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NASA NTRS2004

Review of Computational Stirling Analysis Methods

Nuclear thermal to electric power conversion carries the promise of longer duration missions and higher scientific data transmission rates back to Earth for both Mars rovers and deep space missions. A free-piston Stirling convertor is a candidate technology that is considered an efficient and reliable power conversion device for such purposes. While already very efficient, it is believed that better Stirling engines can be developed if the losses inherent its current designs could be better understood. However, they are difficult to instrument and so efforts are underway to simulate a complete Stirling engine numerically. This has only recently been attempted and a review of the methods leading up to and including such computational analysis is presented. And finally it is proposed that the quality and depth of Stirling loss understanding may be improved by utilizing the higher fidelity and efficiency of recently developed numerical methods. One such method, the Ultra HI-Fl technique is presented in detail.

Dyson, Rodger W.↗

NASA NTRS1998

Baseline Observations of Hemispheric Sea Ice with the Nimbus 7 Scanning Multichannel Microwave Radiometer

The Scanning Multichannel Microwave Radiometer (SMMR) on board the NASA Nimbus 7 satellite was designed to obtain data for sea surface temperatures (SSTs), near-surface wind speeds, sea ice coverage and type, rainfall rates over the oceans, cloud water content, snow water equivalent, and soil moisture. In this paper, I shall emphasize the sea ice observations and mention briefly some important SST observations. A prime factor contributing to the importance of SMMR sea ice observations lies in their successful integration into a long-term time series, presently being extended by observations from the series of Special Sensor Microwave/Imager (SSMI) on board the DOD/DMSP F8, Fl1, and F12 satellites. This currently constitutes a 19-year data set. Almost half of this was provided by the SMMR. Unfortunately, the 4-year data set produced earlier by the single-channel Electrically Scanned Microwave Radiometer (ESMR) was not successfully integrated into the SMMR/SSMI data set. This resulted primarily from the lack of an overlap period to provide intersensor adjustment, but also because of the large difference between the algorithms to produce ice concentrations and large temporal gaps in the ESMR data. The lack of overlap between the SeaSat and Nimbus 7 SMMR data sets was an important consideration for also excluding the SeatSat one, but the spatial gaps especially in the Southern Hemisphere daily SeaSat observations was another. The sea ice observations will continue into the future by means of the Advanced Microwave Scanning Radiometer (AMSR) on board the ADEOS II and EOS satellites due to be launched in mid- and late-2000, respectively. Analysis of the sea ice data has been carried out by a number of different techniques. Long-term trends have been examined by means of ordinary least squares and band-limited regression. Oscillations in the data have been examined by band-limited Fourier analysis. Here, I shall present results from a novel combination of Principal Component analysis and the recently-developed Empirical Mode Decomposition (EMD). In this method, the data are first separated into spatial and temporal parts, and then the temporal parts of the first few PCs are broken into intrinsic modes by the EMD method.

Gloersen, Per↗

NASA NTRS1991

Optical methods of stress analysis applied to cracked components

After briefly describing the principles of frozen stress photoelastic and moire interferometric analyses, and the corresponding algorithms for converting optical data from each method into stress intensity factors (SIF), the methods are applied to the determination of crack shapes, SIF determination, crack closure displacement fields, and pre-crack damage mechanisms in typical aircraft component configurations.

Smith, C. W.↗

NASA NTRS2005

Recent Applications of Higher-Order Spectral Analysis to Nonlinear Aeroelastic Phenomena

Recent applications of higher-order spectral (HOS) methods to nonlinear aeroelastic phenomena are presented. Applications include the analysis of data from a simulated nonlinear pitch and plunge apparatus and from F-18 flight flutter tests. A MATLAB model of the Texas A&MUniversity s Nonlinear Aeroelastic Testbed Apparatus (NATA) is used to generate aeroelastic transients at various conditions including limit cycle oscillations (LCO). The Gaussian or non-Gaussian nature of the transients is investigated, related to HOS methods, and used to identify levels of increasing nonlinear aeroelastic response. Royal Australian Air Force (RAAF) F/A-18 flight flutter test data is presented and analyzed. The data includes high-quality measurements of forced responses and LCO phenomena. Standard power spectral density (PSD) techniques and HOS methods are applied to the data and presented. The goal of this research is to develop methods that can identify the onset of nonlinear aeroelastic phenomena, such as LCO, during flutter testing.

Silva, Walter A.↗

NASA NTRS1972

Development and evaluation of the impulse transfer function technique

The development of the test/analysis technique known as the impulse transfer function (ITF) method is discussed. This technique, when implemented with proper data processing systems, should become a valuable supplement to conventional dynamic testing and analysis procedures that will be used in the space shuttle development program. The method can relieve many of the problems associated with extensive and costly testing of the shuttle for transient loading conditions. In addition, the time history information derived from impulse testing has the potential for being used to determine modal data for the structure under investigation. The technique could be very useful in determining the time-varying modal characteristics of structures subjected to thermal transients, where conventional mode surveys are difficult to perform.

