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At least 379 records · Page 21

Size effect in composite materials and structures: Basic concepts and design considerations

Composite materials display strength characteristics that are similar to those of brittle ceramics, whose strengths are known to decrease with increasing volume for a uniform state of stress (size effect) and also are dependent on stress distribution. These similarities raise the question of whether there is also a size effect in composite materials and structures. There is significant, but inconclusive experimental evidence for the existence of a size effect in composites. Macroscopic and micromechanical statistical models have been developed which predict a size effect and are in general agreement with experimental data. The existence of a significant size effect in composites would be of great importance. For example, it would mean that use of standard test coupons to establish design allowables for large structures could be very nonconservative. Further, it would be necessary to analyze the strength of large composite structures using statistical methods, as is done for ceramics.

Zweben, Carl↗

A strip chart recorder pattern recognition tool kit for Shuttle operations

During Space Shuttle operations, Mission Control personnel monitor numerous mission-critical systems such as electrical power; guidance, navigation, and control; and propulsion by means of paper strip chart recorders. For example, electrical power controllers monitor strip chart recorder pen traces to identify onboard electrical equipment activations and deactivations. Recent developments in pattern recognition technologies coupled with new capabilities that distribute real-time Shuttle telemetry data to engineering workstations make it possible to develop computer applications that perform some of the low-level monitoring now performed by controllers. The number of opportunities for such applications suggests a need to build a pattern recognition tool kit to reduce software development effort through software reuse. We are building pattern recognition applications while keeping such a tool kit in mind. We demonstrated the initial prototype application, which identifies electrical equipment activations, during three recent Shuttle flights. This prototype was developed to test the viability of the basic system architecture, to evaluate the performance of several pattern recognition techniques including those based on cross-correlation, neural networks, and statistical methods, to understand the interplay between an advanced automation application and human controllers to enhance utility, and to identify capabilities needed in a more general-purpose tool kit.

Hammen, David G.↗

Probability of detection of defects in coatings with electronic shearography

The goal of this research was to utilize statistical methods to evaluate the probability of detection (POD) of defects in coatings using electronic shearography. The coating system utilized in the POD studies was to be the paint system currently utilized on the external casings of the NASA Space Transportation System (STS) Revised Solid Rocket Motor (RSRM) boosters. The population of samples was to be large enough to determine the minimum defect size for 90 percent probability of detection of 95 percent confidence POD on these coatings. Also, the best methods to excite coatings on aerospace components to induce deformations for measurement by electronic shearography were to be determined.

Maddux, Gary A.↗

Testing higher-order Lagrangian perturbation theory against numerical simulation. 1: Pancake models

We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of quasi-linear scales. The Lagrangian theory of gravitational instability of an Einstein-de Sitter dust cosmogony investigated and solved up to the third order is compared with numerical simulations. In this paper we study the dynamics of pancake models as a first step. In previous work the accuracy of several analytical approximations for the modeling of large-scale structure in the mildly non-linear regime was analyzed in the same way, allowing for direct comparison of the accuracy of various approximations. In particular, the Zel'dovich approximation (hereafter ZA) as a subclass of the first-order Lagrangian perturbation solutions was found to provide an excellent approximation to the density field in the mildly non-linear regime (i.e. up to a linear r.m.s. density contrast of sigma is approximately 2). The performance of ZA in hierarchical clustering models can be greatly improved by truncating the initial power spectrum (smoothing the initial data). We here explore whether this approximation can be further improved with higher-order corrections in the displacement mapping from homogeneity. We study a single pancake model (truncated power-spectrum with power-spectrum with power-index n = -1) using cross-correlation statistics employed in previous work. We found that for all statistical methods used the higher-order corrections improve the results obtained for the first-order solution up to the stage when sigma (linear theory) is approximately 1. While this improvement can be seen for all spatial scales, later stages retain this feature only above a certain scale which is increasing with time. However, third-order is not much improvement over second-order at any stage. The total breakdown of the perturbation approach is observed at the stage, where sigma (linear theory) is approximately 2, which corresponds to the onset of hierarchical clustering. This success is found at a considerable higher non-linearity than is usual for perturbation theory. Whether a truncation of the initial power-spectrum in hierarchical models retains this improvement will be analyzed in a forthcoming work.

