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At least 1,063 records · Page 59

Determination of model structure and parameters of an airplane from pre- and post-stall flight data

A procedure for airplane model structure determination from flight data based on modified stepwise regression (MSR), several decision criteria and postulated aerodynamic model equations is presented. The MSR is constructed to force a linear model for the aerodynamic coefficient first, then select significant nonlinear terms and reject nonsignificant terms from the model. In addition to the statistical criteria in the stepwise regression, the prediction sum of squares (PRESS) criterion and analysis of residuals are examined for the selection of an adequate model. The procedure is used in examples with simulated and real flight data. It is shown that the MSR performs better than the ordinary stepwise regression and that the technique can be also applied to the large amplitude maneuvers.

Klein, V.↗

Simplified model evaluation of cooling rates for glass-containing lunar compositions

The simplified model of glass formation and the development of partial crystallinity in cooled bodies has been applied to lunar compositions 10060, 15028, 15086, 15101, 15286, 15301, 15498, 15499, 60255, 65016, 77017, Apollo 15 green glass and LUNA 24 highland basalt. The critical cooling rates for glass formation predicted by the simplified model are found to be in good agreement (to within an order of magnitude) with those predicted by the exact treatment of crystallization statistics. These predicted critical cooling rates are in even better agreement (a factor of 2) with measured values of the rates required to form glasses of the materials.

Uhlmann, D. R.↗

The velocity structure and turbulence at the center of the Orion Nebula

Using the Coude Feed System of the Kitt Peak National Observatory at its highest possible dispersion and a CCD detector with wide dynamic range it was possible to examine in detail the radial and turbulent velocities of the Orion Nebula at the seeing limit. For the first time, multiple components of the spectral lines were resolved and the Gaussian profiles fit to them. Using four different observing runs, two circular areas 2 minutes in diameter were observed, the first centered on the theta sup 1 Orionis and the second centered on theta sup 2 Orionis. The velocity resolution of 1 km/s combined with the angular resolution of 2 seconds allowed observation in detail at line splitting as well as the location and measurement of high internal motions, about -50 km/s with respect to the bulk of ionized matter. Because over 900 different positions were measured, modern statistical techniques were used for the analysis of turbulence, so that the dispersion relation and the structure function could be calculated and compared with predictions of the Kolmogorov theory. The random motions showed correlation with spatial separation, as expected for turbulence; but comparison with predictions of the classical theory for nebular turbulence showed poor agreement. If Kolmogorov theory applies, then the energy must be input at many scales.

Castaneda, Hector O.↗

Practical Aspects of Multiple-Input Design for Aircraft System Identification Flight Tests

Practical aspects of multiple-input design methods for aircraft system identification flight tests are discussed. The orthogonal optimized multisine multiple-input design technique is explained and demonstrated, along with useful variations. Practical implementation and application issues associated with applying orthogonal optimized multisine inputs in flight are explained, and solutions are demonstrated using flight data from full-scale and subscale aircraft, as well as simulated flight data from an F-16 nonlinear simulation. Topics include truncated and extended excitation inputs, variations for control effectors with limited movement capabilities, aircraft dynamic response to excitation inputs, pilot implementation, statistical uncertainty quantification, multiple-input efficiency and effectiveness, flight testing with active feedback control, frequency-response estimation, control actuator modeling, and control interaction effects. Examples demonstrate that the orthogonal optimized multisine input design method is a practical, versatile, and effective approach for designing multiple excitation inputs for aircraft system identification flight tests.

Multiple-Input Design↗

Applied regional monitoring of the vernal advancement and retrogradation (green wave effect) of natural vegetation in the Great Plains corridor

The author has identified the following significant results. Rangelands in southwest Texas were used to establish threshold values and limitations on measuring herbaceous biomass under typical arid and semi-arid range conditions. Previous regression relationships established between ND6 and green biomass for two different ecosystems were similar. The west Texas data set for brush-free sites was too small to be statistically conclusive. It appears that a line with a third (and steeper) slope would be best for the west Texas data, and that line would intersect the other two. Results show that similar relationships exist between ND6 and green biomass under low brush canopy cover conditions, but local variations require a calibration to determine the best fit for an ecosystem. The brush canopy has a detrimental effect on the ND6 vs. herbaceous green biomass relationship.

