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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,693 records · Page 94
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Experimental study of digital image processing techniques for LANDSAT data

The author has identified the following significant results. Results are reported for: (1) subscene registration, (2) full scene rectification and registration, (3) resampling techniques, (4) and ground control point (GCP) extraction. Subscenes (354 pixels x 234 lines) were registered to approximately 1/4 pixel accuracy and evaluated by change detection imagery for three cases: (1) bulk data registration, (2) precision correction of a reference subscene using GCP data, and (3) independently precision processed subscenes. Full scene rectification and registration results were evaluated by using a correlation technique to measure registration errors of 0.3 pixel rms thoughout the full scene. Resampling evaluations of nearest neighbor and TRW cubic convolution processed data included change detection imagery and feature classification. Resampled data were also evaluated for an MSS scene containing specular solar reflections.

Rifman, S. S.↗
NASA NTRS1977

As-built design specification for the digital derivation of daily and monthly data bases from synoptic observations of temperature and precipitation for the People's Republic of China

A data base of synoptic meteorological information was compiled for the People's Republic of China, as an integral part of the Large Area Crop Inventory Experiment. A system description is provided, including hardware and software specifications, computation algorithms and an evaluation of output validity. Operations are also outlined, with emphasis placed on least squares interpolation.

Jeun, B. H.↗
NASA NTRS1978

Remote in-situ elemental analysis systems for underwater application

The systems approach, theoretical measurement calculations, and preliminary measurements to be used in monitoring and mapping pollutants (such as traces of heavy metals) in the Chesapeake Bay are discussed. A neutron gamma-ray method is under development for demonstrating the system. The excitation source to be used is a machine accelerator using a deuterium/tritium reaction to produce 14-MeV neutrons. The neutrons excite characteristic gamma ray emission from the neutron irradiated surface. The discrete line emission produced can be used to infer both qualitative and quantitative elemental composition. A data preprocessor will accumulate, digitize, store, format, and prepare the data for transmission which can be accomplished by telephone, microwave, and possibly satellite link to central processors.

Trombka, J. I.↗
NASA NTRS1983

Fast Electronic Solar Cell Tester

Microcomputer controlled system gather current and voltage data. System consists of light source, microcomputer, programable dc power supply, analog/ digital interface, and data storage display equipment. Applies series of test loads to cell via programable dc power supply to obtain I/V characteristic curve and key cell-peformance parameter. Apparatus and programming technique are applicable to devices such as batteries and sensors.

Lathrop, J. W.↗
NASA NTRS1983

Digital Filters for Two-Dimensional Data

Computational efficient filters speed processing of two-dimensional experimental data. Two-dimensional smoothing filter used to attenuate highfrequency noise in two-dimensional numerical data arrays. Filter provides smoothed data values equal to values obtained by fitting surface with secondand third-order terms to 5 by 5 subset of data points centered on points and replacing data at each point by value of surface fitted at point. Especially suited for efficient analysis of two-dimensional experimental data on images.

Edwards, T. R.↗
NASA NTRS1983

Analytical redundancy management mechanization and flight data analysis for the F-8 digital fly-by-wire aircraft flight control sensors

The details are presented of an onboard digital computer algorithm designed to reliably detect and isolate the first failure in a duplex set of flight control sensors aboard the NASA F-8 digital fly-by-wire aircraft. The algorithm's successful flight test program is summarized, and specific examples are presented of algorithm behavior in response to software-induced signal faults, both with and without aircraft parameter modeling errors.

Deckert, J. C.↗
NASA NTRS1989

Model and simulation development for turbopump health monitoring by parameter estimation

The nonlinear equations describing the flow, pressure and temperature dynamics of the High Pressure Fuel Turbopump of the Space Shuttle Main Engine are summarized and implemented in a digital simulation. Some closed form approximations to the operating curves of the turbopump are made so that closed form derivatives exist. These equations and approximations are then used to develop an extended Kalman filter that estimates the dynamic states of the turbopump and a parameter that can reflect turbopump degradation. The filter is implemented as a digital computer program and applied to data generated by the digital simulation of the turbopump with substantial noise added to the output signals. The results indicate that the parameter estimate converges quickly and accurately. This suggests that the parameter estimate can be used to monitor for turbopump degradations affecting its value.

Walker, Bruce K.↗
NASA NTRS2014

Quantification of In-flight Physical Changes: Anthropometry and Neutral Body Posture

