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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 397 records · Page 22

The Extraction of One-Dimensional Flow Properties from Multi-Dimensional Data Sets

The engineering design and analysis of air-breathing propulsion systems relies heavily on zero- or one-dimensional properties (e.g. thrust, total pressure recovery, mixing and combustion efficiency, etc.) for figures of merit. The extraction of these parameters from experimental data sets and/or multi-dimensional computational data sets is therefore an important aspect of the design process. A variety of methods exist for extracting performance measures from multi-dimensional data sets. Some of the information contained in the multi-dimensional flow is inevitably lost when any one-dimensionalization technique is applied. Hence, the unique assumptions associated with a given approach may result in one-dimensional properties that are significantly different than those extracted using alternative approaches. The purpose of this effort is to examine some of the more popular methods used for the extraction of performance measures from multi-dimensional data sets, reveal the strengths and weaknesses of each approach, and highlight various numerical issues that result when mapping data from a multi-dimensional space to a space of one dimension.

Baurle, Robert A.↗

Evaluation of the application of ERTS-1 data to the regional land use planning process

The author has identified the following significant results. Employing simple and economical extraction methods, ERTS can provide valuable data to the planners at the state or regional level with a frequency never before possible. Interactive computer methods of working directly with ERTS digital information show much promise for providing land use information at a more specific level, since the data format production rate of ERTS justifies improved methods of analysis.

Clapp, J. L.↗

Development of data processing, interpretation and analysis system for remote sensing of trace atmospheric gas species

Highly efficient methods were developed for the analysis and reduction of Measurement of Air Pollution from Satellite (MAPS) data. Specific attention was directed to analyzing the data from the Office of Space and Terrestrial Applications 3 (OSTA-3) correlative measurements of aircraft research flights and from the OSTA-3 shuttle flight. Methods were developed for error analysis of the aircraft and spacecraft instruments. The LSI 11/23 software system was modified and expanded for future data analysis.

Gormsen, B. B.↗

Inverse problems in the design, modeling and testing of engineering systems

Formulations, classification, areas of application, and approaches to solving different inverse problems are considered for the design of structures, modeling, and experimental data processing. Problems in the practical implementation of theoretical-experimental methods based on solving inverse problems are analyzed in order to identify mathematical models of physical processes, aid in input data preparation for design parameter optimization, help in design parameter optimization itself, and to model experiments, large-scale tests, and real tests of engineering systems.

Alifanov, Oleg M.↗

Remote-sensing based technique to account for sub-grid scale variability of land surface properties

A method has been presented for the representation of sub-grid scale variability of surface properties within a land surface processes model. The method uses remotely-sensed data to directly or indirectly estimate probability density functions (PDF's) or key surface variables. Application of this technique in a coupled land surface-atmosphere model requires only grid-scale values of the variables of interest, obtained from low-resolution satellite imagery or surface/remote sensing data assimilation. The PDF's of each controlling surface property are superimposed on the respective grid-scale values to simulate sub-grid scale heterogeneity. Sensitivity studies will be carried out to ascertain the relative importance of the heterogeneity of several variables, and the degree to which non-linear property-process interactions impact large-scale fluxes.

Crosson, William L.↗

Wind Tunnel Investigation of Ground Wind Loads for Ares Launch Vehicle

A three year program was conducted at the NASA Langley Research Center (LaRC) Aeroelasticity Branch (AB) and Transonic Dynamics Tunnel (TDT) with the primary objective to acquire scaled steady and dynamic ground-wind loads (GWL) wind-tunnel data for rollout, on-pad stay, and on-pad launch configurations for the Ares I-X Flight Test Vehicle (FTV). The experimental effort was conducted to obtain an understanding of the coupling of aerodynamic and structural characteristics that can result in large sustained wind-induced oscillations (WIO) on such a tall and slender launch vehicle and to generate a unique database for development and evaluation of analytical methods for predicting steady and dynamic GWL, especially those caused by vortex shedding, and resulting in significant WIO. This paper summarizes the wind-tunnel test program that employed two dynamically-aeroelastically scaled GWL models based on the Ares I-X Flight Test Vehicle. The first model tested, the GWL Checkout Model (CM), was a relatively simple model with a secondary objective of restoration and development of processes and methods for design, fabrication, testing, and data analysis of a representative ground wind loads model. In addition, parametric variations in surface roughness, Reynolds number, and protuberances (on/off) were investigated to determine effects on GWL characteristics. The second windtunnel model, the Ares I-X GWL Model, was significantly more complex and representative of the Ares I-X FTV and included the addition of simplified rigid geometrically-scaled models of the Kennedy Space Center (KSC) Mobile Launch Platform (MLP) and Launch Complex 39B primary structures. Steady and dynamic base bending moment as well as model response and steady and unsteady pressure data was acquired during the testing of both models. During wind-tunnel testing of each model, flow conditions (speed and azimuth) where significant WIO occurred, were identified and thoroughly investigated. Scaled data from the Ares I-X GWL model test was used in the determination of worst-case loads for the analysis of Ares I-X FTV design wind conditions. Finally, this paper includes a brief discussion of the limited full-scale GWL data acquired during the rollout and on-pad stay of the Ares I-X FTV that was launched from KSC on October 28, 2009.

