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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.

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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

A Comparison of Wind Speed Data from Mechanical and Ultrasonic Anemometers

This study compared the performance of mechanical and ultrasonic anemometers at the Eastern Range (ER; Kennedy Space Center and Cape Canaveral Air Force Station on Florida's Atlantic coast) and the Western Range (WR; Vandenberg Air Force Base on California's Pacific coast). Launch Weather Officers, forecasters, and Range Safety analysts need to understand the performance of wind sensors at the ER and WR for 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 current ER and WR weather tower wind instruments are being changed from the current propeller-and-vane (ER) and cup-and-vane (WR) sensors to ultrasonic sensors through the Range Standardization and Automation (RSA) program. The differences between mechanical and ultrasonic techniques have been found to cause differences in the statistics of peak wind speed in previous studies. The 45th Weather Squadron (45 WS) and the 30th Weather Squadron (30 WS) requested the Applied Meteorology Unit (AMU) to compare data between RSA and current sensors to determine if there are significant differences. Approximately 3 weeks of Legacy and RSA wind data from each range were used in the study, archived during May and June 2005. The ER data spanned the full diurnal cycle, while the WR data was confined to 1000-1600 local time. The sample of 1-minute data from numerous levels on 5 different towers on each range totaled more than 500,000 minutes of data (482,979 minutes of data after quality control). The 10 towers were instrumented at several levels, ranging from 12 ft to 492 ft above ground level. The RSA sensors were collocated at the same vertical levels as the present sensors and typically within 15 ft horizontally of each another. Data from a total of 53 RSA ultrasonic sensors, collocated with present sensors were compared. The 1-minute average wind speed/direction and the 1-second peak wind speed/direction were compared.

Short, D.↗
NASA NTRS2011

Multiple-Beam Detection of Fast Transient Radio Sources

A method has been designed for using multiple independent stations to discriminate fast transient radio sources from local anomalies, such as antenna noise or radio frequency interference (RFI). This can improve the sensitivity of incoherent detection for geographically separated stations such as the very long baseline array (VLBA), the future square kilometer array (SKA), or any other coincident observations by multiple separated receivers. The transients are short, broadband pulses of radio energy, often just a few milliseconds long, emitted by a variety of exotic astronomical phenomena. They generally represent rare, high-energy events making them of great scientific value. For RFI-robust adaptive detection of transients, using multiple stations, a family of algorithms has been developed. The technique exploits the fact that the separated stations constitute statistically independent samples of the target. This can be used to adaptively ignore RFI events for superior sensitivity. If the antenna signals are independent and identically distributed (IID), then RFI events are simply outlier data points that can be removed through robust estimation such as a trimmed or Winsorized estimator. The alternative "trimmed" estimator is considered, which excises the strongest n signals from the list of short-beamed intensities. Because local RFI is independent at each antenna, this interference is unlikely to occur at many antennas on the same step. Trimming the strongest signals provides robustness to RFI that can theoretically outperform even the detection performance of the same number of antennas at a single site. This algorithm requires sorting the signals at each time step and dispersion measure, an operation that is computationally tractable for existing array sizes. An alternative uses the various stations to form an ensemble estimate of the conditional density function (CDF) evaluated at each time step. Both methods outperform standard detection strategies on a test sequence of VLBA data, and both are efficient enough for deployment in real-time, online transient detection applications.

Thompson, David R.↗
NASA NTRS1990

Supply Current Diagnosis in VLSI

This paper presents a technique based upon the power supply current signature (cd) which allows for the testing of mixed-signal systems, in situ. Through experiments with a microprocessor, the cd is shown to contain important information concerning the operational status of the system which may be easily extracted using approaches based on statistical signal detection theory. The fault-detection performance of these techniques is compared to that achieved through auto-regressive modeling of the cd.

Frenzel, J. F.↗
NASA NTRS1994

Can we identify lensed gamma-ray bursts?