Mantus, M.↗

NASA NTRS2012

Wavespace-Based Coherent Deconvolution

Array deconvolution is commonly used in aeroacoustic analysis to remove the influence of a microphone array's point spread function from a conventional beamforming map. Unfortunately, the majority of deconvolution algorithms assume that the acoustic sources in a measurement are incoherent, which can be problematic for some aeroacoustic phenomena with coherent, spatially-distributed characteristics. While several algorithms have been proposed to handle coherent sources, some are computationally intractable for many problems while others require restrictive assumptions about the source field. Newer generalized inverse techniques hold promise, but are still under investigation for general use. An alternate coherent deconvolution method is proposed based on a wavespace transformation of the array data. Wavespace analysis offers advantages over curved-wave array processing, such as providing an explicit shift-invariance in the convolution of the array sampling function with the acoustic wave field. However, usage of the wavespace transformation assumes the acoustic wave field is accurately approximated as a superposition of plane wave fields, regardless of true wavefront curvature. The wavespace technique leverages Fourier transforms to quickly evaluate a shift-invariant convolution. The method is derived for and applied to ideal incoherent and coherent plane wave fields to demonstrate its ability to determine magnitude and relative phase of multiple coherent sources. Multi-scale processing is explored as a means of accelerating solution convergence. A case with a spherical wave front is evaluated. Finally, a trailing edge noise experiment case is considered. Results show the method successfully deconvolves incoherent, partially-coherent, and coherent plane wave fields to a degree necessary for quantitative evaluation. Curved wave front cases warrant further investigation. A potential extension to nearfield beamforming is proposed.

Bahr, Christopher J.↗

NASA NTRS2021

Truncated ARQ Statistical Link Analysis for Dynamic Links

The future deep space links are migrating towards higher frequency bands such as Ka band and optical. These links are susceptible to non Gaussian and non linear effects such as atmospheric turbulence, scintillation, antenna mis-pointing, jitter, etc. These dynamic links thus will experience various degrees of fading loss, and some of these link disruptions cannot be effectively mitigated by forward error correction coding and/or interleaving. One effective way to ensure reliable communication is by using Automatic Repeat Request (ARQ) protocol, where the receiver acknowledges to the transmitter whether or not a data unit is successfully received. If a data unit is not successfully received (such as after a pre-set time-out), the transmitter would then re-transmit the lost data unit to the receiver. In a previous paper, we derived a statistical link analysis method of finding the optimal operating Signal-to-Noise Ratio (SNR) and estimating the latency of an ARQ scheme. In a more recent paper, we demonstrated the above method using the SNR distribution constructed from the Ka-band (32 GHz) flight data. To simplify the discussion, we considered the academic approach that the ARQ scheme allows for an infinite number of retransmissions. In this paper, we consider the more practical case of a truncated ARQ scheme, where there is a limit on the number of retransmissions. We derive the error probability, the optimal SNR setting, and the latency statistics of the correctly received frames of the truncated ARQ schemes. We first discuss the truncated ARQ link analysis principles using the Gaussian assumption for SNR distribution with a large variance. Next, we demonstrate the statistical truncated ARQ link analysis using the SNR distribution constructed from the Ka-band flight data. The results in this paper can be applied in the design of reliable communication systems such as the Consultative Committee for Space Data System (CCSDS) File Transfer Protocol (CFTP) and the Delay Tolerant Network (DTN).

Morabito, David↗

NASA NTRS2003

Kernel PLS-SVC for Linear and Nonlinear Discrimination

A new methodology for discrimination is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by support vector machines for classification. Close connection of orthonormalized PLS and Fisher's approach to linear discrimination or equivalently with canonical correlation analysis is described. This gives preference to use orthonormalized PLS over principal component analysis. Good behavior of the proposed method is demonstrated on 13 different benchmark data sets and on the real world problem of the classification finger movement periods versus non-movement periods based on electroencephalogram.

