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At least 595 records · Page 33

Quantitative Measures for Software Independent Verification and Validation

As software is maintained or reused, it undergoes an evolution which tends to increase the overall complexity of the code. To understand the effects of this, we brought in statistics experts and leading researchers in software complexity, reliability, and their interrelationships. These experts' project has resulted in our ability to statistically correlate specific code complexity attributes, in orthogonal domains, to errors found over time in the HAL/S flight software which flies in the Space Shuttle. Although only a prototype-tools experiment, the result of this research appears to be extendable to all other NASA software, given appropriate data similar to that logged for the Shuttle onboard software. Our research has demonstrated that a more complete domain coverage can be mathematically demonstrated with the approach we have applied, thereby ensuring full insight into the cause-and-effects relationship between the complexity of a software system and the fault density of that system. By applying the operational profile we can characterize the dynamic effects of software path complexity under this same approach We now have the ability to measure specific attributes which have been statistically demonstrated to correlate to increased error probability, and to know which actions to take, for each complexity domain. Shuttle software verifiers can now monitor the changes in the software complexity, assess the added or decreased risk of software faults in modified code, and determine necessary corrections. The reports, tool documentation, user's guides, and new approach that have resulted from this research effort represent advances in the state of the art of software quality and reliability assurance. Details describing how to apply this technique to other NASA code are contained in this document.

Lee, Alice↗

A Statistical Method for Reducing Sidelobe Clutter for the Ku-Band Precipitation Radar on Board the GPM Core Observatory

A statistical method to reduce the sidelobe clutter of the Ku-band precipitation radar (KuPR) of the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory is described and evaluated using DPR observations. The KuPR sidelobe clutter was much more severe than that of the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM), and it has caused the misidentification of precipitation. The statistical method to reduce sidelobe clutter was constructed by subtracting the estimated sidelobe power, based upon a multiple regression model with explanatory variables of the normalized radar cross section (NRCS) of surface, from the received power of the echo. The saturation of the NRCS at near-nadir angles, resulting from strong surface scattering, was considered in the calculation of the regression coefficients.The method was implemented in the KuPR algorithm and applied to KuPR-observed data. It was found that the received power from sidelobe clutter over the ocean was largely reduced by using the developed method, although some of the received power from the sidelobe clutter still remained. From the statistical results of the evaluations, it was shown that the number of KuPR precipitation events in the clutter region, after the method was applied, was comparable to that in the clutter-free region. This confirms the reasonable performance of the method in removing sidelobe clutter. For further improving the effectiveness of the method, it is necessary to improve the consideration of the NRCS saturation, which will be explored in future work.

Atm/Ocean Structure/ Phenomena; Precipitation; Obs↗

Statistical geometry of a small surface patch in a developed sea

The fractal and marginal fractal regimes in surface geometry are studied. The basic notions of fractal geometry are applied to a small surface patch in a developed sea, corresponding to the equilibrium wave number spectrum. Topothesy, outer and inner boundaries of the fractal range, and a cascade pattern in surface geometry are discussed. Theoretical predictions of whitecap and foam coverage are presented. A fractal decomposition for a surface patch is developed based on the Karhunen-Loeve expansion. The resulting series formalizes the cascade process of constructing realization of a Gaussian random patch. The implications of the research for microwave remote sensing signatures are considered.

Glazman, Roman E.↗

Statistical Model Selection for TID Hardness Assurance

Radiation Hardness Assurance (RHA) methodologies against Total Ionizing Dose (TID) degradation impose rigorous statistical treatments for data from a part's Radiation Lot Acceptance Test (RLAT) and/or its historical performance. However, no similar methods exist for using "similarity" data - that is, data for similar parts fabricated in the same process as the part under qualification. This is despite the greater difficulty and potential risk in interpreting of similarity data. In this work, we develop methods to disentangle part-to-part, lot-to-lot and part-type-to-part-type variation. The methods we develop apply not just for qualification decisions, but also for quality control and detection of process changes and other "out-of-family" behavior. We begin by discussing the data used in ·the study and the challenges of developing a statistic providing a meaningful measure of degradation across multiple part types, each with its own performance specifications. We then develop analysis techniques and apply them to the different data sets.

