SEARCH · Search NASA

Results for “statistical sampling techniques”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10

All sources NASA NTRS DOE OSTI

NASA NTRS1988

Nondestructive evaluation of sintered ceramics

Radiography and several acoustic and thermoacoustic microscopy techniques are investigated for application to structural ceramics for advanced heat engines. A comparison is made of the results obtained from the use of scanning acoustic microscopy (SAM), scanning laser acoustic microscopy (SLAM), and thermoacoustic microscopy (TAM). These techniques are evaluated on research samples of green and sintered monolithic silicon nitrides and silicon carbides in the form of modulus-of-rupture (MOR) bars containing deliberately introduced flaws. Strengths and limitations of the techniques are described, with the emphasis being on statistics of detectability of flaws that constitute potential fracture origins. Further, it is shown that radiographic evaluation and guidance helped develop uniform high-density Si3N4 MOR bars with improved four-point flexural strength (875, 544, and 462 MPa at room temperature, 1200 C, 1370 C, respectively) and reduced scatter in bend strength.

Baaklini, George Y.↗

NASA NTRS2016

Persistence Mapping Using EUV Solar Imager Data

We describe a simple image processing technique that is useful for the visualization and depiction of gradually evolving or intermittent structures in solar physics extreme-ultraviolet imagery. The technique is an application of image segmentation, which we call "Persistence Mapping," to isolate extreme values in a data set, and is particularly useful for the problem of capturing phenomena that are evolving in both space and time. While integration or "time-lapse" imaging uses the full sample (of size N ), Persistence Mapping rejects (N - 1)/N of the data set and identifies the most relevant 1/N values using the following rule: if a pixel reaches an extreme value, it retains that value until that value is exceeded. The simplest examples isolate minima and maxima, but any quantile or statistic can be used. This paper demonstrates how the technique has been used to extract the dynamics in long-term evolution of comet tails, erupting material, and EUV dimming regions.

Thompson, B. J.↗

NASA NTRS1975

A method of using cluster analysis to study statistical dependence in multivariate data

A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.

Borucki, W. J.↗

NASA NTRS1986

Evolution of the luminosity function of extragalactic objects

A nonparametric procedure for determining the evolution of the luminosity function (LF) of extragalactic objects is described. The following steps are required: (1) selection of complete samples with known observational selection effects, (2) choice of a cosmological model, (3) statistical analysis of the sample and determination of the evolution of the luminosity function, and (4) the use of the luminosity function for the determination of the formation rate and the physical evolution of the objects. When the present technique is applied to a sample of optically selected quasars with redshifts less than two, it is shown that the LF evolves more strongly for higher luminosities, indicating a larger quasar activity at earlier epochs and a more rapid evolution of the objects during their higher luminosity phases.

Petrosian, V.↗

NASA NTRS1993

Properties of high-redshift Lyman-alpha clouds. I - Statistical analysis of the Schneider-Schmidt-Gunn quasars

Techniques for statistical analysis of the Lyman-alpha forest in high-redshift quasars are developed, and applied to the low-resolution (25 A) spectra of 29 of the 33 quasars in the Schneider-Schmidt-Gunn sample. We extrapolate each quasar's continuum shortward of Lyman-alpha emission, then consider each spectral bin of each quasar to be an (approximately) independent measurement of the absorption due to the Lyman-alpha clouds. With several thousand such measurements thus available, we can obtain good determinations of some interesting properties of clouds in the redshift range 2.5-4.3 without actually resolving any single cloud. We find that the mean absorption increases with z approximately as a power law (1 + z) exp (gamma + 1) with gamma = 2.46 +/- 0.37. The mean ratio of Lyman-alpha to Lyman-beta absorption in the clouds is 0.476 +/- 0.054. We also detect, and obtain ratios, for Lyma-gamma, delta, and possibly epsilon.