Keller, Donald F.↗

Mountain building processes in the Central Andes

False color composite images of the Thematic Mapper (TM) bands 5, 4, and 2 were examined to make visual interpretations of geological features. The use of the roam mode of image display with the International Imaging Systems (IIS) System 600 image processing package running on the IIS Model 75 was very useful. Several areas in which good comparisons with ground data existed, were examined in detail. Parallel to the visual approach, image processing methods are being developed which allow the complete use of the seven TM bands. The data was organized into easily accessible files and a visual cataloging of the quads (quarter TM scenes) with preliminary registration with the best available charts for the region. The catalog has proved to be a valuable tool for the rapid scanning of quads for a specific investigation. Integration of the data into a complete approach to the problems of uplift, deformation, and magnetism in relation to the Nazca-South American plate interaction is at an initial stage.

Bloom, A. L.↗

WFC3 Calibration and Data Processing

Wide Field Camera 3 (WFC3), a panchromatic imager being developed for the Hubble Space Telescope (HST), is now fully integrated and over the past year has completed first rounds of extensive ground testing at Goddard Space Flight Center (GSFC), in both ambient and thermal-vacuum test environments. This report summarizes the results of those tests and describes the pipeline processing methods that will be used to calibrate WFC3 data. WFC3 is designed to ensure that the superb imaging performance of HST is maintained through the end of the mission and takes advantage of recent developments in detector technology to provide new and unique capabilities for HST. WFC3 contains ultraviolet/visible (UVIS) and near-infrared (IR) imaging channels, offering high sensitivity and wide field of view over the broadest wavelength range of any HST instrument. It is slated to replace the current Wide Field and Planetary Camera 2 during Servicing Mission 4. The WFC3 UVIS channel is based on elements from the Advanced Camera for Surveys (ACS)Wide Field Camera (WFC), with a 4096x4096 pixel Marconi CCD covering a 160x160 arcsecond field of view. The WFC3 UVIS channel is optimized for maximum sensitivity in the near-UV and contains a complement of 48 spectral filters and a grism. The WFC3 IR channel uses a 1024x1024 pixel HgCdTe Hawaii-1R detector array covering a 135x135 arcsecond field of view. The array sensitivity is optimized in the 0.8-1.7micron spectral range. The IR channel accomodates 15 filters and 2 grisms for slitless spectroscopy.

Bushouse, H.↗

A generalized method for the identification of aircraft stability and control derivatives from flight test data.

This paper discusses the application of a generalized identification method for flight test data analysis. The method is based on the maximum likelihood (ML) criterion and includes output error and equation error methods as special cases. Both the linear and nonlinear models with and without process noise are considered. The flight test data from lateral maneuvers of HL-10 and M2/F3 lifting bodies are processed to determine the lateral stability and control derivatives, instrumentation accuracies and biases. A comparison is made between the results of the output error method and the generalized ML method for M2/F3 data containing gusts. It is shown that better fits to time histories are obtained by using the generalized ML method.

Mehra, R. K.↗

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

On Certain New Methodology for Reducing Sensor and Readout Electronics Circuitry Noise in Digital Domain

NASA Hubble Space Telescope (HST) and upcoming cosmology science missions carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection, and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensors. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed by the Hubble Space Telescope and the James Webb Space Telescope Projects. These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active (non-reference) pixel signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert- Huang Transform Data Processing System (HHT-DPS) for reference pixel information processing and its utilization in reconfigurable hardware on-board a spaceflight instrument or post-processing on the ground. The methodology examines signal processing for a 2-D domain, in which high-variance components of the thermal noise are carried by both active and reference pixels, similar to that in processing of low-voltage differential signals and subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the aforementioned statistical parameters in the digital domain (such as statistical averaging of the reference pixels themselves) zeroes out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast-varying noise components using the Hilbert-Huang Transform Data Processing System tool (HHT-DPS) developed at NASA and the high-level programming language MATLAB (Trademark of MathWorks Inc.), as well as alternative methods for correcting for the high-variance noise component, using an HgCdTe sensor data. The NASA Hubble Space Telescope data post-processing, as well as future deep-space cosmology projects on-board instrument data processing from all the sensor channels, would benefit from this effort.

