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At least 307 records · Page 17

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NASA NTRS1987

Mercurian crater-filling classes constrain the emplacement process of the intercrater plains material

The multivariate method for statistical analysis of crater-filling classes, as presently applied to craters of more than 10-km diameter on Mercury, is noted to be superior to current techniques due to the obviation of any amalgamation of data from regions with different histories in order to arrive at the pertinent counting statistics. In this application to the Mercury intercrater plains, the process responsible for emplacement is constrained to be one that leaves the crater class distribution unaltered from that observed on the densely cratered terrain. The analysis explicitly eliminates the viability of the pulse emplacement of volcanics or basin ejecta.

Woronow, Alex↗

NASA NTRS1979

Electromagnetic noise and radio wave propagation below 100 kHz in the Jovian atmosphere. I - The equatorial region

The Galileo satellite program includes the delivery of an entry probe to the Jovian equatorial atmosphere in mid-1985. Optical and RF sensors for a lightning detection system are included as a part of the probe experimental payload. In this paper, calculations of the RF wave propagation and reflection characteristics of the equatorial Jovian atmosphere and ionosphere for frequencies less than 100 kHz are presented. It is shown that wave propagation is limited to line-of-sight and one-hop from the ionosphere. Results are also presented of a statistical treatment of the RF wave power densities for the case of a finite number of events and for the case of a uniformly distributed source. The results can be applied to specific RF experiment configurations concerned with establishing the statistical characteristics of Jovian lightning.

Rinnert, K.↗

NASA NTRS2014

MARGInS: Model-Based Analysis of Realizable Goals in Systems

Under NASAs Constellation effort, the Exploration Technology Development Program funded research toward a system validation capability that applied machine learning and test-case generation techniques to the analysis of black-box system behavior. The behavior analysis capability scaled to spaces of hundreds of input parameters and tens of thousands of test cases. Aerospace systems at the vehicle level, especially those systems which contain some level of autonomy, are best described by hybrid and non-linear mathematics. Even simplified models of such systems need parameter dimensionalities in the hundreds or thousands of parameters in order to capture sufficient fidelity. The System Safety Assessments (such as those described in the SAE ARP 4761A Safety Assessment Process guidelines) for these systems are prone to errorinteractions between the vehicles subsystems are complex, and can display emergent behaviors. NASA captured this new analysis in the Model-based Analysis of Realizable Goals in Systems (MARGInS) tool and applied it to the Pad Abort 1 (PA-1) simulation as part of the independent validation and verification cycle before the PA-1 flight test in May of 2010. MARGInS evaluated the adherence of the high-fidelity simulation to its requirements, and deter- mined the margins to failure from the expected nominal input conditions. Following the PA-1 test, the capabilities within the MARGInS framework have been extended with sophisticated statistical and white-box test case generation techniques and applied to other NASA missions. The frame- work now includes a critical factors analysis that was applied to NASAs Orion simulation and design. NASAs Aeronautics Research Mission Directorate (ARMD) leveraged the existing MARGInS framework for work on aviation safety for civil transport vehicles and for research on autonomy issues. The NASA ARMD effort created a time series output prediction capability that has been used to characterize trajectories for a plane with an adaptive control system, and a safety boundary detection capability that has been applied to an air traffic control concept of operation for the Federal Aviation Administration. The statistical and machine- learning based techniques within MARGInS have been successfully combined with concolic execution to improve the coverage of a critical unit by driving system-level inputs. The use case driving the concolic execution and MARGInS integration was inspired by the Air France 447 disaster in which the loss of a critical functionality (the airspeed calculation from the pitot tubes) led to loss of the entire plane with the people aboard. To illustrate capabilities and limitations, we will highlight the analyses for the applications listed above. We will then discuss the future plans for MARGInS and its interfaces with other tools.