Press, William H.↗

NASA NTRS1988

Testing for periodicity of extinction

The statistical techniques used by Raup and Sepkoski (1984 and 1986) to identify a 26-Myr periodicity in the biological extinction record for the past 250 Myr are reexamined, responding in detail to the criticisms of Stigler and Wagner (1987). It is argued that evaluation of a much larger set of extinction data using a time scale with 51 sampling intervals supports the finding of periodicity. In a reply by Sigler and Wagner, the preference for a 26-Myr period is attributed to a numerical quirk in the Harland et al. (1982) time scale, in which the subinterval boundaries are not linear interpolations between the stage boundaries but have 25-Myr periodicity. It is stressed that the results of the stringent statistical tests imposed do not disprove periodicity but rather indicate that the evidence and analyses presented so far are inadequate.

Raup, David M.↗

DOE OSTI2025

3D Printing of Cement-Based Materials Using Seawater for Simulated Marine Environments

Global demand for adaptable and rapidly deployable construction solutions in offshore, coastal, and fluvial environments continues to rise, driven by pressing needs to develop energy platforms, improve coastal resilience, and support emergency response in the face of natural disasters. Increased investment in human-made coastal infrastructure, such as piers, support structures for power lines, offshore wind farms, and seawall protection systems, further underscores this trend. This study investigates the development of printable concrete mixtures for underwater environments using seawater as a replacement for freshwater, using a 3D printing syringe-based extrusion system. The effect of seawater addition and the printing medium (in air vs. underwater) was assessed via rheological and mechanical performance characterization. The results indicate rheological properties are favorable for seawater adoption by producing mixtures with higher yield stress and viscosity with the same levels of admixtures used for freshwater. Seawater-based mixtures demonstrated superior dimensional stability compared to freshwater counterparts, maintaining cross-sectional geometry, while compressive strength results showed no statistical differences between in-air and underwater samples. However, flexural strength was significantly influenced by geometry and printing medium. These findings establish critical rheological parameters for printable underwater mixtures and highlight the need for optimized curing strategies and layer bonding techniques to improve interfacial strength in underwater 3D printing applications.

36 MATERIALS SCIENCE↗

NASA NTRS1980

On the accuracy and precision of extinctions derived from general star counts

The accuracy and the applicability of the method of general star counts are discussed. The effects of statistical errors, pseudorandom errors, systematic errors, and sampling errors are considered. The conditions under which quantitatively useful results can be derived are identified. It is found that for plates reaching 17th to 20th mag, general star counts can be a useful technique for investigating the structure of dark cloud complexes located within 500 to 1000 pc of the sun.

Rossano, G. S.↗

DOE OSTI2024

Classification of events from α -induced reactions in the MUSIC detector via statistical and ML methods

The Multi-Sampling Ionization Chamber (MUSIC) detector is typically used to measure nuclear reaction cross sections relevant for nuclear astrophysics, fusion studies, and other applications. From the MUSIC data produced in one experiment scientists carefully extract an order of 10 3 events of interest from about 10 9 total events, where each event can be represented by an 18-dimensional vector. However, the standard data classification process is based on expert driven, manually intensive data analysis techniques that require several months to identify patterns and classify the relevant events from the collected data. Here, to address this issue, we present a method for the classification of events originating from specific α-induced reactions by combining statistical and machine learning methods that require significantly less input from the domain scientist, relative to the standard technique. Here, we applied the new method to two experimental data sets and compared our results with those obtained using traditional methods. With few exceptions, the number of events classified by our method agrees within ±20% with the results obtained using traditional methods. With the present method, which is the first of its kind for the MUSIC data, we have established the foundation for the automated extraction of physical events of interest from experiments using the MUSIC detector.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2020

Multiple Transits during a Single Conjunction: Identifying Transiting Circumbinary Planetary Candidates from TESS