Ladbury, R.↗

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↗

Nested rain cell contour statistics derived from radar measurements in the mid-Atlantic coast of the United States

During a period spanning more than 5 years, a series of low elevation rain radar measurements encompassing 17 rain days were systematically executed in the mid-Atlantic coast of the United States. Drop size distribution measurements with a nearby disdrometer were also acquired during the same rain days. The drop size data were utilized to convert the radar reflectivity factors to estimated rain rates for the respective rain days of operation. Applying developed algorithms to the radar and disdrometer data, 'core' values of rain intensities and nested families of rain rate isopleths enveloping them were identified and their equi-circle diameters were statistically analyzed.

Goldhirsh, Julius↗

The AutoBayes Program Synthesis System: System Description

AUTOBAYES is a fully automatic program synthesis system for the statistical data analysis domain. Its input is a concise description of a data analysis problem in the form of a statistical model; its output is optimized and fully documented C/C++ code which can be linked dynamically into the Matlab and Octave environments. AUTOBAYES synthesizes code by a schema-guided deductive process. Schemas (i.e., code templates with associated semantic constraints) are applied to the original problem and recursively to emerging subproblems. AUTOBAYES complements this approach by symbolic computation to derive closed-form solutions whenever possible. In this paper, we concentrate on the interaction between the symbolic computations and the deductive synthesis process. A statistical model specifies for each problem variable (i.e., data or parameter) its properties and dependencies in the form of a probability distribution, A typical data analysis task is to estimate the best possible parameter values from the given observations or measurements. The following example models normal-distributed data but takes prior information (e.g., from previous experiments) on the data's mean value and variance into account.

Fischer, Bernd↗

Solar wind latitudinal variations deduced from Mariner 10 interplanetary H /1216 A/ observations

The Mariner 10 H (1216-A) interplanetary observations are examined by using models that consider anisotropies in the solar fluxes. It is verified that the dominant contribution to asymmetric structure in the Mariner 10 H (1216-A) data is a latitudinal variation of the solar-wind flux and of the solar wind velocity, leading to a hydrogen atom lifetime that is latitude dependent. The average lifetime at 1 AU is found to increase from the solar equator to the solar poles by about 25%. This allows interstellar hydrogen to penetrate closer to the solar poles than to the equator. A general analytic model is constructed for evaluating the neutral hydrogen density distribution in interplanetary space. This model takes into account the latitude-dependent ionization rate. When this model is applied to the Mariner 10 H (1216-A) data, it is shown to be capable of matching the observations with a statistical accuracy of 5%. The effect of this latitudinal variation on H (1216-A) sky background maps is to produce a latitudinal shift in the maximum toward the north ecliptic pole.

Witt, N.↗

Synchronization for Optical PPM Signals

Method based on statistical properties of weak pulse-positionmodulated (PPM) signal enables synchronization of receiver clock with received-signal time base. Method applies to weak optical M-ary PPM signals, for which there is only one pulse of length Tp transmitted during one of timeslots of length T in each successive interval of M timeslots. Method requires small dead time, Td, at beginning and end of each timeslot, during which pulse amplitude is zero.

Vilnrotter, V. A.↗

Signal Detection Techniques for Diagnostic Monitoring of Space Shuttle Main Engine Turbomachinery

An investigation to develop, implement, and evaluate signal analysis techniques for the detection and classification of incipient mechanical failures in turbomachinery is reviewed. A brief description of the Space Shuttle Main Engine (SSME) test/measurement program is presented. Signal analysis techniques available to describe dynamic measurement characteristics are reviewed. Time domain and spectral methods are described, and statistical classification in terms of moments is discussed. Several of these waveform analysis techniques have been implemented on a computer and applied to dynamc signals. A laboratory evaluation of the methods with respect to signal detection capability is described. A unique coherence function (the hyper-coherence) was developed through the course of this investigation, which appears promising as a diagnostic tool. This technique and several other non-linear methods of signal analysis are presented and illustrated by application. Software for application of these techniques has been installed on the signal processing system at the NASA/MSFC Systems Dynamics Laboratory.

Coffin, Thomas↗

Accurate low-cost methods for performance evaluation of cache memory systems

Methods of simulation based on statistical techniques are proposed to decrease the need for large trace measurements and for predicting true program behavior. Sampling techniques are applied while the address trace is collected from a workload. This drastically reduces the space and time needed to collect the trace. Simulation techniques are developed to use the sampled data not only to predict the mean miss rate of the cache, but also to provide an empirical estimate of its actual distribution. Finally, a concept of primed cache is introduced to simulate large caches by the sampling-based method.