Validation↗

NASA NTRS1991

Maximum entropy method applied to deblurring images on a MasPar MP-1 computer

A statistical inference method based on the principle of maximum entropy is developed for the purpose of enhancing and restoring satellite images. The proposed maximum entropy image restoration method is shown to overcome the difficulties associated with image restoration and provide the smoothest and most appropriate solution consistent with the measured data. An implementation of the method on the MP-1 computer is described, and results of tests on simulated data are presented.

Bonavito, N. L.↗

NASA NTRS1973

Atmospheric attenuation relative to earth-viewing orbital sensors

Earth viewing space missions offer exciting new possibilities in several earth resources disciplines - geography, hydrology, agriculture, geology, and oceanography, to name a few. A most useful tool in planning experiments and applying space technology to earth observation is a statistical description of atmospheric parameters. Four dimensional atmospheric models and a world wide cloud model are used to produce atmospheric attenuation models to predict degradation effects for all classes of sensors for application to earth sensing experiments from spaceborne platforms. To insure maximum utility and application of these products, the development of an interaction model of microwave energy and atmospheric variables provides a complete description of the effects of atmospheric moisture upon microwaves.

Brown, S. C.↗

NASA NTRS1974

An analysis of pilot error-related aircraft accidents

A multidisciplinary team approach to pilot error-related U.S. air carrier jet aircraft accident investigation records successfully reclaimed hidden human error information not shown in statistical studies. New analytic techniques were developed and applied to the data to discover and identify multiple elements of commonality and shared characteristics within this group of accidents. Three techniques of analysis were used: Critical element analysis, which demonstrated the importance of a subjective qualitative approach to raw accident data and surfaced information heretofore unavailable. Cluster analysis, which was an exploratory research tool that will lead to increased understanding and improved organization of facts, the discovery of new meaning in large data sets, and the generation of explanatory hypotheses. Pattern recognition, by which accidents can be categorized by pattern conformity after critical element identification by cluster analysis.

Kowalsky, N. B.↗

NASA NTRS1965

A Field-Effect Transistor (FET) model for ASAP

The derivation of the circuitry of a field effect transistor (FET) model, the procedure for adapting the model to automated statistical analysis program (ASAP), and the results of applying ASAP on this model are described.

Ming, L.↗

NASA NTRS1977

Life-test methodology for mechanical components

System is based on examining and testing each part of item under evaluation to determine whether aging processes, wear, or other inherent failure modes are likely to limit life to less than that required. Procedure may be applied to many long-life devices where statistical reliability analysis would be impractical.

Dufrane, K. F.↗

NASA NTRS1977

Multivariate-normality goodness-of-fit tests

Computer program applies chi-square Pearson test to multivariate statistics for application in any field in which data of two or more variables (dimensions) are sampled for statistical purposes. Program handles dimensions two through five, with up to thousand data sets.

Falls, L. W.↗

NASA NTRS1982

Program for narrow-band analysis of aircraft flyover noise using ensemble averaging techniques

A package of computer programs was developed for analyzing acoustic data from an aircraft flyover. The package assumes the aircraft is flying at constant altitude and constant velocity in a fixed attitude over a linear array of ground microphones. Aircraft position is provided by radar and an option exists for including the effects of the aircraft's rigid-body attitude relative to the flight path. Time synchronization between radar and acoustic recording stations permits ensemble averaging techniques to be applied to the acoustic data thereby increasing the statistical accuracy of the acoustic results. Measured layered meteorological data obtained during the flyovers are used to compute propagation effects through the atmosphere. Final results are narrow-band spectra and directivities corrected for the flight environment to an equivalent static condition at a specified radius.