Kizhner, Semion↗

Image processing applied to gravity and topography data covering the continental United States

The applicability of fairly standard image processing techniques to processing and analyzing large geologic data sets in addressed. Image filtering techniques were used to interpolate between gravity station locations to produce a regularly spaced data array that preserves detail in areas with good coverage, and that produces a continuous tone image rather than a contour map. Standard image processing techniques were used to digitally register and overlay topographic and gravity data, and the data were displayed in ways that emphasize subtle but pervasive structural features. The potential of the methods is illustrated through a discussion of linear structures that appear in the processed data between the midcontinent gravity high and the Appalachians.

Arvidson, R. E.↗

Investigation of correlation classification techniques

A two-step classification algorithm for processing multispectral scanner data was developed and tested. The first step is a single pass clustering algorithm that assigns each pixel, based on its spectral signature, to a particular cluster. The output of that step is a cluster tape in which a single integer is associated with each pixel. The cluster tape is used as the input to the second step, where ground truth information is used to classify each cluster using an iterative method of potentials. Once the clusters have been assigned to classes the cluster tape is read pixel-by-pixel and an output tape is produced in which each pixel is assigned to its proper class. In addition to the digital classification programs, a method of using correlation clustering to process multispectral scanner data in real time by means of an interactive color video display is also described.

Haskell, R. E.↗

Filtering flight data prior to aerodynamic system identification

An algorithm for processing flight-test data to provide state estimates and instrument calibrations for aerodynamic or hydrodynamic system identification by the equation error estimation method is developed and demonstrated on synthesized data. The extended-Kalman-filter algorithm employs a locally level, north-pointing frame of reference, accounts for rotating ellipsoidal earth effects, and estimates sensor bias, scale factors, wind components, and process noise levels by maximum-likelihood parameters. The method is found to be most effective with navigation quality inertial input data. The algorithm is applied to data from a six-degree-of-freedom F-4 aircraft simulation and shown to produce state estimates in good agreement with the simulation values.

Trankle, T. L.↗

Intelligent monitoring and control of semiconductor manufacturing equipment

The use of AI methods to monitor and control semiconductor fabrication in a state-of-the-art manufacturing environment called the Rapid Thermal Multiprocessor is described. Semiconductor fabrication involves many complex processing steps with limited opportunities to measure process and product properties. By applying additional process and product knowledge to that limited data, AI methods augment classical control methods by detecting abnormalities and trends, predicting failures, diagnosing, planning corrective action sequences, explaining diagnoses or predictions, and reacting to anomalous conditions that classical control systems typically would not correct. Research methodology and issues are discussed, and two diagnosis scenarios are examined.

Murdock, Janet L.↗

On the Use of Mahalanobis Distance in Particle Image Velocimetry Post-Processing

Particle Image Velocimetry (PIV) is a method of flow measurement that has become increasingly popular as an experimental tool. New technology has made high-speed and higher-dimension (stereoscopic, tomographic, etc) methods available to an ever-growing population of researchers. These advanced methods can provide significantly more data than traditional low-speed planar PIV, but these larger data sets also require more resources to process and store. A major time sink in the post-processing of large PIV data sets is the identification and rejection of “bad” or ”spurious” vectors that survive an initial processing step in commercial software, which attempts to identify spurious vectors on an image-by-image basis and not with respect to repeated trials. The Mahalanobis distance, an almost 100-year-old statistical function, was determined to be well suited for this task for its computational efficiency and higher-dimensional nature. This work includes a summary of the Mahalanobis distance and validation of its usefulness as a tool for outlier rejection in the post-processing of PIV data.

Experimental Methods↗

A user-oriented time-shared online system.

Computerized method for on-line data analysis, elucidating SLIP language, request, processing, interpretation, time sharing, background activity, etc

LANGUAGE PROGRAMMING↗

Environmental data display

Methods for using a combination of computer-generated color graphics and image processing techniques to display a large data base of environment information are described. The data source can be either field data or mathematical models, reduced to summary statistics that characterize the data field as a whole. Sharp gradients are plotted into contour plots, which can also feature shades, degree of brightness, and saturation levels for fine-tuning the image. The basic concepts of digital image processing are reviewed, including location of the pixels, intensity mapping operations, pseudocolor enhancements, neighborhood averaging, and smoothing. Sample applications are presented in terms of emissions and air quality distributions over the south coast air basin of southern California.

Hussey, K. J.↗