Buchert, T.↗

Probability of detection of defects in coatings with electronic shearography

The goal of this research was to utilize statistical methods to evaluate the probability of detection (POD) of defects in coatings using electronic shearography. The coating system utilized in the POD studies was to be the paint system currently utilized on the external casings of the NASA space transportation system reusable solid rocket motor boosters. The population of samples was to be large enough to determine the minimum defect size for 90-percent POD of 95-percent confidence POD on these coatings. Also, the best methods to excite coatings on aerospace components to induce deformations for measurement by electronic shearography were to be determined.

Russell, S. S.↗

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Djorgovski, George↗

A comparison of CO(J = 1 yields 0) and CO(J = 2 yields 1) emission in the Milky Way molecular ring

We have carried out a CO (J = 2 right arrow 1) survey of the Scutum Arm region of the Milky Way molecular ring. Our goals are to compare CO (J = 2 right arrow 1) maps of individual Galactic clouds with the large-scale CO (J = 2 right arrow 1) emission from the Galactic plane, and to predict the CO (J = 2 right arrow 1) appearance of a Galactic cloud ensemble in an external galaxy. The angular resolution and spatial coverage of our survey are compatible with the existing CO (J = 1 right arrow 0) survey of this region by Sanders et al., which we use for comparison. We identify 34 molecular clouds in our map region; their relationships between size and line width and between virial mass and luminosity are consistent with the relationships seen in CO (J = 1 right arrow 0) emission. However, we note that previous studies have shown considerable variation in these relationships; we attribute much of this variation to differences in their cloud definition algorithm and statistical method. We find that the median ratio of integrated emission in the two lowest CO transitions for the clouds in our sample is I(2 right arrow 1)/ I(1 right arrow 0) = 0.69, implying that the typical emitting region in the line of sight contains cold gas that is not actively star-forming. Our conclusion that the molecular ring emission is not dominated by star-forming regions is consistent with other large-scale studies of the Milky Way. Our distributions of cloud size and temperature also imply that relatively massive molecular clouds that lac k star formation, such as Maddalena's cloud, are not rare in the inner Galaxy.

Chiar, Jean E.↗

SeaWiFS Technical Report Series: SeaWiFS Calibration and Validation Quality Control Procedures - Volume 38

This document provides five brief reports that address several quality control procedures under the auspices of the Calibration and Validation Element (CVE) within the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project. Chapter 1 describes analyses of the 32 sensor engineering telemetry streams. Anomalies in any of the values may impact sensor performance in direct or indirect ways. The analyses are primarily examinations of parameter time series combined with statistical methods such as auto- and cross-correlation functions. Chapter 2 describes how the various onboard (solar and lunar) and vicarious (in situ) calibration data will be analyzed to quantify sensor degradation, if present. The analyses also include methods for detecting the influence of charged particles on sensor performance such as might be expected in the South Atlantic Anomaly (SAA). Chapter 3 discusses the quality control of the ancillary environmental data that are routinely received from other agencies or projects which are used in the atmospheric correction algorithm (total ozone, surface wind velocity, and surface pressure; surface relative humidity is also obtained, but is not used in the initial operational algorithm). Chapter 4 explains the procedures for screening level-, level-2, and level-3 products. These quality control operations incorporate both automated and interactive procedures which check for file format errors (all levels), navigation offsets (level-1), mask and flag performance (level-2), and product anomalies (all levels). Finally, Chapter 5 discusses the match-up data set development for comparing SeaWiFS level-2 derived products with in situ observations, as well as the subsequent outlier analyses that will be used for evaluating error sources.

Hooker, Stanford B.↗

Conjugate-Gradient Neural Networks in Classification of Multisource and Very-High-Dimensional Remote Sensing Data

Application of neural networks to classification of remote sensing data is discussed. Conventional two-layer backpropagation is found to give good results in classification of remote sensing data but is not efficient in training. A more efficient variant, based on conjugate-gradient optimization, is used for classification of multisource remote sensing and geographic data and very-high-dimensional data. The conjugate-gradient neural networks give excellent performance in classification of multisource data, but do not compare as well with statistical methods in classification of very-high-dimentional data.