Harlan, J. C.↗

NRLMSISE-00 Empirical Model of the Atmosphere: Statistical Comparisons and Scientific Issues

The new NRLMSISE-00 model and the associated NRLMSIS database now include the following data: (1) total mass density from satellite accelerometers and from orbit determination, including the Jacchia and Barlier data; (2) temperature from incoherent scatter radar, and; (3) molecular oxygen number density, [O2], from solar ultraviolet occultation aboard the Solar Maximum Mission (SMM). A new component, 'anomalous oxygen,' allows for appreciable O(+) and hot atomic oxygen contributions to the total mass density at high altitudes and applies primarily to drag estimation above 500 km. Extensive tables compare our entire database to the NRLMSISE-00, MSISE-90, and Jacchia-70 models for different altitude bands and levels of geomagnetic activity. We also investigate scientific issues related to the new data sets in the NRLMSIS database. Especially noteworthy is the solar activity dependence of the Jacchia data, with which we investigate a large O(+) contribution to the total mass density under the combination of summer, low solar activity, high latitudes, and high altitudes. Under these conditions, except at very low solar activity, the Jacchia data and the Jacchia-70 model indeed show a significantly higher total mass density than does MSISE-90. However, under the corresponding winter conditions, the MSIS-class models represent a noticeable improvement relative to Jacchia-70 over a wide range of F(sub 10.7). Considering the two regimes together, NRLMSISE-00 achieves an improvement over both MSISE-90 and Jacchia-70 by incorporating advantages of each.

Aikin, A. C.↗

Multivariate Statistical Analysis Software Technologies for Astrophysical Research Involving Large Data Bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complex database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects of the SKICAT system, and of some of the scientific results achieved to date. We also developed a user-friendly package for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications and has produced real, published results.

Djorgovski, S. G.↗

Application of statistical distribution theory to launch-on-time for space construction logistic support

The ability to launch-on-time and to send payloads into space has progressed dramatically since the days of the earliest missile and space programs. Causes for delay during launch, i.e., unplanned 'holds', are attributable to several sources: weather, range activities, vehicle conditions, human performance, etc. Recent developments in space program, particularly the need for highly reliable logistic support of space construction and the subsequent planned operation of space stations, large unmanned space structures, lunar and Mars bases, and the necessity of providing 'guaranteed' commercial launches have placed increased emphasis on understanding and mastering every aspect of launch vehicle operations. The Center of Space Construction has acquired historical launch vehicle data and is applying these data to the analysis of space launch vehicle logistic support of space construction. This analysis will include development of a better understanding of launch-on-time capability and simulation of required support systems for vehicle assembly and launch which are necessary to support national space program construction schedules. In this paper, the author presents actual launch data on unscheduled 'hold' distributions of various launch vehicles. The data have been supplied by industrial associate companies of the Center for Space Construction. The paper seeks to determine suitable probability models which describe these historical data and that can be used for several purposes such as: inputs to broader simulations of launch vehicle logistic space construction support processes and the determination of which launch operations sources cause the majority of the unscheduled 'holds', and hence to suggest changes which might improve launch-on-time. In particular, the paper investigates the ability of a compound distribution probability model to fit actual data, versus alternative models, and recommends the most productive avenues for future statistical work.

Morgenthaler, George W.↗

Determination of airplane model structure from flight data by using modified stepwise regression

The linear and stepwise regressions are briefly introduced, then the problem of determining airplane model structure is addressed. The MSR was constructed to force a linear model for the aerodynamic coefficient first, then add significant nonlinear terms and delete nonsignificant terms from the model. In addition to the statistical criteria in the stepwise regression, the prediction sum of squares (PRESS) criterion and the analysis of residuals were examined for the selection of an adequate model. The procedure is used in examples with simulated and real flight data. It is shown that the MSR performs better than the ordinary stepwise regression and that the technique can also be applied to the large amplitude maneuvers.