A gravitationally lensed gamma-ray burst (GRB) would appear as multiple bursts with identical light curves, separated in time and differing only by the scaling of their amplitudes. In reality, the detected bursts will be noisy, and therefore they may be difficult to identify as lensed images. Furthermore, faint, intrinsically similar, yet distinct light curves may be falsely identified as lensing events. In this paper we develop two statistical tests to distinguish noisy burst light curves. We use Fourier analysis techniques to analyze the signals for both intrinsic variability and variability due to noise. We are able to determine the noise level, and we compare the bursts only at frequency channels that are signal dominated. Utilizing these methods, we are able to make quantitative statements about whether two bursts are distinct. We apply these statistics to scaled versions of two subbursts of GRB 910503 -- subbursts previously investigated by Wambsganss using a different statistical test. We find that our methods are able to distinguish these bursts at slightly smaller amplitudes than those at which Wambsganss's method succeeds. We then apply our techniques to 'candidate' lensing events taken from the Burst and Transient Source Experiment (BATSE) catalog, and we find that nearly all of them, except for the very shortest ones (durations approx. less than 3 sec), are distinguishable. We therefore expect that a majority of bursts will be distinguishable from one another.

Nowak, Michael A.↗
DOE OSTI2017

Tracing Interstellar Magnetic Field Using Velocity Gradient Technique: Application to Atomic Hydrogen Data

The advancement of our understanding of MHD turbulence opens ways to develop new techniques to probe magnetic fields. In MHD turbulence, the velocity gradients are expected to be perpendicular to magnetic fields and this fact was used by González-Casanova and Lazarian to introduce a new technique to trace magnetic fields using velocity centroid gradients (VCGs). The latter can be obtained from spectroscopic observations. We apply the technique to GALFA-H i survey data and then compare the directions of magnetic fields obtained with our technique to the direction of magnetic fields obtained using PLANCK polarization. We find an excellent correspondence between the two ways of magnetic field tracing, which is obvious via the visual comparison and through the measuring of the statistics of magnetic field fluctuations obtained with the polarization data and our technique. This suggests that the VCGs have a potential for measuring of the foreground magnetic field fluctuations, and thus provide a new way of separating foreground and CMB polarization signals.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Recovering crater production functions from densely cratered surfaces

Two techniques proposed for the recovery of the crater-production functions on densely cratered surfaces have been appraised. The first technique classifies craters according to their degree of rim preservation, then interprets the statistics of the freshest craters as closely mimicking the full population's production function. Although commonly practiced, in fact, this method is demonstrably misleading for densely cratered surfaces. The second technique uses a weighting scheme to recover the production function. Each crater diameter measured is weighed by the fraction of the crater that remains unoverlapped by subsequent impacts. While this method is theoretically sound even at saturation crater densities, it too fails at high densities due to practical difficulties. For this technique to work effectively, one would have to be able to recognize and accurately measure the diameters of craters having less than 10 percent of their rims remaining, a feat beyond reasonable expectation.

Woronow, A.↗
DOE OSTI2019

Sparse Bayesian mass mapping with uncertainties: local credible intervals

ABSTRACT Until recently, mass-mapping techniques for weak gravitational lensing convergence reconstruction have lacked a principled statistical framework upon which to quantify reconstruction uncertainties, without making strong assumptions of Gaussianity. In previous work, we presented a sparse hierarchical Bayesian formalism for convergence reconstruction that addresses this shortcoming. Here, we draw on the concept of local credible intervals (cf. Bayesian error bars) as an extension of the uncertainty quantification techniques previously detailed. These uncertainty quantification techniques are benchmarked against those recovered via Px-MALA – a state-of-the-art proximal Markov chain Monte Carlo (MCMC) algorithm. We find that, typically, our recovered uncertainties are everywhere conservative (never underestimate the uncertainty, yet the approximation error is bounded above), of similar magnitude and highly correlated with those recovered via Px-MALA. Moreover, we demonstrate an increase in computational efficiency of $\mathcal {O}(10^6)$ when using our sparse Bayesian approach over MCMC techniques. This computational saving is critical for the application of Bayesian uncertainty quantification to large-scale stage IV surveys such as LSST and Euclid.