We present results of a study on identifying circumbinary planet candidates that produce multiple transits during one conjunction with eclipsing binary systems. The occurrence of these transits enables us to estimate the candidates’ orbital periods, which is crucial as the periods of the currently known transiting circumbinary planets are significantly longer than the typical observational baseline of the Transiting Exoplanet Survey Satellite (TESS). Combined with the derived radii, it also provides valuable information needed for follow-up observations and subsequent confirmation of a large number of circumbinary planet candidates from TESS. Motivated by the discovery of the 1108 day circumbinary planet Kepler-1647, we show the application of this technique to four of Kepler’s circumbinary planets that produce such transits. Our results indicate that in systems where the circumbinary planet is on a low-eccentricity orbit, the estimated planetary orbital period is within <10%–20% of the true value. This estimate is derived from photometric observations spanning less than 5% of the planet’s period, demonstrating the strong capability of the technique. Capitalizing on the current and future eclipsing binaries monitored by NASA’s TESS mission, we estimate that hundreds of circumbinary planet candidates producing multiple transits during one conjunction will be detected in the TESS data. Such a large sample will enable statistical understanding of the population of planets orbiting binary stars and shed new light on their formation and evolution.

Veselin Kostov↗

NASA NTRS1996

Signal Processing and Calibration of Continuous-Wave Focused CO2 Doppler Lidars for Atmospheric Backscatter Measurement

Two continuous-wave(CW)focused C02 Doppler lidars (9.1 and 10.6 micrometers) were developed for airborne in situ aerosol backscatter measurements. The complex path of reliably calibrating these systems, with different signal processors, for accurate derivation of atmospheric backscatter coefficients is documented. Lidar calibration for absolute backscatter measurement for both lidars is based on range response over the lidar sample volume, not solely at focus. Both lidars were calibrated with a new technique using well-characterized aerosols as radiometric standard targets and related to conventional hard-target calibration. A digital signal processor (DSP), a surface acoustic and spectrum analyzer and manually tuned spectrum analyzer signal analyzers were used. The DSP signals were analyzed with an innovative method of correcting for systematic noise fluctuation; the noise statistics exhibit the chi-square distribution predicted by theory. System parametric studies and detailed calibration improved the accuracy of conversion from the measured signal-to-noise ratio to absolute backscatter. The minimum backscatter sensitivity is approximately 3 x 10(exp -12)/m/sr at 9.1 micrometers and approximately 9 x 10(exp -12)/m/sr at 10.6 micrometers. Sample measurements are shown for a flight over the remote Pacific Ocean in 1990 as part of the NASA Global Backscatter Experiment (GLOBE) survey missions, the first time to our knowledge that 9.1-10.6 micrometer lidar intercomparisons were made. Measurements at 9.1 micrometers, a potential wavelength for space-based lidar remote-sensing applications, are to our knowledge the first based on the rare isotope C-12 O(2)-18 gas.

Rothermel, Jeffry↗

DOE OSTI2025

Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis

ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.

Bennett, Danielle T. (ORCID:0009000188748827)↗

NASA NTRS1975

New capabilities for the Wallops Island SPANDAR

Systems incorporated into the SPANDAR to increase spatial resolution and data processing capabilities are described. They include a minicomputer that performs real-time formatting of video data, rapid antenna scan control, and control of a digital integrator; a frequency diversity technique for faster accumulation of independent video samples; the on-line calibration system for insertion of high and low calibration signals during every PRF interval; and utilization of a large capacity, high speed computer. The resultant data will be used to create statistical thunderstorm models for designing microwave communications systems.

Kropfli, R. A.↗

NASA NTRS1975

A preliminary investigation of remotely piloted vehicles for airframe noise research

Aircraft noise encountered in the community is caused predominantly by the aircraft engines. However, expected advances in engine noise technology combined with recent experimental evidence indicate that airframe (nonpropulsive) noise, may be a significant aircraft noise component in the future. Thus, methods for research into control of this type of noise are being evaluated and a technique based on the remotely piloted vehicle (RPV) concept appears to overcome some of the difficulties encountered with other test techniques. In particular, this paper presents sample experimental data, gathered during a preliminary RPV experiment, which illustrate the high signal-to-noise ratio attainable with this technique. Further, since the data are recorded as transients or nonstationary signals, a method of measurement and analysis is presented which increases statistical confidence in the results.

