization process is full automatic, which is controlled by the master station. Employing an autoscanning technique and conversational mode, the system accomplishes the following tasks: linking up liaison with each secondary station in turn, establishing a coarse time synchronization, calibrating date (years, months, days) and time of day (hours, minutes, seconds), precisely measuring the time difference between local station and the opposite station, exchanging measurement data, statistically processing the data, rejecting error terms, printing the data, calculating the clock difference and correcting the phase, thus realizing real-time synchronization from one point to multiple points. We also designed an adaptive phase circuit to eliminate the phase ambiguity of the PSK demodulator. The experiments have shown that the time synchronization accuracy is better than 2 mu S. The system has been put into regular operation.

Heng-Qiu, Zheng

Collection, processing and dissemination of data for the national solar demonstration program

A national solar data system developed for the DOE by IBM provides for automatic gathering, conversion, transfer, and analysis of demonstration site data. NASA requirements for this system include providing solar site hardware, engineering, data collection, and analysis. The specific tasks include: (1) solar energy system design/integration; (2) developing a site data acquisition subsystem; (3) developing a central data processing system; (4) operating the test facility at Marshall Space Flight Center; (5) collecting and analyzing data. The systematic analysis and evaluation of the data from the National Solar Data System is reflected in a monthly performance report and a solar energy system performance evaluation report.

Day, R. E.

Browser-Based Application for Telemetry Monitoring of Robotic Assets

AEGSE Virtuoso Charting is an application that enables animated, real-time charting of telemetry streams of data from a rover. These automatically scaled charts are completely interactive, and allow users to choose the variables that they want to monitor. The charts can process data from streams with many variables. This application allows for the simultaneous viewing of up to four individually configured charts on a small touch-screen laptop. The charting application has been tested and found to be extremely robust during long operations. It was left running overnight, with incoming telemetry at 100 Hz, and it did not experience any signs of lost functionality or memory leaks. This robustness is critical for an application that will be used to support vital tests for the Mars Science Laboratory rover. The charting component also provides an interactive interface that allows the engineers to decide how many charts they want on their screen, and which attributes should be plotted on each chart. The application is optimized to make the charts on display take up as much of the available space as possible to maximize the use of the screen real estate. Engineers are also able to plot multiple attributes on the same chart, which enables them to observe the correlation between various attributes.

Breed, Kelly S.

NASA Pilot-Engaged Expert Response Using IBM Watson Technology: Prototype Evaluation of Knowledge Retrieval System

NASA Langley Research Center and IBM have been investigating the use of IBM Watson technology in aerospace research and development. One application of Watson technology is the Pilot-Engaged Expert Response (PEER) use case. The PEER system is envisioned as an in-cockpit advisor that will act as a source of situationally-relevant information for pilots and other flight crew members to assist in decision making about real-time events and situations that arise in the course of aircraft operations. PEER will make available vast stores of knowledge and information quickly and directly, putting important informational resources where they are needed most. IBM has worked with NASA to develop an architecture and articulate a roadmap for the development of the PEER system. That vision is built around Watson Discovery Advisor (WDA) software solution, derived from IBM's Jeopardy!-winning automatic question answering system. PEER makes use of WDA's sophisticated question-answering capabilities as its core, adding important User Interface components and other customizations for the cockpit environment, including communication with flight systems and other external data sources. The development plan for PEER includes four development stages, with the current project constituting the first phase. In this project, a prototype instance of PEER was successfully adapted to the aviation domain, enabling users to ask questions about aviation topics and receive useful and accurate answers to these questions. Major tasks accomplished include the development of procedures for domain adaptation through automatic lexicon extraction from domain glossaries; generation of question-answer training data which was used to train the system; and assessment of the effectiveness of domain adaptation, which showed a dramatic improvement in the ability of the PEER system to answer domain-relevant questions. In addition, the vision for the PEER system was pushed forward by the articulation of a plan for the automatic enhancement of question-answering with contextual information. This initial phase focused on two main goals: 1) the targeted domain adaptation of the underlying WDA system to the aviation domain; and, 2) the design of the software systems needed to leverage flight-contextual data. Domain adaptation of the WDA system proceeds via three main activities: Domain data ingestion, lexical customization and model training. A textual corpus consisting of 1,147 individual documents with more than 7.5 million words of text was ingested into the system and this served as the basis of all further development. A domain lexicon of over 3,500 aviation-domain terms was semi-automatically generated from domain documents and used to train the system. In addition, a set of over 500 question-answer (QA) pairs relevant to the PEER use case was developed; these were used to train and assess the system. These important first steps established the basis for the PEER system. In addition, steps were taken towards the integration of the PEER system into the cockpit environment with the development of a functional design for the Contextual Data Augmentation (CDA) subsystem. This subsystem brings to bear contextual data to improve system responses. It has three main submodules: the Contextual Data Collection module, the Contextual Data Selection module, and the Contextual QA Augmentation module. These modules form a processing pipeline that addresses the problems associated with automatically integrating information from external resources into the knowledge-retrieval mechanism.

Machine learning

Automated Registration of Multi-Mode Nondestructive Evaluation Data

Registration techniques play a central role in applications of image processing to computer vision, medical imaging, and automatic target tracking. Feature-based techniques such as scale-invariant feature transform (SIFT) and speeded up robust features (SURF) are commonly used to register images derived from a single modality. However, SIFT and SURF struggle to register images from different modalities because the features tend to manifest rather differently and at sometimes very different length-scales. The most successful methods that have been developed to register multi-modal data use information-theoretic approaches. These methods play a key part in nondestructive evaluation scenarios where data that is collected by sensors of different modalities must be registered to be fused. In this paper, automated registration based on normalized mutual information is applied to align data derived from ultrasonic and radiographic inspections of (i) additively manufactured titanium alloy test coupons, and (ii) thin, lithium metal pouch-cell batteries. The quality of the registration is quantified in terms of computational resources and spatial accuracy. In the first case the X-ray computed tomography (XCT) data is captured on a region corresponding to a small subset of the ultrasonic data, while in the case of the lithium batteries the digital radiography (DR) captures a larger region of interest than the ultrasonic data. In both cases the radiographic data resolution is much higher than for ultrasound, but interestingly, in both cases the accuracy of the registration is approximately equal to two-to-three-pixel lengths in the ultrasonic images.