Currently, NASA does not have sufficient in-flight anthropometric data gathered to assess the impact of physical body shape and size changes on suit sizing. For developing future planetary and reduced gravity suits, NASA needs to quantify the impacts of microgravity on anthropometry, body posture, and neutral body postures (NBP) to ensure optimal crew performance, fit, and comfort. To obtain these impacts, anthropometric data, circumference, length, height, breadth, and depth for body segments (i.e. chest, waist, bicep, thigh, calf) from astronauts for pre, in-, and postflight conditions needs to be collected. Once this data has been collected, a comparison between pre, in-, and postflight anthropometric values will be analyzed, yielding microgravity factors. The NBP will be used to determined body posture (joint angle) changes between subjects throughout the duration of a mission. Data collection, starting with Increments 37/38, is still in progress with the completion of 3 out of 12 subjects. NASA suit engineers and NASA's Extravehicular Activity (EVA) Project Office have identified that suit fit in microgravity could become an issue. It has been noted that crewmembers often need to adjust their suit sizing once they are in orbit. This adjustment could be due to microgravity effects on anthropometry and postural changes, and is necessary to ensure optimal crew performance, fit, and comfort in space. To date, the only data collected to determine the effects of microgravity on physical human changes have been during Skylab, STS-57, and a recent HRP study on seated height changes due to spinal elongation (Spinal Elongation, Master Task List [MTL] #221). The Skylab and the STS-57 studies found that there is a distinct neutral body posture (NBP) based on photographs. The still photographs showed that there is a distinguishable posture with the arms raised and the shoulder abducted; and, in addition, the knees were flexed with noticeable hip flexion and the foot plantar flexed [1,2]. This is the one standard set of body joint angles for a NBP in microgravity. A recent simulated microgravity NBP study [3] has shown an individual variability and inconsistencies in defining NBP. This variation may be influenced by spinal growth, the type of suit fit, and other potential anthropometry factors such as spinal curvature, age, and gender. The variation aspect of this essential data is required for all kinds of space device designs (e.g. suits, habitat, mobility aids, etc.). The method proposed considers the dynamic nature of body movement and will use a measurement technique to continually monitor posture and develop a probability likelihood of the natural posture and how the NBP postures are affected by anthropometry. Additionally, Skylab studies found that crewmembers experienced a stature growth of up to 3%. The data included 3 crewmembers that showed that there is a bi-phasic stature growth once the crew enters into weightlessness. However, the Spinal Elongation study identified that the crewmembers could experience about a 6% growth in seated height and a 3% stature growth, when exposed to microgravity. The results prove that not all anthropometric measurements have the same microgravity percent growth factor. For EVA and suit engineers to properly update the sizing protocol for microgravity, they need additional anthropometric data from space missions. Hence, this study is aimed to gather additional in-flight anthropometric measurements, such as length, depth, breadth, and circumference, to determine the changes to body shape and size due to microgravity effects. It is anticipated that by recording the potential changes to body shape and size, a better suit sizing protocol will be developed for ISS and other space missions. In essence, this study will help NASA quantify the impacts of microgravity on anthropometry to ensure optimal crew performance, fit, and comfort. This study will use simplistic data collection techniques, 3D laser scanning, digital still, and video data, and perform photogrammetric analyses to determine the changes that occur to the body shape, size, and NBP when exposed to a microgravity environment.

Young, K. S.↗
NASA NTRSDate not supplied

Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation

National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.

Machine Learning (ML)↗
NASA NTRS1991

Surface reconstruction from scattered data through pruning of unstructured grids

This paper describes an algorithm for reconstructing a surface from a randomly digitized object. Scan data (treated as a cloud of points) is first tesselated out to its convex hull using Delaunay triangulation. The line-of-sight between each surface point and the scanning device is traversed, and any tetrahedra which are pierced by it are removed. The remaining tetrahedra form an approximate solid model of the scanned object. Due to the inherently limited resolution of any scan, this algorithm requires two additional procedures to produce a smooth, polyhedral surface: one process removes long, narrow tetrahedra which span indentations in the surface between digitized points; the other smooths sharp edges. The results for a moderately resolved sample body and a highly resolved aircraft are displayed.

Maksymiuk, C. M.↗
NASA NTRS1978

Applications of digital image processing techniques to problems of data registration and correlation

An overview is presented of the evolution of the computer configuration at JPL's Image Processing Laboratory (IPL). The development of techniques for the geometric transformation of digital imagery is discussed and consideration is given to automated and semiautomated image registration, and the registration of imaging and nonimaging data. The increasing complexity of image processing tasks at IPL is illustrated with examples of various applications from the planetary program and earth resources activities. It is noted that the registration of existing geocoded data bases with Landsat imagery will continue to be important if the Landsat data is to be of genuine use to the user community.

Green, W. B.↗
NASA NTRS1985

Some Opinions on Remote Sensing and Geologic Studies

The principal role of remote sensing data in geologic studies is as a source of geologic information from which meaningful geologic interpretations can be made. Remote sensing data are important in sedimentary basin analysis and other geologic studies as independent and sometimes unique sources of important lithologic and structural information; however, their greatest benefit to exploration-oriented investigations may come when these data are used with other relevant data in a digital database approach to exploration. Modern computer technology facilitates the rapid integration and synthesis of satellite, topographic, gravity, aeromagnetic, geochemical, and other data collected from a given region. Once such data are geometrically registered, they can be digitally processed, within the constraints of defined geologic models, to rapidly identify, and focus further exploration efforts on, target areas that have the greatest potential for success.