Gridley, D.↗

NASA NTRS1983

Procedure for generating ground wind environments for Shuttle liftoff studies

Ground-wind environments for Monte Carlo simulations of Space Shuttle liftoff at KSC are developed. Input parameters include randomly selected 18.3-m-altitude peak wind speed (from which mean wind profile and turbulence intensity are calculated), randomly selected mean wind direction, and longitudinal and lateral turbulence components obtained from the Shuttle-simulation turbulence tapes (SSTT: Tatom et al., 1982). The steps in the simulation of turbulence time histories and horizontal wind fields are listed. It is found that separate statistical analysis of each hour-season pair, applying data on the time fraction of occurrence of peak winds and wind directions at KSC, will be necessary to interpret simulation results consistently.

Fichtl, G. H.↗

NASA NTRS1984

Identifying environmental features for land management decisions

Multivariate statistical analysis and imaging processing techniques are being applied to the study of arid/semiarid environments, with emphasis on desertification. Field level indicators of land-soil biota degradation are being sifted out with staging up to the low aircraft reconnaissance level, to LANDSAT TM & MSS, and even to the AVHRR level. Three completed projects are reviewed: riparian habitat on the Humboldt River floodplain, Salt Lake County Urban expansion detection, and salinization/desertification detection in the delta area. Beginning projects summarized include: comparative condition of rangeland in Rush Valley; modeling a GIS/remote sensing data base for Cache County; universal soil loss equation applied to Pinyon-Juniper; relating MSS to ground radiometry near Battle Mountain; and riparian habitat mapping on Mary's River, Nevada.

Source record↗

NASA NTRS1986

Simulation and analysis of natural rain in a wind tunnel via digital image processing techniques

It is desired to simulate natural rain in a wind tunnel in order to investigate its influence on the aerodynamic characteristics of aircraft. Rain simulation nozzles have been developed and tested at JPL. Pulsed laser sheet illumination is used to photograph the droplets in the moving airstream. Digital image processing techniques are applied to these photographs for calculation of rain statistics to evaluate the performance of the nozzles. It is found that fixed hypodermic type nozzles inject too much water to simulate natural rain conditions. A modification uses two aerodynamic spinners to flex a tube in a pseudo-random fashion to distribute the water over a larger area.

Aaron, K. M.↗

NASA NTRS1990

Fractal image analysis - Application to the topography of Oregon and synthetic images.

Digitized topography for the state of Oregon has been used to obtain maps of fractal dimension and roughness amplitude. The roughness amplitude correlates well with variations in relief and is a promising parameter for the quantitative classification of landforms. The spatial variations in fractal dimension are low and show no clear correlation with different tectonic settings. For Oregon the mean fractal dimension from a two-dimensional spectral analysis is D = 2.586, and for a one-dimensional spectral analysis the mean fractal dimension is D = 1.487, which is close to the Brown noise value D = 1.5. Synthetic two-dimensional images have also been generated for a range of D values. For D = 2.6, the synthetic image has a mean one-dimensional spectral fractal dimension D = 1.58, which is consistent with the results for Oregon. This approach can be easily applied to any digitzed image that obeys fractal statistics.

Huang, Jie↗

NASA NTRS1994

Signal detection amid noise with known statistics

Conventional methods of signal detection are based on the comparison of a local signal-to-noise ratio S/N to some threshold value. We present a new method that compares instead the histogram of the data with the one expected for background noise alone. Signals are detected from discrepancies between the two. We expect it to be applicable in the detection of signals from any data whose background statistics is known. To illustrate the method, we apply it to the case of photon-limited imaging data where the underlying background is Poissonian. Numerical simulations are used to check the efficiency of our method, finding that for signals with low S/N (less than 5), it detects signals with a higher degree of reliability than the conventional method.