Fratello, D. J.↗

NASA NTRS1981

The evaluation of alternate methodologies for land cover classification in an urbanizing area

The usefulness of LANDSAT in classifying land cover and in identifying and classifying land use change was investigated using an urbanizing area as the study area. The question of what was the best technique for classification was the primary focus of the study. The many computer-assisted techniques available to analyze LANDSAT data were evaluated. Techniques of statistical training (polygons from CRT, unsupervised clustering, polygons from digitizer and binary masks) were tested with minimum distance to the mean, maximum likelihood and canonical analysis with minimum distance to the mean classifiers. The twelve output images were compared to photointerpreted samples, ground verified samples and a current land use data base. Results indicate that for a reconnaissance inventory, the unsupervised training with canonical analysis-minimum distance classifier is the most efficient. If more detailed ground truth and ground verification is available, the polygons from the digitizer training with the canonical analysis minimum distance is more accurate.

Smekofski, R. M.↗

NASA NTRS1983

Vegetation monitoring and classification using NOAA/AVHRR satellite data

A vegetation gradient model, based on a new surface hydrologic index and NOAA/AVHRR meteorological satellite data, has been analyzed along a 1300 km east-west transect across the state of Texas. The model was developed to test the potential usefulness of such low-resolution data for vegetation stratification and monitoring. Normalized Difference values (ratio of AVHRR bands 1 and 2, considered to be an index of greenness) were determined and evaluated against climatological and vegetation characteristics at 50 sample locations (regular intervals of 0.25 deg longitude) along the transect on five days in 1980. Statistical treatment of the data indicate that a multivariate model incorporating satellite-measured spectral greenness values and a surface hydrologic factor offer promise as a new technique for regional-scale vegetation stratification and monitoring.

Greegor, D. H., Jr.↗

NASA NTRS1992

Systematic differences between the field and cluster elliptical galaxies

Multivariate statistical techniques and fundamental plane fits are used here to study possible systematic differences between field ellipticals (FEs) and cluster ellipticals (CEs). The FEs show more intrinsic scatter in their properties, especially when stellar population variables are included. Pairwise correlations for the two samples are different; the correlations are systematically better for the cluster sample, meaning that ellipticals in the two samples populate their fundamental planes in different ways. Bivariate correlations are different for the two samples, implying that they have different fundamental planes. This is especially true for the correlations which include the population variables Mg2 and (B-V), which are sensitive both to the enrichment history and the storm formation history.

De Carvalho, R. R.↗

NASA NTRS1990

Neural net diagnostics for VLSI test

This paper discusses the application of neural network pattern analysis algorithms to the IC fault diagnosis problem. A fault diagnostic is a decision rule combining what is known about an ideal circuit test response with information about how it is distorted by fabrication variations and measurement noise. The rule is used to detect fault existence in fabricated circuits using real test equipment. Traditional statistical techniques may be used to achieve this goal, but they can employ unrealistic a priori assumptions about measurement data. Our approach to this problem employs an adaptive pattern analysis technique based on feedforward neural networks. During training, a feedforward network automatically captures unknown sample distributions. This is important because distributions arising from the nonlinear effects of process variation can be more complex than is typically assumed. A feedforward network is also able to extract measurement features which contribute significantly to making a correct decision. Traditional feature extraction techniques employ matrix manipulations which can be particularly costly for large measurement vectors. In this paper we discuss a software system which we are developing that uses this approach. We also provide a simple example illustrating the use of the technique for fault detection in an operational amplifier.

Lin, T.↗