Klein, V.↗

Defect-phase-dynamics approach to statistical domain-growth problem of clock models

The growth of statistical domains in quenched Ising-like p-state clock models with p = 3 or more is investigated theoretically, reformulating the analysis of Ohta et al. (1982) in terms of a phase variable and studying the dynamics of defects introduced into the phase field when the phase variable becomes multivalued. The resulting defect/phase domain-growth equation is applied to the interpretation of Monte Carlo simulations in two dimensions (Kaski and Gunton, 1983; Grest and Srolovitz, 1984), and problems encountered in the analysis of related Potts models are discussed. In the two-dimensional case, the problem is essentially that of a purely dissipative Coulomb gas, with a sq rt t growth law complicated by vertex-pinning effects at small t.

Kawasaki, K.↗

A synthetic seismicity model for the Middle America Trench

A novel iterative technique, based on the concept of fault segmentation and computed using 2D static dislocation theory, for building models of seismicity and fault interaction which are physically acceptable and geometrically and kinematically correct, is presented. The technique is applied in two steps to seismicity observed at the Middle America Trench. The first constructs generic models which randomly draw segment strengths and lengths from a 2D probability distribution. The second constructs predictive models in which segment lengths and strengths are adjusted to mimic the actual geography and timing of large historical earthquakes. Both types of models reproduce the statistics of seismicity over five units of magnitude and duplicate other aspects including foreshock and aftershock sequences, migration of foci, and the capacity to produce both characteristic and noncharacteristic earthquakes. Over a period of about 150 yr the complex interaction of fault segments and the nonlinear failure conditions conspire to transform an apparently deterministic model into a chaotic one.

Ward, Steven N.↗

Stochastic performance modeling and evaluation of obstacle detectability with imaging range sensors

Statistical modeling and evaluation of the performance of obstacle detection systems for Unmanned Ground Vehicles (UGVs) is essential for the design, evaluation, and comparison of sensor systems. In this report, we address this issue for imaging range sensors by dividing the evaluation problem into two levels: quality of the range data itself and quality of the obstacle detection algorithms applied to the range data. We review existing models of the quality of range data from stereo vision and AM-CW LADAR, then use these to derive a new model for the quality of a simple obstacle detection algorithm. This model predicts the probability of detecting obstacles and the probability of false alarms, as a function of the size and distance of the obstacle, the resolution of the sensor, and the level of noise in the range data. We evaluate these models experimentally using range data from stereo image pairs of a gravel road with known obstacles at several distances. The results show that the approach is a promising tool for predicting and evaluating the performance of obstacle detection with imaging range sensors.

Matthies, Larry↗

Using Clustering to Establish Climate Regimes from PCM Output

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Oglesby, Robert↗

Renormalization Group Tutorial

Complex physical systems sometimes have statistical behavior characterized by power- law dependence on the parameters of the system and spatial variability with no particular characteristic scale as the parameters approach critical values. The renormalization group (RG) approach was developed in the fields of statistical mechanics and quantum field theory to derive quantitative predictions of such behavior in cases where conventional methods of analysis fail. Techniques based on these ideas have since been extended to treat problems in many different fields, and in particular, the behavior of turbulent fluids. This lecture will describe a relatively simple but nontrivial example of the RG approach applied to the diffusion of photons out of a stellar medium when the photons have wavelengths near that of an emission line of atoms in the medium.

Bell, Thomas L.↗

Availability of High Quality TRMM Ground Validation Data from Kwajalein, RMI: A Practical Application of the Relative Calibration Adjustment Technique