Price, M. A.↗
NASA NTRS2019

On the Calculation of Exact Cumulative Distribution Statistics for Burgers Equation

A mathematical procedure is presented for the calculation of exact cumulative distribution statistics for a viscosity-free variant of Burgers nonlinear partial differential equation (PDE) in one space dimension and time subject to sinusoidal initial data with uncertain (random variable) amplitude or phase shift. Analytical solutions of nonlinear PDEs with uncertain initial and/or boundary data are invaluable benchmarks in assessing approximate uncertainty quantification techniques. The Burgers equation solution with uncertain initial data results in nonsmooth solution behavior in both physical and random variable dimensions which provides a severe test for approximate uncertainty quantification techniques. Mathematical proofs are provided to verify that exact cumulative distribution statistics can be systematically and robustly obtained for all forward time.

Burgers↗
DOE OSTI2016

In-situ X-ray Nanocharacterization of Defect Kinetics in Chalcogenide Solar Cell Materials

For decades the optimization of polycrystalline absorbers has been done using an Edisonian approach, where trial and error and complex design of experiments in large parameter spaces have driven efficiencies to the record values we see today – CIGS at 22.5%, 22.1% for CdTe, 21.3% for high purity multi-crystalline silicon. Appropriate growth parameters are critical to ensure good quality crystals with low concentration of structural defects - low dislocation density and large grain sizes. However, to bridge the gap between the efficiencies today and the fundamental Shockley-Queisser limit for these materials a much more fundamental understanding of the role and interaction between composition, structure, defect density and electrical properties is required. In recent years multiple novel characterization techniques have shown the potential that nanoscale characterization can have in deciphering the composition of grain boundaries in materials like CIGS and CdTe. However, high resolution has come at the cost of small sampling areas and number of specimens, making it extremely difficult to draw conclusions based on the characteristic small sampling sizes. The missing links thus far have been: (1) the lack of statistical meaningfulness of the nanosclae studies and (2) the direct correlation of compositional variations to electrical performance with nanoscale resolution. In this work we present the use of synchrotron-based nano-X-ray fluorescence microscopy (nano-XRF), x-ray absorption nanospectroscopy (nano-XAS) coupled with nano-x-ray beam induced current (nano-XBIC) as ideal tools for investigating elemental, chemical and electrical properties of large areas of solar cell materials at the sub-micron scale with very high sensitivity. We show how the technique can provide statistical valuable information regarding the elemental segregation in CIGS and the direct correlation to current collection. For example, we demonstrate that Cu and Ga (and with that, CGI and GGI) correlate positively, and In negatively with charge collection efficiency for cells with low Ga content, both at grain boundaries and in grain cores. For cells with high Ga content, the charge collection efficiency depends to much lesser extent on the elemental distribution. The objective is three folded: (1) develop an x-ray in-situ microscopy capability to simulate growth and processing conditions, (2) apply it to elucidate performance-governing defect kinetics in chalcogenide solar cell materials, and (3) to study approaches to engineer materials from the nanoscale up. The development of these capabilities will enable experimental characterization to take place under actual processing and operating conditions and it will have impact well beyond the proposed research, enabling future studies on a large variety of materials system where electronic properties depend on underlying structural or chemical inhomogeneities.

14 SOLAR ENERGY↗
DOE OSTI2022

An overview of visualization and visual analytics applications in water resources management

