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DOE OSTI2022

Deep learning-based noise filtering toward millisecond order imaging by using scanning transmission electron microscopy

Application of scanning transmission electron microscopy (STEM) to in situ observation will be essential in the current and emerging data-driven materials science by taking STEM’s high affinity with various analytical options into account. As is well known, STEM’s image acquisition time needs to be further shortened to capture a targeted phenomenon in real-time as STEM’s current temporal resolution is far below the conventional TEM’s. However, rapid image acquisition in the millisecond per frame or faster generally causes image distortion, poor electron signals, and unidirectional blurring, which are obstacles for realizing video-rate STEM observation. Here we show an image correction framework integrating deep learning (DL)-based denoising and image distortion correction schemes optimized for STEM rapid image acquisition. By comparing a series of distortion corrected rapid scan images with corresponding regular scan speed images, the trained DL network is shown to remove not only the statistical noise but also the unidirectional blurring. This result demonstrates that rapid as well as high-quality image acquisition by STEM without hardware modification can be established by the DL. The DL-based noise filter could be applied to in-situ observation, such as dislocation activities under external stimuli, with high spatio-temporal resolution.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Estimation of wintertime cloud radiative effects in the Western Arctic, a function of cloud-moisture-coupling and sea ice conditions

Cloud radiative effects are estimated using up- and downward ground-based observations of broadband thermal infrared sensors in cloudy conditions which are provided by the ARM data repository. The ARM Surface Radiation measurement is analyzed. To study the cloud radiative effects, the observed thermal infrared measurements under cloudy conditions are analyzed together with microphysical cloud properties like liquid and ice water path obtained from the CloudNet algorithms applied to the remote-sensing instrumentation suite at the ARM site in Utqiagvik. Cloud observations have been sorted depending on the coupling of the cloud with upwind water vapor transport events that can interact with sea ice upwind. Statistics of surface net thermal fluxes and cloud water/ice properties show a distinguished distribution for coupled and decoupled clouds. It was found that coupled clouds contain more liquid water and are more efficient reduce the cooling of surface LW radiation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Stealth dark matter spectrum using Laplacian Heaviside smearing and irreducible representations

We present nonperturbative lattice calculations in the quenched approximation of the low-lying meson and baryon spectrum of the SU(4) gauge theory with fundamental fermion constituents. This theory is one instance of stealth dark matter, a class of strongly coupled theories, where the lowest mass stable baryon is the dark matter candidate. This work constitutes the first milestone in the program to study stealth dark matter self-interactions. Here, we focus on reducing excited state contamination in the single-baryon channel by applying the Laplacian Heaviside method, as well as projecting our baryon operators onto the irreducible representations of the octahedral group. We compare our resulting spectrum to previous work involving Gaussian smeared nonprojected operators and find good agreement with reduced statistical uncertainties. We also present the spectrum of the low-lying odd-parity baryons for the first time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Software for Transformative Remedial Action Scheme Tool (TRAST)

The transformative remedial action scheme tool (TRAST) can be applied to improve and validate the power system remedial action scheme (RAS), and further improve the performance of power system operation and control. This tool provides a full suite of advanced functionalities, which are given as follows: 1. Advanced statistical data analysis; 2. OPF-based automated power flow case generation; 3. Customized dynamic simulation in HPC/cloud platform; 4. Machine learning based RAS coefficient prediction; 5. A reliable RAS validation strategy in multiple commercial platforms.

Fan, Xiaoyuan↗

DOE OSTI2023

Deep Learning Parameterization of Vertical Wind Velocity Variability via Constrained Adversarial Training

Atmospheric models with typical resolution in the tenths of kilometers cannot resolve the dynamics of air parcel ascent, which varies on scales ranging from tens to hundreds of meters. Small-scale wind fluctuations are thus characterized by a subgrid distribution of vertical wind velocity W with standard deviation σ W . The parameterization of σ W is fundamental to the representation of aerosol–cloud interactions, yet it is poorly constrained. Using a novel deep learning technique, this work develops a new parameterization for σ W merging data from global storm-resolving model simulations, high-frequency retrievals of W , and climate reanalysis products. The parameterization reproduces the observed statistics of σ W and leverages learned physical relations from the model simulations to guide extrapolation beyond the observed domain. Incorporating observational data during the training phase was found to be critical for its performance. The parameterization can be applied online within large-scale atmospheric models, or offline using output from weather forecasting and reanalysis products.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Beyond Generalized Eigenvalues

Two analysis techniques, the generalized eigenvalue method (GEM) or Prony's method (PM), are commonly used to analyze statistical estimates of correlation functions produced in lattice quantum field theory calculations. GEM takes full advantage of the matrix structure of correlation functions but only considers individual pairs of time separations when much more data exists. PM can be applied to many time separations and many individual matrix elements simultaneously but does not fully exploit the matrix structure of the correlation function. We combine both these methods into a single framework based on matrix polynomials which we call block Prony method (BPM).