Rosipal, Roman↗

NASA NTRS2008

RHSEG and Subdue: Background and Preliminary Approach for Combining these Technologies for Enhanced Image Data Analysis, Mining and Knowledge Discovery

Under a project recently selected for funding by NASA's Science Mission Directorate under the Applied Information Systems Research (AISR) program, Tilton and Cook will design and implement the integration of the Subdue graph based knowledge discovery system, developed at the University of Texas Arlington and Washington State University, with image segmentation hierarchies produced by the RHSEG software, developed at NASA GSFC, and perform pilot demonstration studies of data analysis, mining and knowledge discovery on NASA data. Subdue represents a method for discovering substructures in structural databases. Subdue is devised for general-purpose automated discovery, concept learning, and hierarchical clustering, with or without domain knowledge. Subdue was developed by Cook and her colleague, Lawrence B. Holder. For Subdue to be effective in finding patterns in imagery data, the data must be abstracted up from the pixel domain. An appropriate abstraction of imagery data is a segmentation hierarchy: a set of several segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. The RHSEG program, a recursive approximation to a Hierarchical Segmentation approach (HSEG), can produce segmentation hierarchies quickly and effectively for a wide variety of images. RHSEG and HSEG were developed at NASA GSFC by Tilton. In this presentation we provide background on the RHSEG and Subdue technologies and present a preliminary analysis on how RHSEG and Subdue may be combined to enhance image data analysis, mining and knowledge discovery.

Tilton, James C.↗

NASA NTRS1994

Practical Planning in COLLAGE

COLLAGE is a domain-independent planner that differs from traditional planners in two key ways: (1) it uses a diverse and extendible set of (it action-based) plan constructions methods; and (2) it utilizes a technique called (it localization) to partition the planning problem into smaller (and potentially interacting) sub problems. In this paper, we describe these features and how they are exploited in two different real-world planning domains. The first domain, building construction planning, has served as a framework for us to investigate how localization can improve scalability. The second domain, data analysis planning, benefits from COLLAGE's unique plan construction and representation methods. In addition, we describe extensions that were necessary to tackle these real-world problems.

Lansky, Amy L.↗

NASA NTRS1988

A design for a ground-based data management system

An initial design for a ground-based data management system which includes intelligent data abstraction and cataloging is described. The large quantity of data on some current and future NASA missions leads to significant problems in providing scientists with quick access to relevant data. Human screening of data for potential relevance to a particular study is time-consuming and costly. Intelligent databases can provide automatic screening when given relevent scientific parameters and constraints. The data management system would provide, at a minimum, information of availability of the range of data, the type available, specific time periods covered together with data quality information, and related sources of data. The system would inform the user about the primary types of screening, analysis, and methods of presentation available to the user. The system would then aid the user with performing the desired tasks, in such a way that the user need only specify the scientific parameters and objectives, and not worry about specific details for running a particular program. The design contains modules for data abstraction, catalog plan abstraction, a user-friendly interface, and expert systems for data handling, data evaluation, and application analysis. The emphasis is on developing general facilities for data representation, description, analysis, and presentation that will be easily used by scientists directly, thus bypassing the knowledge acquisition bottleneck. Expert system technology is used for many different aspects of the data management system, including the direct user interface, the interface to the data analysis routines, and the analysis of instrument status.

Lambird, Barbara A.↗

NASA NTRS1976

Creep-Rupture Data Analysis - Engineering Application of Regression Techniques

The results are presented of investigations to apply regression techniques to the development of methodology for creep-rupture data analysis. Regression analysis techniques are applied to the explicit description of the creep behavior of materials for space shuttle thermal protection systems. A regression analysis technique is compared with five parametric methods for analyzing three simulated and twenty real data sets, and a computer program for the evaluation of creep-rupture data is presented.

Rummler, D. R.↗

NASA NTRS2001

Left ventricular endocardial surface detection based on real-time 3D echocardiographic data

OBJECTIVE: A new computerized semi-automatic method for left ventricular (LV) chamber segmentation is presented. METHODS: The LV is imaged by real-time three-dimensional echocardiography (RT3DE). The surface detection model, based on level set techniques, is applied to RT3DE data for image analysis. The modified level set partial differential equation we use is solved by applying numerical methods for conservation laws. The initial conditions are manually established on some slices of the entire volume. The solution obtained for each slice is a contour line corresponding with the boundary between LV cavity and LV endocardium. RESULTS: The mathematical model has been applied to sequences of frames of human hearts (volume range: 34-109 ml) imaged by 2D and reconstructed off-line and RT3DE data. Volume estimation obtained by this new semi-automatic method shows an excellent correlation with those obtained by manual tracing (r = 0.992). Dynamic change of LV volume during the cardiac cycle is also obtained. CONCLUSION: The volume estimation method is accurate; edge based segmentation, image completion and volume reconstruction can be accomplished. The visualization technique also allows to navigate into the reconstructed volume and to display any section of the volume.

Non-NASA Center↗

NASA NTRS1994

Computer modeling the fatigue crack growth rate behavior of metals in corrosive environments

The objective of this task was to develop a method to digitize FCP (fatigue crack propagation) kinetics data, generally presented in terms of extensive da/dN-Delta K pairs, to produce a file for subsequent linear superposition or curve-fitting analysis. The method that was developed is specific to the Numonics 2400 Digitablet and is comparable to commercially available software products as Digimatic(sup TM 4). Experiments demonstrated that the errors introduced by the photocopying of literature data, and digitization, are small compared to those inherent in laboratory methods to characterize FCP in benign and aggressive environments. The digitizing procedure was employed to obtain fifteen crack growth rate data sets for several aerospace alloys in aggressive environments.