Zepka, A. F.↗

NASA NTRS1997

Current Activities and Capabilities of the Terrestrial Environment Group at NASA's Marshall Space Flight Center

The National Aeronautics and Space Administration (NASA) designated Marshall Space Flight Center (MSFC) the center of excellence for space transportation. The Aerospace Environments and Effects (AEE) team of the Electromagnetics and Aerospace Environments Branch (EL23) in the Systems Analysis and Integration Laboratory at MSFC, supports the center of excellence designation by providing near-Earth space, deep space, planetary, and terrestrial environments expertise to projects as required. The Terrestrial Environment (TE) group within the AEE team maintains an extensive TE data base. Statistics and models derived from this data are applied to the design and development of new aerospace vehicles, as well as performance enhancement of operational vehicles such as the Space Shuttle. The TE is defined as the Earth's atmospheric environment extending from the surface to orbital insertion altitudes (approximately 90 km).

Roberts, Barry C.↗

NASA NTRS1996

Identification, Uncertainty Characterization and Robust Control Synthesis Applied to Large Flexible Structures Control

This paper demonstrates an approach to frequency domain identification for the explicit purpose of designing robust H(infinity) controllers. The approach transforms raw experimental data into a plant set estimate directly usable by modern robust control design software(e.g., Matlab Robust Control Toolboxes [11][2]). A key issue in control design from raw data is the question of whether the controller will work when applied to the true system. The main feature fo this approach is that the resulting controller in guaranteed to work as designed(when applied to the true system) to a prescribed statistical confidence. While the overall methodology addresses key theoretical issues, it has at the same time been specifically designed to support practical implementations. A simulation example is included to demonstrate the overall approach.

software↗

NASA NTRS2005

Forecasting Lightning at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

The Applied Meteorology Unit (AMU) developed a set of statistical forecast equations that provide a probability of lightning occurrence on Kennedy Space Center (KSC) I Cape Canaveral Air Force Station (CCAFS) for the day during the warm season (May September). The 45th Weather Squadron (45 WS) forecasters at CCAFS in Florida include a probability of lightning occurrence in their daily 24-hour and weekly planning forecasts, which are briefed at 1100 UTC (0700 EDT). This information is used for general scheduling of operations at CCAFS and KSC. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts for the KSC/CCAFS area during Shuttle flight operations. Much of the current lightning probability forecast at both groups is based on a subjective analysis of model and observational data. The objective tool currently available is the Neumann-Pfeffer Thunderstorm Index (NPTI, Neumann 1971), developed specifically for the KSCICCAFS area over 30 years ago. However, recent studies have shown that 1-day persistence provides a better forecast than the NPTI, indicating that the NPTI needed to be upgraded or replaced. Because they require a tool that provides a reliable estimate of the daily thunderstorm probability forecast, the 45 WS forecasters requested that the AMU develop a new lightning probability forecast tool using recent data and more sophisticated techniques now possible through more computing power than that available over 30 years ago. The equation development incorporated results from two research projects that investigated causes of lightning occurrence near KSCICCAFS and over the Florida peninsula. One proved that logistic regression outperformed the linear regression method used in NPTI, even when the same predictors were used. The other study found relationships between large scale flow regimes and spatial lightning distributions over Florida. Lightning, probabilities based on these flow regimes were used as candidate predictors in the equation development. Fifteen years (1 989-2003) of warm season data were used to develop the forecast equations. The data sources included a local network of cloud-to-ground lightning sensors called the Cloud-to-Ground Lightning Surveillance System (CGLSS), 1200 UTC Florida synoptic soundings, and the 1000 UTC CCAFS sounding. Data from CGLSS were used to determine lightning occurrence for each day. The 1200 UTC soundings were used to calculate the synoptic-scale flow regimes and the 1000 UTC soundings were used to calculate local stability parameters, which were used as candidate predictors of lightning occurrence. Five logistic regression forecast equations were created through careful selection and elimination of the candidate predictors. The resulting equations contain five to six predictors each. Results from four performance tests indicated that the equations showed an increase in skill over several standard forecasting methods, good reliability, an ability to distinguish between non-lightning and lightning days, and good accuracy measures and skill scores. Given the overall good performance the 45 WS requested that the equations be transitioned to operations and added to the current set of tools used to determine the daily lightning probability of occurrence.

Lambert, Winfred↗