Fleming, George T.↗

NASA NTRS1983

A renormalization group model for the stick-slip behavior of faults

A fault which is treated as an array of asperities with a prescribed statistical distribution of strengths is described. For a linear array the stress is transferred to a single adjacent asperity and for a two dimensional array to three ajacent asperities. It is shown that the solutions bifurcate at a critical applied stress. At stresses less than the critical stress virtually no asperities fail on a large scale and the fault is locked. At the critical stress the solution bifurcates and asperity failure cascades away from the nucleus of failure. It is found that the stick slip behavior of most faults can be attributed to the distribution of asperities on the fault. The observation of stick slip behavior on faults rather than stable sliding, why the observed level of seismicity on a locked fault is very small, and why the stress on a fault is less than that predicted by a standard value of the coefficient of friction are outlined.

Smalley, R. F., Jr.↗

NASA NTRS1984

Three-dimensional analysis of magnetometer array data

A technique is developed for mapping magnetic variation fields in three dimensions using data from an array of magnetometers, based on the theory of optimal linear estimation. The technique is applied to data from the Scandinavian Magnetometer Array. Estimates of the spatial power spectra for the internal and external magnetic variations are derived, which in turn provide estimates of the spatial autocorrelation functions of the three magnetic variation components. Statistical errors involved in mapping the external and internal fields are quantified and displayed over the mapping region. Examples of field mapping and of separation into external and internal components are presented. A comparison between the three-dimensional field separation and a two-dimensional separation from a single chain of stations shows that significant differences can arise in the inferred internal component.

Richmond, A. D.↗

NASA NTRS1985

A renormalization group approach to the stick-slip behavior of faults

A fault which is treated as an array of asperities with a perscribed statistical distribution of strengths is described. For a linear array the stress is transferred to a single adjacent asperity and for a two dimensional array to three adjacent asperities. It is shown that the solutions bifurcate at a critical applied stress. At stresses less than the critical stress virtually no asperities fail on a large scale and the fault is locked. At the critical stress the solution bifurcates and asperity failure cascades away from the nucleus of failure. It is found that the stick slip behavior of most faults can be attributed to the distribution of asperities on the fault. The observation of stick slip behavior on faults rather than stable sliding, why the observed level of seismicity on a locked fault is very small, and why the stress on a fault is less than that predicted by a standard value of the coefficient of friction are outlined.

Smalley, R. F., Jr.↗

NASA NTRS1990

Cloud and surface textural features in polar regions

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

Welch, Ronald M.↗

NASA NTRS1992

Precision of the calibration of the AXAF engineering test article (VETA) mirrors

Measurements of the VETA encircled energies have been performed at 5 energies within 16 radii ranging from 0.05 to 200 arcseconds. We report here on the analysis of the accuracy of those measurements. A common 'error tree' structure applies, and we present representative numbers for the larger terms. At 0.277, 1.5, and 2.07 keV, and for radii of 3 arcsec and larger, our measurements have estimated 1 sigma errors of 0.6 to 1.5 percent. Effects of measurement statistics and of the VETA test mount limit the accuracy at smaller angles, and modulation by the counter window support structure together with the imperfect position repeatability limit the accuracy for the 0.93 and 2.3 keV energies. We expect to mitigate these limitations when calibrating the complete AXAF flight mirror assembly.

Schwartz, D. A.↗

NASA NTRS1993

Precision of the calibration of the AXAF Engineering Test Article (VETA) mirrors

Schwartz, D. A.↗

NASA NTRS1994

Automatic generation of efficient orderings of events for scheduling applications

In scheduling a set of tasks, it is often not known with certainty how long a given event will take. We call this duration uncertainty. Duration uncertainty is a primary obstacle to the successful completion of a schedule. If a duration of one task is longer than expected, the remaining tasks are delayed. The delay may result in the abandonment of the schedule itself, a phenomenon known as schedule breakage. One response to schedule breakage is on-line, dynamic rescheduling. A more recent alternative is called proactive rescheduling. This method uses statistical data about the durations of events in order to anticipate the locations in the schedule where breakage is likely prior to the execution of the schedule. It generates alternative schedules at such sensitive points, which can be then applied by the scheduler at execution time, without the delay incurred by dynamic rescheduling. This paper proposes a technique for making proactive error management more effective. The technique is based on applying a similarity-based method of clustering to the problem of identifying similar events in a set of events.