Laha, Subhasis↗

Probing the tides in interacting galaxy pairs

Detailed spectroscopic and imaging observations of colliding elliptical galaxies revealed unmistakable diagnostic signatures of the tidal interactions. It is possible to compare both the distorted luminosity distributions and the disturbed internal rotation profiles with numerical simulations in order to model the strength of the tidal gravitational field acting within a given pair of galaxies. Using the best-fit numerical model, one can then measure directly the mass of a specific interacting binary system. This technique applies to individual pairs and therefore complements the classical methods of measuring the masses of galaxy pairs in well-defined statistical samples. The 'personalized' modeling of galaxy pairs also permits the derivation of each binary's orbit, spatial orientation, and interaction timescale. Similarly, one can probe the tides in less-detailed observations of disturbed galaxies in order to estimate some of the physical parameters for larger samples of interacting galaxy pairs. These parameters are useful inputs to the more universal problems of (1) the galaxy merger rate, (2) the strength and duration of the driving forces behind tidally stimulated phenomena (e.g., starbursts and maybe quasi steller objects), and (3) the identification of long-lived signatures of interaction/merger events.

Borne, Kirk D.↗

Inherent Conservatism in Deterministic Quasi-Static Structural Analysis

The cause of the long-suspected excessive conservatism in the prevailing structural deterministic safety factor has been identified as an inherent violation of the error propagation laws when reducing statistical data to deterministic values and then combining them algebraically through successive structural computational processes. These errors are restricted to the applied stress computations, and because mean and variations of the tolerance limit format are added, the errors are positive, serially cumulative, and excessively conservative. Reliability methods circumvent these errors and provide more efficient and uniform safe structures. The document is a tutorial on the deficiencies and nature of the current safety factor and of its improvement and transition to absolute reliability.

Verderaime, V.↗

Disintegration of Dust Aggregates in Interstellar Shocks and the Lifetime of Dust Grains in the ISM

Interstellar grains are destroyed by shock waves moving through the ISM. In fact, the destruction of grains may be so effective that it is difficult to explain the observed abundance of dust in the ISM as a steady state between input of grains from stellar sources and destruction of grains in shocks. This is especially a problem for the larger grains. Therefore, the dust grains must be protected in some way. Jones et al. have already considered coatings and the increased post-shock drag effects for low density grains. In molecular clouds and dense clouds, coagulation of grains is an important process, and the largest interstellar grains may indeed be aggregates of smaller grains rather than homogeneous particles. This may provide a means to protect the larger grains, in that, in moderate velocity grain-grain collisions in a shock the aggregates may disintegrate rather than be vaporized. The released small particles are more resilient to shock destruction (except in fast shocks) and may reform larger grains later, recovering the observed size distribution. We have developed a model for the binding forces in grain aggregates and apply this model to the collisions between an aggregate and fast small grains. We discuss the results in the light of statistical collision probabilities and grain life times.

Dominik, C.↗

First Year Wilkinson Microwave Anisotropy Probe(WMAP) Observations: Data Processing Methods and Systematic Errors Limits

We describe the calibration and data processing methods used to generate full-sky maps of the cosmic microwave background (CMB) from the first year of Wilkinson Microwave Anisotropy Probe (WMAP) observations. Detailed limits on residual systematic errors are assigned based largely on analyses of the flight data supplemented, where necessary, with results from ground tests. The data are calibrated in flight using the dipole modulation of the CMB due to the observatory's motion around the Sun. This constitutes a full-beam calibration source. An iterative algorithm simultaneously fits the time-ordered data to obtain calibration parameters and pixelized sky map temperatures. The noise properties are determined by analyzing the time-ordered data with this sky signal estimate subtracted. Based on this, we apply a pre-whitening filter to the time-ordered data to remove a low level of l/f noise. We infer and correct for a small (approx. 1 %) transmission imbalance between the two sky inputs to each differential radiometer, and we subtract a small sidelobe correction from the 23 GHz (K band) map prior to further analysis. No other systematic error corrections are applied to the data. Calibration and baseline artifacts, including the response to environmental perturbations, are negligible. Systematic uncertainties are comparable to statistical uncertainties in the characterization of the beam response. Both are accounted for in the covariance matrix of the window function and are propagated to uncertainties in the final power spectrum. We characterize the combined upper limits to residual systematic uncertainties through the pixel covariance matrix.