Richey, Edward, III↗

NASA NTRS1978

Interplanetary approach optical navigation with applications

The use of optical data from onboard television cameras for the navigation of interplanetary spacecraft during the planet approach phase is investigated. Three optical data types were studied: the planet limb with auxiliary celestial references, the satellite-star, and the planet-star two-camera methods. Analysis and modelling issues related to the nature and information content of the optical methods were examined. Dynamic and measurement system modelling, data sequence design, measurement extraction, model estimation and orbit determination, as relating optical navigation, are discussed, and the various error sources were analyzed. The methodology developed was applied to the Mariner 9 and the Viking Mars missions. Navigation accuracies were evaluated at the control and knowledge points, with particular emphasis devoted to the combined use of radio and optical data. A parametric probability analysis technique was developed to evaluate navigation performance as a function of system reliabilities.

Jerath, N.↗

NASA NTRS1978

A physical parameter method for the design of broad-band X-ray imaging systems to do coronal plasma diagnostics

The technique commonly used for the analysis of data from broad-band X-ray imaging systems for plasma diagnostics is the filter ratio method. This requires the use of two or more broad-band filters to derive temperatures and line-of-sight emission integrals or emission measure distributions as a function of temperature. Here an alternative analytical approach is proposed in which the temperature response of the imaging system is matched to the physical parameter being investigated. The temperature response of a system designed to measure the total radiated power along the line of sight of any coronal structure is calculated. Other examples are discussed.

Kahler, S.↗

NASA NTRS2000

Long-term Global Morphology of Gravity Wave Activity Using UARS Data

This quarter was largely devoted to a detailed study of temperature data acquired by the Cryogenic Limb Array Etalon Spectrometer (CLAES) on UARS. Our analysis used the same sequence of methods that have been developed, tested and refined on a more limited subset of temperature data acquired by the CRISTA instrument. We focused on a limited subset of our reasoning that geographical and vertical trends in the small-scale temperature variability could be compared with similar trends observed in November 1994 by the CRISTA-SPAS satellite. Results, backed up with hindcasts from the Mountain Wave Forecast Model (MWFM), reveal strong evidence of mountain waves, most persuasively in the Himalayas on 16-17 November, 1992. These CLAES results are coherent over the 30-50 km range and compare well with MWFM hindcasts for the same period. This constitutes, we believe, the first clear evidence that CLAES explicitly resolved long wavelength gravity waves in its CO2 temperature channel. A series of other tasks, related to mesoscale modeling of mountain waves in CRISTA data and fitting of ground-based and HRDI data on global scales, were seen through to publication stage in peer-reviewed journals.

Eckermann, Stephen D.↗

NASA NTRS2011

Improve Data Mining and Knowledge Discovery Through the Use of MatLab

Data mining is widely used to mine business, engineering, and scientific data. Data mining uses pattern based queries, searches, or other analyses of one or more electronic databases/datasets in order to discover or locate a predictive pattern or anomaly indicative of system failure, criminal or terrorist activity, etc. There are various algorithms, techniques and methods used to mine data; including neural networks, genetic algorithms, decision trees, nearest neighbor method, rule induction association analysis, slice and dice, segmentation, and clustering. These algorithms, techniques and methods used to detect patterns in a dataset, have been used in the development of numerous open source and commercially available products and technology for data mining. Data mining is best realized when latent information in a large quantity of data stored is discovered. No one technique solves all data mining problems; challenges are to select algorithms or methods appropriate to strengthen data/text mining and trending within given datasets. In recent years, throughout industry, academia and government agencies, thousands of data systems have been designed and tailored to serve specific engineering and business needs. Many of these systems use databases with relational algebra and structured query language to categorize and retrieve data. In these systems, data analyses are limited and require prior explicit knowledge of metadata and database relations; lacking exploratory data mining and discoveries of latent information. This presentation introduces MatLab(R) (MATrix LABoratory), an engineering and scientific data analyses tool to perform data mining. MatLab was originally intended to perform purely numerical calculations (a glorified calculator). Now, in addition to having hundreds of mathematical functions, it is a programming language with hundreds built in standard functions and numerous available toolboxes. MatLab's ease of data processing, visualization and its enormous availability of built in functionalities and toolboxes make it suitable to perform numerical computations and simulations as well as a data mining tool. Engineers and scientists can take advantage of the readily available functions/toolboxes to gain wider insight in their perspective data mining experiments.

Shaykhian, Gholam Ali↗