Morris, Robert A.↗

NASA NTRS1997

Surface Plasmon Resonance Evaluation of Colloidal Metal Aerogel Filters

We have fabricated aerogels containing gold, silver, and platinum nanoparticles for gas catalysis applications. By applying the concept of an average or effective dielectric constant to the heterogeneous interlayer surrounding each particle, we extend the technique of immersion spectroscopy to porous or heterogeneous media. Specifically, we apply the predominant effective medium theories for the determination of the average fractional composition of each component in this inhomogeneous layer. Hence, the surface area of metal available for catalytic gas reaction is determined. The technique is satisfactory for statistically random metal particle distributions but needs further modification for aggregated or surfactant modified systems. Additionally, the kinetics suggest that collective particle interactions in coagulated clusters are perturbed during silica gelation resulting in a change in the aggregate geometry.

Smith, David D.↗

NASA NTRS1998

Noble Metal Immersion Spectroscopy of Silica Alcogels and Aerogels

We have fabricated aerogels containing gold and silver nanoparticles for gas catalysis applications. By applying the concept of an average or effective dielectric constant to the heterogeneous interlayer surrounding each particle, we extend the technique of immersion spectroscopy to porous or heterogeneous media. Specifically, we apply the predominant effective medium theories for the determination of the average fractional composition of each component in this inhomogeneous layer. Hence, the surface area of metal available for catalytic gas reaction is determined. The technique is satisfactory for statistically random metal particle distributions but needs further modification for aggregated or surfactant modified systems. Additionally, the kinetics suggest that collective particle interactions in coagulated clusters are perturbed during silica gelation resulting in a change in the aggregate geometry.

Smith, David D.↗

NASA NTRS2000

A Detailed Investigation into the Use of Planetary Nebulae as Standard Candles

The program's goal was to understand the physics underlying the [O III] (lambda)5007 planetary nebula luminosity function (PNLF) and evaluate its accuracy as an extragalactic distance indicator. Work under the grant concentrated in two areas. The first major goal was to extensively test the PNLF method to find its limits. We did this performing yet another internal test of the method in the core galaxies of the Fornax Cluster, performing external comparisons of PNLF distances with distances derived from Cepheids and the Surface Brightness Fluctuation method (SBF), and, in general, examining the PNLF in as many different galactic environments as possible, including the disks of late-type spirals. Because of the difficulty distinguishing planetary nebulae (PNe) from H II regions, and because spiral galaxies have uneven internal extinction, the process of identifying "statistical" samples of PNe in these objects is extremely complicated. Nevertheless, by using the ratio of [O III] (lambda)5007 to H(alpha) as a diagnostic, we were able to effectively discriminate PNe from most H II regions, and apply the method to systems such as NGC 300, M101, M51, and M96. The second goal of this research was to determine theoretically, why the PNLF is such an excellent standard candle.

Ciardullo, Robin↗

NASA NTRS2006

The Novel Nonlinear Adaptive Doppler Shift Estimation Technique and the Coherent Doppler Lidar System Validation Lidar

The signal processing aspect of a 2-m wavelength coherent Doppler lidar system under development at NASA Langley Research Center in Virginia is investigated in this paper. The lidar system is named VALIDAR (validation lidar) and its signal processing program estimates and displays various wind parameters in real-time as data acquisition occurs. The goal is to improve the quality of the current estimates such as power, Doppler shift, wind speed, and wind direction, especially in low signal-to-noise-ratio (SNR) regime. A novel Nonlinear Adaptive Doppler Shift Estimation Technique (NADSET) is developed on such behalf and its performance is analyzed using the wind data acquired over a long period of time by VALIDAR. The quality of Doppler shift and power estimations by conventional Fourier-transform-based spectrum estimation methods deteriorates rapidly as SNR decreases. NADSET compensates such deterioration in the quality of wind parameter estimates by adaptively utilizing the statistics of Doppler shift estimate in a strong SNR range and identifying sporadic range bins where good Doppler shift estimates are found. The authenticity of NADSET is established by comparing the trend of wind parameters with and without NADSET applied to the long-period lidar return data.

Beyon, Jeffrey Y.↗

NASA NTRS2016

Uncertainty Analysis of the NASA Glenn 8x6 Supersonic Wind Tunnel

This paper presents methods and results of a detailed measurement uncertainty analysis that was performed for the 8- by 6-foot Supersonic Wind Tunnel located at the NASA Glenn Research Center. The statistical methods and engineering judgments used to estimate elemental uncertainties are described. The Monte Carlo method of propagating uncertainty was selected to determine the uncertainty of calculated variables of interest. A detailed description of the Monte Carlo method as applied for this analysis is provided. Detailed uncertainty results for the uncertainty in average free stream Mach number as well as other variables of interest are provided. All results are presented as random (variation in observed values about a true value), systematic (potential offset between observed and true value), and total (random and systematic combined) uncertainty. The largest sources contributing to uncertainty are determined and potential improvement opportunities for the facility are investigated.

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