Benediktsson, J. A.↗

A New Approach to Extreme Value Estimation Applicable to a Wide Variety of Random Variables

Designing reliable structures requires an estimate of the maximum and minimum values (i.e., strength and load) that may be encountered in service. Yet designs based on very extreme values (to insure safety) can result in extra material usage and hence, uneconomic systems. In aerospace applications, severe over-design cannot be tolerated making it almost mandatory to design closer to the assumed limits of the design random variables. The issue then is predicting extreme values that are practical, i.e. neither too conservative or non-conservative. Obtaining design values by employing safety factors is well known to often result in overly conservative designs and. Safety factor values have historically been selected rather arbitrarily, often lacking a sound rational basis. To answer the question of how safe a design needs to be has lead design theorists to probabilistic and statistical methods. The so-called three-sigma approach is one such method and has been described as the first step in utilizing information about the data dispersion. However, this method is based on the assumption that the random variable is dispersed symmetrically about the mean and is essentially limited to normally distributed random variables. Use of this method can therefore result in unsafe or overly conservative design allowables if the common assumption of normality is incorrect.

Holland, Frederic A., Jr.↗

Global Warming Estimation from MSU

In this study, we have developed time series of global temperature from 1980-97 based on the Microwave Sounding Unit (MSU) Ch 2 (53.74 GHz) observations taken from polar-orbiting NOAA operational satellites. In order to create these time series, systematic errors (approx. 0.1 K) in the Ch 2 data arising from inter-satellite differences are removed objectively. On the other hand, smaller systematic errors (approx. 0.03 K) in the data due to orbital drift of each satellite cannot be removed objectively. Such errors are expected to remain in the time series and leave an uncertainty in the inferred global temperature trend. With the help of a statistical method, the error in the MSU inferred global temperature trend resulting from orbital drifts and residual inter-satellite differences of all satellites is estimated to be 0.06 K decade. Incorporating this error, our analysis shows that the global temperature increased at a rate of 0.13 +/- 0.06 K decade during 1980-97.

Prabhakara, C.↗

Physics Based Modeling and Rendering of Vegetation in the Thermal Infrared

We outline a procedure for rendering physically-based thermal infrared images of simple vegetation scenes. Our approach incorporates the biophysical processes that affect the temperature distribution of the elements within a scene. Computer graphics plays a key role in two respects. First, in computing the distribution of scene shaded and sunlit facets and, second, in the final image rendering once the temperatures of all the elements in the scene have been computed. We illustrate our approach for a simple corn scene where the three-dimensional geometry is constructed based on measured morphological attributes of the row crop. Statistical methods are used to construct a representation of the scene in agreement with the measured characteristics. Our results are quite good. The rendered images exhibit realistic behavior in directional properties as a function of view and sun angle. The root-mean-square error in measured versus predicted brightness temperatures for the scene was 2.1 deg C.

Smith, J. A.↗

Single Crystal Fibers of Yttria-Stabilized Cubic Zirconia with Ternary Oxide Additions

Single crystal fibers of yttria (Y2O3)-stabilized cubic zirconia, (ZrO2) with ternary oxide additions were grown using the laser float zone fiber processing technique. Ternary additions to the ZrO2-Y2O3 binary system were studied aimed at increasing strength while maintaining the high coefficient of thermal expansion of the binary system. Statistical methods aided in identifying the most promising ternary oxide candidate (Ta2O5, Sc2O3, and HfO2) and optimum composition. The yttria, range investigated was 14 to 24 mol % and the ternary oxide component ranged from 1 to 5 mol %. Hafnium oxide was the most promising ternary oxide component based on 816 C tensile strength results and ease of fabrication. The optimum composition for development was 81 ZrO2-14 Y203-5 HfO2 based upon the same elevated temperature strength tests. Preliminary results indicate process improvements could improve the fiber performance. We also investigated the effect of crystal orientation on strength.