Recent advances in information, communication, and environmental monitoring technologies have increased the availability, spatiotemporal resolution, and quality of water-related data, thereby leading to the emergence of many innovative big data applications. Among these applications, visualization and visual analytics, also known as the visual computing techniques, empower the synergy of computational methods (e.g., machine learning and statistical models) with human reasoning to improve the understanding and solution toward complex science and engineering problems. These approaches are frequently integrated with geographic information systems and cyberinfrastructure to provide new opportunities and methods for enhancing water resources management. Here, we present a comprehensive review of recent hydroinformatics applications that employ visual computing techniques to (1) support complex data-driven research problems, and (2) support the communication and decision-makings in the water resources management sector. Then, we conduct a technical review of the state-of-the-art web-based visualization technologies and libraries to share our experiences on developing shareable, adaptive, and interactive visualizations and visual interfaces for water resources management applications. We close with a vision that applies the emerging visual computing technologies and paradigms to develop the next generation of hydroinformatics applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Detecting hidden transient events in noisy nonlinear time-series

The information impulse function (IIF), running Variance, and local Hölder Exponent are three conceptually different time-series evaluation techniques. These techniques examine time-series for local changes in information content, statistical variation, and point-wise smoothness, respectively. Using simulated data emulating a randomly excited nonlinear dynamical system, this study interrogates the utility of each method to correctly differentiate a transient event from the background while simultaneously locating it in time. Computational experiments are designed and conducted to evaluate the efficacy of each technique by varying pulse size, time location, and noise level in time-series. Our findings reveal that, in most cases, the first instance of a transient event is more easily observed with the information-based approach of IIF than with the Variance and local Hölder Exponent methods. While our study highlights the unique strengths of each technique, the results suggest that very robust and reliable event detection for nonlinear systems producing noisy time-series data can be obtained by incorporating the IIF into the analysis.

42 ENGINEERING↗
DOE OSTI2015

Black hole and galaxy coevolution from continuity equation and abundance matching

We investigate the coevolution of galaxies and hosted supermassive black holes (BHs) throughout the history of the universe by a statistical approach based on the continuity equation and the abundance matching technique. Specifically, we present analytical solutions of the continuity equation without source terms to reconstruct the supermassive BH mass function from the active galactic nucleus (AGN) luminosity functions. Such an approach includes physically motivated AGN light curves tested on independent data sets, which describe the evolution of the Eddington ratio and radiative efficiency from slim- to thin-disk conditions. We nicely reproduce the local estimates of the BH mass function, the AGN duty cycle as a function of mass and redshift, along with the Eddington ratio function and the fraction of galaxies with given stellar mass hosting an AGN with given Eddington ratio. We exploit the same approach to reconstruct the observed stellar mass function at different redshift from the ultraviolet and far-IR luminosity functions associated with star formation in galaxies. These results imply that the build-up of stars and BHs in galaxies occurs via in situ processes, with dry mergers playing a marginal role at least for stellar masses ≲3×10{sup 11} M{sub ⊙} and BH masses ≲10{sup 9} M{sub ⊙}, where the statistical data are more secure and less biased by systematic errors. In addition, we develop an improved abundance matching technique to link the stellar and BH content of galaxies to the gravitationally dominant dark matter (DM) component. The resulting relationships constitute a testbed for galaxy evolution models, highlighting the complementary role of stellar and AGN feedback in the star formation process. In addition, they may be operationally implemented in numerical simulations to populate DM halos or to gauge subgrid physics. Moreover, they may be exploited to investigate the galaxy/AGN clustering as a function of redshift, mass, and/or luminosity. In fact, the clustering properties of BHs and galaxies are found to be in full agreement with current observations, thus further validating our results from the continuity equation. Finally, our analysis highlights that (i) the fraction of AGNs observed in the slim-disk regime, where most of the BH mass is accreted, increases with redshift; and (ii) already at z≳6 a substantial amount of dust must have formed over timescales ≲10{sup 8} yr in strongly star-forming galaxies, making these sources well within the reach of ALMA surveys in (sub)millimeter bands.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

An adaptive knowledge-based data-driven approach for turbulence modeling using ensemble learning technique under complex flow configuration: 3D PWR sub-channel with DNS data