Hinshaw, G.↗

POD Model Reconstruction for Gray-Box Fault Detection

Proper orthogonal decomposition (POD) is the mathematical basis of a method of constructing low-order mathematical models for the "gray-box" fault-detection algorithm that is a component of a diagnostic system known as beacon-based exception analysis for multi-missions (BEAM). POD has been successfully applied in reducing computational complexity by generating simple models that can be used for control and simulation for complex systems such as fluid flows. In the present application to BEAM, POD brings the same benefits to automated diagnosis. BEAM is a method of real-time or offline, automated diagnosis of a complex dynamic system.The gray-box approach makes it possible to utilize incomplete or approximate knowledge of the dynamics of the system that one seeks to diagnose. In the gray-box approach, a deterministic model of the system is used to filter a time series of system sensor data to remove the deterministic components of the time series from further examination. What is left after the filtering operation is a time series of residual quantities that represent the unknown (or at least unmodeled) aspects of the behavior of the system. Stochastic modeling techniques are then applied to the residual time series. The procedure for detecting abnormal behavior of the system then becomes one of looking for statistical differences between the residual time series and the predictions of the stochastic model.

Park, Han↗

An Analysis of Peak Wind Speed Data from Collocated Mechanical and Ultrasonic Anemometers

This study focuses on a comparison of peak wind speeds reported by mechanical and ultrasonic anemometers at Cape Canaveral Air Force Station and Kennedy Space Center (CCAFS/KSC) on the east central coast of Florida and Vandenberg Air Force Base (VAFB) on the central coast of California. The legacy mechanical wind instruments on CCAFS/KSC and VAFB weather towers are being changed from propeller-and-vane (CCAFS/KSC) and cup-and-vane (VAFB) sensors to ultrasonic sensors under the Range Standardization and Automation (RSA) program. The wind tower networks on KSC/CCAFS and VAFB have 41 and 27 towers, respectively. Launch Weather Officers, forecasters, and Range Safety analysts at both locations need to understand the performance of the new wind sensors for a myriad of reasons that include weather warnings, watches, advisories, special ground processing operations, launch pad exposure forecasts, user Launch Commit Criteria (LCC) forecasts and evaluations, and toxic dispersion support. The Legacy sensors measure wind speed and direction mechanically. The ultrasonic RSA sensors have no moving parts. Ultrasonic sensors were originally developed to measure very light winds (Lewis and Dover 2004). The technology has evolved and now ultrasonic sensors provide reliable wind data over a broad range of wind speeds. However, because ultrasonic sensors respond more quickly than mechanical sensors to rapid fluctuations in speed, characteristic of gusty wind conditions, comparisons of data from the two sensor types have shown differences in the statistics of peak wind speeds (Lewis and Dover 2004). The 45th Weather Squadron (45 WS) and the 30 WS requested the Applied Meteorology Unit (AMU) to compare data from RSA and Legacy sensors to determine if there are significant differences in peak wind speed information from the two systems.

Short, David A.↗

Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors

We estimated global fine particulate matter (PM(sub 2.5)) concentrations using information from satellite-, simulation- and monitor-based sources by applying a Geographically Weighted Regression (GWR) to global geophysically-based satellite-derived PM(sub 2.5) estimates. Aerosol optical depth from multiple satellite products (MISR, MODIS Dark Target, MODIS and SeaWiFS Deep Blue, and MODIS MAIAC) was combined with simulation (GEOS-Chem) based upon their relative uncertainties as determined using ground-based sun photometer (AERONET) observations for 1998−2014. The GWR predictors included simulated aerosol composition and land use information. The resultant PM(sub 2.5) estimates were highly consistent (R(sup 2) equals 0.81) with out-of-sample cross-validated PM(sub 2.5) concentrations from monitors. The global population-weighted annual average PM(sub 2.5) concentrations were 3-fold higher than the 10 micrograms per cubic meter WHO guideline, driven by exposures in Asian and African regions. Estimates in regions with high contributions from mineral dust were associated with higher uncertainty, resulting from both sparse ground-based monitoring, and challenging conditions for retrieval and simulation. This approach demonstrates that the addition of even sparse ground-based measurements to more globally continuous PM(sub 2.5) data sources can yield valuable improvements to PM(sub 2.5) characterization on a global scale.

aerosols↗