Bailey, G. B.↗
NASA NTRS1984

Spatial variation analyses of Thematic Mapper data for the identification of linear features in agricultural landscapes

A need exists for digitized information pertaining to linear features such as roads, streams, water bodies and agricultural field boundaries as component parts of a data base. For many areas where this data may not yet exist or is in need of updating, these features may be extracted from remotely sensed digital data. This paper examines two approaches for identifying linear features, one utilizing raw data and the other classified data. Each approach uses a series of data enhancement procedures including derivation of standard deviation values, principal component analysis and filtering procedures using a high-pass window matrix. Just as certain bands better classify different land covers, so too do these bands exhibit high spectral contrast by which boundaries between land covers can be delineated. A few applications for this kind of data are briefly discussed, including its potential in a Universal Soil Loss Equation Model.

Pelletier, R. E.↗
NASA NTRS1986

Analysis of multiple incidence angle SIR-B data for determining forest stand characteristics

For the first time in the U.S. space program, digital synthetic aperture radar (SR) data were obtained from different incidence angles during Space Shuttle Mission 41-G. Shuttle Imaging Radar-B (SIR-B) data were obtained at incidence angles of 58 deg., 45 deg., and 28 deg., on October 9, 10, and 11, 1984, respectively, for a predominantly forested study area in northern Florida. Cloud-free LANDSAT Thematic Mapper (T.M.) data were obtained over the same area on October 12. The SIR-B data were processed and then digitally registered to the LANDSAT T.M. data by scientists at the Jet Propulsion Laboratory. This is the only known digitally registered SIR-B and T.M. data set for which the data were obtained nearly simultaneously. The data analysis of this information is discussed.

Hoffer, R. M.↗
NASA NTRS1992

Lunar Resources Using Moderate Spectral Resolution Visible and Near-infrared Spectroscopy: Al/si and Soil Maturity

Modern visible and near-infrared detectors are critically important for the accurate identification and relative abundance measurement of lunar minerals; however, even a very small number of well-placed visible and near-infrared bandpass channels provide a significant amount of general information about crucial lunar resources. The Galileo Solid State Imaging system (SSI) multispectral data are an important example of this. Al/Si and soil maturity will be discussed as examples of significant general lunar resource information that can be gleaned from moderate spectral resolution visible and near-infrared data with relative ease. Because quantitative-albedo data are necessary for these kinds of analyses, data such as those obtained by Galileo SSI are critical. SSI obtained synoptic digital multispectral image data for both the nearside and farside of the Moon during the first Galileo Earth-Moon encounter in December 1990. The data consist of images through seven filters with bandpasses ranging from 0.40 microns in the ultraviolet to 0.99 microns in the near-infrared. Although these data are of moderate spectral resolution, they still provide information for the following lunar resources: (1) titanium content of mature mare soils based upon the 0.40/0.56-micron (UV/VIS) ratio; (2) mafic mineral abundance based upon the 0.76/0.99-micron ratio; and (3) the maturity or exposure age of the soils based upon the 0.56-0.76-micron continuum and the 0.76/0.99-micron ratio. Within constraints, these moderate spectral resolution visible and near-infrared reflectance data can also provide elemental information such as Al/Si for mature highland soils.

Fischer, Erich M.↗
NASA NTRS2012

Satellite Observation Systems for Polar Climate Change Studies

The key observational tools for detecting large scale changes of various parameters in the polar regions have been satellite sensors. The sensors include passive and active satellite systems in the visible, infrared and microwave frequencies. The monitoring started with Tiros and Nimbus research satellites series in the 1970s but during the period, not much data was stored digitally because of limitations and cost of the needed storage systems. Continuous global data came about starting with the launch of ocean color, passive microwave, and thermal infrared sensors on board Nimbus-7 and Synthetic Aperture Radar, Radar Altimeter and Scatterometer on board SeaSat satellite both launched in 1978. The Nimbus-7 lasted longer than expected and provided about 9 years of useful data while SeaSat quit working after 3 months but provided very useful data that became the baseline for follow-up systems with similar capabilities. Over the years, many new sensors were launched, some from Japan Aeronautics and Space Agency (JAXA), some from the European Space Agency (ESA) and more recently, from RuSSia, China, Korea, Canada and India. For polar studies, among the most useful sensors has been the passive microwave sensor which provides day/night and almost all weather observation of the surface. The sensor provide sea surface temperature, precipitation, wind, water vapor and sea ice concentration data that have been very useful in monitoring the climate of the region. More than 30 years of such data are now available, starting with the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7, the Special Scanning Microwave/Imager (SSM/I) on board a Defense Meteorological Satellite Program (DMSP) and the Advanced Microwave Scanning Radiometer on board the EOS/ Aqua satellite. The techniques that have been developed to derive geophysical parameters from data provided by these and other sensors and associated instrumental and algorithm errors and validation techniques will be discussed. An important issue is the organization and storage of hundreds of terabytes of data collected by even just a few of these satellite sensors. Advances in mass storage and computer technology have made it possible to overcome many of the collection and archival problems and the availability of comprehensive satellite data sets put together by NASA's Earth Observing System project will be discussed.

Comiso, Josefino C.↗