This work describes a new approach to increase the accuracy of Reynolds-averaged Navier–Stokes (RANS) in modeling turbulence flow leveraging the machine learning technique. Traditionally, different turbulence models for Reynolds stress are developed for different flow patterns based on human knowledge. Each turbulence model has a certain application domain and prediction uncertainty. In recent years, with the rapid improvements of machine learning techniques, researchers start to develop an approach to compensate for the prediction discrepancy of traditional turbulence models with statistical models and data. However, the approach has deficiencies in several aspects. For example, the amount of human knowledge introduced to the statistical model couldn’t be controlled, which makes the statistical model learn from a very naïve stage and limits its application. In this work, a new approach is developed to address those deficiencies. Here, the new approach uses the “ensemble learning” technique to control the amount of human knowledge introduced into the statistical model. Therefore, the new approach could be adaptive to the multiple application domains. In conclusion, according to the results of case study, the new approach shows higher accuracy than both traditional turbulence models and the previous machine learning approach.

42 ENGINEERING↗
DOE OSTI2017

Paracousti-UQ: A Stochastic 3-D Acoustic Wave Propagation Algorithm.

Acoustic full waveform algorithms, such as Paracousti, provide deterministic solutions in complex, 3-D variable environments. In reality, environmental and source characteristics are often only known in a statistical sense. Thus, to fully characterize the expected sound levels within an environment, this uncertainty in environmental and source factors should be incorporated into the acoustic simulations. Performing Monte Carlo (MC) simulations is one method of assessing this uncertainty, but it can quickly become computationally intractable for realistic problems. An alternative method, using the technique of stochastic partial differential equations (SPDE), allows computation of the statistical properties of output signals at a fraction of the computational cost of MC. Paracousti-UQ solves the SPDE system of 3-D acoustic wave propagation equations and provides estimates of the uncertainty of the output simulated wave field (e.g., amplitudes, waveforms) based on estimated probability distributions of the input medium and source parameters. This report describes the derivation of the stochastic partial differential equations, their implementation, and comparison of Paracousti-UQ results with MC simulations using simple models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1974

Statistical method for the prediction of matching results in spectral file searching

In file-search techniques, the distribution of mismatches quantitatively measures the fit of a particular unknown against a given library. A simple theoretical method is developed to predict, a priori, this distribution. With this procedure, for any unknown code and library, the mean number of mismatches can be calculated exactly. For a given library and coding scheme, the mismatch distribution for most unknown codes closely follows a common curve which is easily calculated from statistical properties of the library. When this common curve is normalized to a constant mean, the observed matching behavior is well predicted. The theory should permit the user to more clearly assess the effects of errors on file search performance and suggest techniques by which recognition performance may be optimized.

Grotch, S. L.↗
DOE OSTI2018

Applying neutron transmission physics and 3D statistical full-field model to understand 2D Bragg-edge imaging

Bragg-edge imaging, which is also known as neutron radiography, has recently emerged as a novel crystalline characterization technique. Modelling of this novel technique by incorporating various features of the underlying microstructure (including the crystallographic texture, the morphological texture, and the grain size) of the material remains a subject of considerable research and development. In this paper, Inconel 718 samples made by additive manufacturing were investigated by neutron diffraction and neutron radiography techniques. The specimen features strong morphological and crystallographic textures and a highly heterogeneous microstructure. A 3D statistical full-field model is introduced by taking details of the microstructure into account to understand the experimental neutron radiography results. The Bragg-edge imaging and the total cross section were calculated based on the neutron transmission physics. A good match was obtained between the model predictions and experimental results at different incident beam angles with respect to the sample build direction. The current theoretical approach has the ability to incorporate 3D spatially resolved microstructural heterogeneity information and shows promise in understanding the 2D neutron radiography of bulk samples. With further development to incorporate the heterogeneity in lattice strain in the model, it can be used as a powerful tool in the future to better understand the neutron radiography data.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1970

Technique for Evaluating Multiple Probability Occurrences /TEMPO/

Technique is described for adjustment of engineering response information by broadening the application of statistical subjective stimuli theory. The study is specifically concerned with a mathematical evaluation of the expected probability of relative occurrence which can be identified by comparison rating techniques.

Mezzacappa, M. A.↗