Since the Tropical Rainfall Measuring Mission (TRMM) satellite launch in November 1997, the TRMM Satellite Validation Office (TSVO) at NASA Goddard Space Flight Center (GSFC) has been performing quality control and estimating rainfall from the KPOL S-band radar at Kwajalein, Republic of the Marshall Islands. Over this period, KPOL has incurred many episodes of calibration and antenna pointing angle uncertainty. To address these issues, the TSVO has applied the Relative Calibration Adjustment (RCA) technique to eight years of KPOL radar data to produce Ground Validation (GV) Version 7 products. This application has significantly improved stability in KPOL reflectivity distributions needed for Probability Matching Method (PMM) rain rate estimation and for comparisons to the TRMM Precipitation Radar (PR). In years with significant calibration and angle corrections, the statistical improvement in PMM distributions is dramatic. The intent of this paper is to show improved stability in corrected KPOL reflectivity distributions by using the PR as a stable reference. Inter-month fluctuations in mean reflectivity differences between the PR and corrected KPOL are on the order of 1-2 dB, and inter-year mean reflectivity differences fluctuate by approximately 1 dB. This represents a marked improvement in stability with confidence comparable to the established calibration and uncertainty boundaries of the PR. The practical application of the RCA method has salvaged eight years of radar data that would have otherwise been unusable, and has made possible a high-quality database of tropical ocean-based reflectivity measurements and precipitation estimates for the research community.

Marks, David A.↗

Recommendations on the Use of Commercial-Off-The-Shelf (COTS) Electrical, Electronic, and Electromechanical (EEE) Parts for NASA Missions - Phase II

This assessment had two Phases. Phase I captured NASA Centers’ current practices for commercial-off-the-shelf (COTS) Electrical, Electronic, and Electromechanical (EEE) parts 1 used in spaceflight systems and ground support equipment (available at https://ntrs.nasa.gov/citations/20205011579) [ref. 1]. The Phase II report provides guidance for selecting and using COTS parts in NASA missions. The approaches proposed in this report differ from current agency practices. This top-level executive summary touches on these new approaches for using COTS parts but does not provide the detailed information that is critical in understanding the rationale behind these new approaches. Readers will need to read the entire report to gain full understanding and effectively use the recommendations herein. NASA’s historical approach to selecting and applying parts has been to define certain parts, primarily specific classes of military specification (MIL-SPEC) parts, as “standard”, leaving all others, including COTS parts, as nonstandard. Standard parts typically are used without further testing (“use-as-is”). Nonstandard parts are subjected to initial screening and subsequent lot acceptance testing of representative samples from each procured lot per MIL-SPEC or similar requirements. Decades later, top-tier commercial part manufacturers have evolved significant manufacturing, statistical control, and technological improvements that can now provide parts as reliable or more reliable than MIL-SPEC parts, when used within their datasheet limits. Concurrently, the space science and exploration community’s needs demand technological advances unavailable with MIL-SPEC parts. This ongoing change necessitates using COTS parts for space missions. Properly selected COTS parts in appropriate applications can offer performance and supply availability advantages compared to MIL-SPEC parts. Their utility and demonstrated reliability result from large volumes and automated production and testing processes. However, careful review and a thorough understanding of their specifications (i.e., datasheet limitations) is needed, and verifying that manufacturer specifications and reliability meet space hardware application needs are necessary. This report recommends MIL-SPEC screening and non-radiation-related lot acceptance testing be reduced or eliminated in cases where evidence of sufficient quality and reliability exists for COTS parts. The extent of NASA's insight into COTS manufacturers and the amount and nature of the needed evidence will differ by mission and will likely be driven by a mission's resources and associated risk posture. To facilitate this goal, two new terminologies have been defined and described: “Industry Leading Parts Manufacturer (ILPM)” and “Established COTS parts.” An ILPM is a COTS manufacturer that produces high quality and reliable parts. Some parts produced by ILPMs, defined as Established COTS parts, do not need any additional MIL-SPEC or NASA screening and lot acceptance testing to be used in space applications. This report provides guidance for selecting, procuring, and applying COTS parts and for performing part-, board-, and system-level COTS parts verification. The recommendation to select Established COTS parts from ILPMs will assure those COTS parts will have comparable quality to corresponding MIL-SPEC parts. Selecting, applying, and verifying Established COTS parts from ILPMs requires a holistic team approach, engaging parts engineers, circuit designers, quality, reliability, and systems engineers, procurement specialists, radiation specialists, avionics leads, and program/project managers. A mission-specific approach tailored to a project’s Mission, Environment, Applications and Lifetime (MEAL) [ref. 2] requirements should be developed and approved by program/project managers. Any associated risks should be clearly identified, quantified, mitigated, and/or accepted. Different approaches are recommended according to program/project Risk Classes A, B, C, and D [ref. 3] and human-rated missions [ref. 4]: 1. Recommend Classes A and B and human-rated missions consider a “MIL-SPEC parts- based design” approach. ”MIL-SPEC parts-based design” approach is one in which most parts are MIL-SPEC parts and Established COTS parts from ILPMs are used only when an equivalent MIL-SPEC part does not meet functional or size, weight, and power (SWaP) or performance requirements, or is not available. 2. Recommend Classes D and Sub-D missions consider a “System of COTS” approach. “System of COTS” approach is one which most parts are Established COTS parts from ILPMs. 3. Recommend Class C missions determine which approach is the best for their projects; that is, use either a “MIL-SPEC parts-based design” approach, “System of COTS” approach, or a combined approach utilizing elements of both. This report intends to provide guidance in using COTS parts for NASA missions with risk classifications of A through D and human-rated missions; but it does not address the costs of using COTS parts. Costs of using COTS parts in different NASA mission classes can vary significantly even if the same parts are used in different risk postures, due to differing verification levels needed. The guidance does not distinguish between critical or non-critical systems, and a given project will need to apply the appropriate guidance based on their risk posture. The intended audience of this report are NASA personnel and commercial practitioners who support NASA’s spaceflight missions, including spaceflight program or project managers, parts engineers, parts manufacturers, radiation engineers, avionics engineers, system engineers, circuit design engineers, reliability engineers, safety and mission assurance (SMA) personnel, and parts procurement specialists. The NEPP Program will perform a pathfinder study to explore implementing the guidance in this NESC report. An ILPM verification process is not the same as conventional vendor qualification processes performed according to military standards and specifications. This NESC report intends to provide guidance in utilizing available parts data from ILPM manufacturers for parts assurance assessments needed for NASA missions. The report also captured the current practices from DoD and Federal Aviation Administration (FAA) in Section 10. Note each DoD and FAA report was provided by the corresponding agencies regarding their practices, which are independent from the NESC recommendations in the report.