Ritzert, F. J.↗

Chemical Compositions and Abundance Anomalies in Stellar Coronae ADP99

We have been investigating different statistical methods for analysing the metal abundances of sources with low S/N. A Bayesian technique has been developed that determines the most probable line-to-continuum ratio in the source, thereby leading to the metallicity. This method is a promising approach with which to mine the ASCA archive. Some of this work has now been published in conference proceedings. The flavour of the project has changed very slightly in the last year owing to the increasing availability of several good quality Chandra HETG and LETG spectra for stars for which we had reduced and analysed ASCA data. The Chandra grating spectra in principle provide a means of calibrating the results from the low resolution ASCA spectra and we have started some work toward that goal. One paper concerning abundance ratios in active stars is appearing shortly in conference proceedings and is being readied for publication in a main-stream astrophysical journal. This paper demonstrates for the first time that abundance anomalies cannot be categorized simply in terms of First Ionization Potential (FIP) or inverse-FIP based effects. Different Ne enhancements are found in different star types but a link between enhancement factors and stellar properties is not obvious. The publication noted as in preparation in an earlier report, finding strong Ne enhancements in active stars, is now published. These results will again be used to "calibrate" low resolution results for which line ratio techniques cannot be employed.

Drake, Jeremy↗

Statistical Analysis of Complexity Generators for Cost Estimation

Predicting the cost of cutting edge new technologies involved with spacecraft hardware can be quite complicated. A new feature of the NASA Air Force Cost Model (NAFCOM), called the Complexity Generator, is being developed to model the complexity factors that drive the cost of space hardware. This parametric approach is also designed to account for the differences in cost, based on factors that are unique to each system and subsystem. The cost driver categories included in this model are weight, inheritance from previous missions, technical complexity, and management factors. This paper explains the Complexity Generator framework, the statistical methods used to select the best model within this framework, and the procedures used to find the region of predictability and the prediction intervals for the cost of a mission.

Rowell, Ginger Holmes↗

Monitoring and Assimilation of MIPAS and SCIAMACHY Ozone Data

Preliminary results are presented from experiments that integrate ozone observations from two ENVISAT-borne instruments with the ozone data assimilation system developed at NASA's Data Assimilation Office (DAO). The data used are ozone total column provided by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) and stratospheric profiles from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument. The DAO's existing system sequentially assimilates the Solar Backscatter Ultraviolet/2 total and partial ozone column data. Incorporation of SCIAMACHY and MIPAS data is done in two stages. First, the observations are monitored. The monitoring consists of computing the differences between Envisat observations and the ozone system forecast, i.e. observed-minus-forecast (O-F) residuals. The O-F residuals are then analyzed using simple statistical methods to examine the spatial distribution of differences, which are large for SCIAMACHY near the terminator. In the second stage, the MIPAS data will be actively assimilated along with the SBW/2 observations; any preliminary results of note will be discussed.

Wargan, K.↗

Research in Computational Astrobiology

We report on several projects in the field of computational astrobiology, which is devoted to advancing our understanding of the origin, evolution and distribution of life in the Universe using theoretical and computational tools. Research projects included modifying existing computer simulation codes to use efficient, multiple time step algorithms, statistical methods for analysis of astrophysical data via optimal partitioning methods, electronic structure calculations on water-nuclei acid complexes, incorporation of structural information into genomic sequence analysis methods and calculations of shock-induced formation of polycylic aromatic hydrocarbon compounds.

Chaban, Galina↗

Facility Monitoring: A Qualitative Theory for Sensor Fusion

Data fusion and sensor management approaches have largely been implemented with centralized and hierarchical architectures. Numerical and statistical methods are the most common data fusion methods found in these systems. Given the proliferation and low cost of processing power, there is now an emphasis on designing distributed and decentralized systems. These systems use analytical/quantitative techniques or qualitative reasoning methods for date fusion.Based on other work by the author, a sensor may be treated as a highly autonomous (decentralized) unit. Each highly autonomous sensor (HAS) is capable of extracting qualitative behaviours from its data. For example, it detects spikes, disturbances, noise levels, off-limit excursions, step changes, drift, and other typical measured trends. In this context, this paper describes a distributed sensor fusion paradigm and theory where each sensor in the system is a HAS. Hence, given the reach qualitative information from each HAS, a paradigm and formal definitions are given so that sensors and processes can reason and make decisions at the qualitative level. This approach to sensor fusion makes it possible the implementation of intuitive (effective) methods to monitor, diagnose, and compensate processes/systems and their sensors. This paradigm facilitates a balanced distribution of intelligence (code and/or hardware) to the sensor level, the process/system level, and a higher controller level. The primary application of interest is in intelligent health management of rocket engine test stands.

Figueroa, Fernando↗