Nondestructive Evaluation

Processing Welding Images For Robot Control

Image data from two distinct windows used to locate weld features. Analyzer part of vision system described in companion article, "Image Control in Automatic Welding Vision System" (MFS-26035). Horizontal video lines define windows for viewing unwelded joint and weld pool. Data from picture elements outside windows not processed. Widely-separated local features carry no significance, but closely spaced features indicate welding feature. Image processor assigns confidence level to group of local features according to spacing and pattern.

Richardson, Richard W.

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/ deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.

Recent improvements and enhancements to NASTRAN

Several improvements and enhancements recently made to NASTRAN are described. Some of the more important features are: streamlined rigid formats; improved rigid formats; changes related to plotting; checking of required PARAM bulk data cards; checkpoint/restart capability; unsorted and sorted bulk data deck echo; automatic output of the DMAP source listing; elimination of link switching caused by use of utility modules; paging the NASTRAN output; processing of mixed record data blocks by INPUT2/OUTPUT2 modules; module execute flag included in the OSCAR listing; and use of the multiple XDMAP cards in the DMAP. It is concluded that these changes increase the usefulness of the program.

Pamidi, P. R.

Interpretation and automatic image enhancement facility

The author has identified the following significant results. Efforts to provide data processing support for ERTS-1 investigators in Kansas are summarized. Programs have been developed for data retrieval, feature extraction, and classification of digital MSS data. The IDECS/PDP-15 facility at the University of Kansas Remote Sensing Laboratory has been used for quick look analysis of ERTS-1 imagery. Programs have been developed for studying fresh water bodies in ERTS-1 imagery over Kansas on the IDECS.

Haralick, R. M.

A feasibility study: Forest Fire Advanced System Technology (FFAST)

The National Aeronautics and Space Administration/Jet Propulsion Laboratory and the United States Department of Agriculture Forest Service completed a feasibility study that examined the potential uses of advanced technology in forest fires mapping and detection. The current and future (1990's) information needs in forest fire management were determined through interviews. Analysis shows that integrated information gathering and processing is needed. The emerging technologies that were surveyed and identified as possible candidates for use in an end to end system include ""push broom'' sensor arrays, automatic georeferencing, satellite communication links, near real or real time image processing, and data integration. Matching the user requirements and the technologies yielded a ""strawman'' system configuration. The feasibility study recommends and outlines the implementation of the next phase for this project, a two year, conceptual design phase to define a system that warrants continued development.

Mcleod, R. G.

Principal components technique analysis for vegetation and land use discrimination

Automatic pre-processing technique called Principal Components (PRINCO) in analyzing LANDSAT digitized data, for land use and vegetation cover, on the Brazilian cerrados was evaluated. The chosen pilot area, 223/67 of MSS/LANDSAT 3, was classified on a GE Image-100 System, through a maximum-likehood algorithm (MAXVER). The same procedure was applied to the PRINCO treated image. PRINCO consists of a linear transformation performed on the original bands, in order to eliminate the information redundancy of the LANDSAT channels. After PRINCO only two channels were used thus reducing computer effort. The original channels and the PRINCO channels grey levels for the five identified classes (grassland, "cerrado", burned areas, anthropic areas, and gallery forest) were obtained through the MAXVER algorithm. This algorithm also presented the average performance for both cases. In order to evaluate the results, the Jeffreys-Matusita distance (JM-distance) between classes was computed. The classification matrix, obtained through MAXVER, after a PRINCO pre-processing, showed approximately the same average performance in the classes separability.

Parada, N. D. J.

Signature-extendable technology - Global space-based crop recognition

The use of signature-extendable technology to improve the efficiency of machine processing of remotely sensed data is examined. Temporal profile technology is employed to automatically recognize crops; the technique uses the Kauth and Thomas (1976) transform of Landsat, multidata, and parameters derived from a model of each crop's greenness-time trajectory. The basic characteristics of temporal profile technology and the U.S. based labeling algorithm are described. Consideration is given to signature extension, signature-extendable spaces, and signature-extendable features. The greenness and brightness parameters used in temporal profile technology are derived. The signature extendability of the parameters is evaluated by applying them to the analysis of corn and soybean crops in the U.S. and Argentina. It is noted that the technique is an affordable and efficient method for deriving data on crops on a global basis.

Hall, Forrest G.

The NASA master directory quick reference guide

The NASA Master Directory (MD) is a free, online, multidisciplinary directory of space and Earth science data sets (NASA and non-NASA data) that are of potential interest to the NASA-sponsored research community. The MD contains high-level descriptions of data sets, other data systems and archives, and campaigns and projects. It provides mechanisms for searching for data sets by important criteria such as geophysical parameters, time, and spatial coverage. The MD also provides information on ordering the data. In order to simplify the process of finding more detailed information or accessing online data, the MD provides automatic connections to a number of data systems such as the NASA Climate Data System, the Planetary Data System, the NASA Ocean Data System, the Pilot Land Data System, and others. The MD also provides general information about many data systems, data centers, and coordinated data analysis projects. It represents the first major step in the Catalog Interoperability project, whose objective is to enable researchers to quickly and efficiently identity, obtain information about, and get access to space and Earth science data.

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