Commercial-Off-The-Shelf↗

Physics through the 1990s: Elementary-particle physics

The volume begins with a non-mathematical discussion of the motivation behind, and basic ideas of, elementary-particle physics theory and experiment. The progress over the past two decades with the quark model and unification of the electromagnetic and weak interactions is reviewed. Existing theoretical problems in the field, such as the origin of mass and the unification of the fundamental forces, are detailed, along with experimental programs to test the new theories. Accelerators, instrumentation, and detectors are described for both current and future facilities. Interactions with other areas of both theoretical and applied physics are presented. The sociology of the field is examined regarding the education of graduate students, the organization necessary in large-scale experiments, and the decision-making process involved in high-cost experiments. Finally, conclusions and recommendations for maintaining US excellence in theory and experiment are given. Appendices list both current and planned accelerators, and present statistical data on the US elementary-particle physics program. A glossary is included.

Source record↗

Extracting galactic structure parameters from multivariated density estimation

Multivariate statistical analysis, including includes cluster analysis (unsupervised classification), discriminant analysis (supervised classification) and principle component analysis (dimensionlity reduction method), and nonparameter density estimation have been successfully used to search for meaningful associations in the 5-dimensional space of observables between observed points and the sets of simulated points generated from a synthetic approach of galaxy modelling. These methodologies can be applied as the new tools to obtain information about hidden structure otherwise unrecognizable, and place important constraints on the space distribution of various stellar populations in the Milky Way. In this paper, we concentrate on illustrating how to use nonparameter density estimation to substitute for the true densities in both of the simulating sample and real sample in the five-dimensional space. In order to fit model predicted densities to reality, we derive a set of equations which include n lines (where n is the total number of observed points) and m (where m: the numbers of predefined groups) unknown parameters. A least-square estimation will allow us to determine the density law of different groups and components in the Galaxy. The output from our software, which can be used in many research fields, will also give out the systematic error between the model and the observation by a Bayes rule.

Chen, B.↗