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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Hybrid Ultrasonic TOFD Imaging of Weld Flaws Using Wavelet Transforms and Image Registration

Ultrasonic time of flight diffraction (TOFD) is an effective weld crack inspection technique. Due to the intensity of diffraction wave is rather weak compared with the lateral wave and the bottom echo wave, thus the signal-to-ratio (SNR) of TOFD image is low. A new dichotomous method is comprised of two steps that contains wavelet shrinkage and image registration is proposed in this paper to reduce the noise and improve the resolution of TOFD images as well. In order to evaluate the reliability of our proposed method in this paper, we have established the experiment system, and sampled a number of TOFD data with random distribution of noise characteristics. We adopted one-dimension wavelet transform and two-dimension wavelet transform in the very beginning of the first step of the proposed algorithm respectively. The SNR of the result obtained in this step is improved significantly compared with the classic algorithms. Next, the image registration is applied. After the registered images have been added to form a new one, then it comes to the final result that shows not only the SNR but also the definition of the image is enhanced effectively.

42 ENGINEERING↗
DOE OSTI2025

A statistical approach to screening isotopic signatures in monitoring for underground nuclear explosions

The ability to differentiate between atmospheric radionuclide signatures from underground nuclear explosions (UNEs) and signals from other sources, such as medical isotope-production facilities and nuclear reactors, can be critical to the detection and monitoring of unannounced, low-yield nuclear events. Signatures having anomalously high amplitudes, compared to background levels, remain the best indicator in screening for a UNE. However, isotopic composition can further validate a suspected UNE signature, but separation from any atmospheric background composition is first necessary. To date, evaluating the challenges of performing this separation has typically involved comparing an observed background with a highly idealized deterministic model of radioxenon signature production by a UNE that does not consider the influence of post-detonation chemical/physical processes in the detonation cavity or the subsequent gas transport mechanisms that can also affect the isotopic composition of the detected gas signature. In addition, purely deterministic models, as previously employed, overlook the uncertainty inherent in estimating critical parameters characterizing the UNE and its detonation environment. In this paper, we create detailed, multi-parameter models of radionuclide evolution using the widely accepted England and Rider post-detonation radionuclide decay-chain network coupled to detailed models simulating physical production and transport processes affecting the gas signature. Because these models are governed by uncertain parameters including barometric fluctuations, realistic ranges of variation for each of the parameters influencing isotopic composition are then defined. A Latin-Hypercube sampling approach is used to obtain a random distribution of isotopic production and gas transport results associated with a given value of each parameter. We apply these results to background histories of two stations, one providing 4-isotope background measurements and the other providing two-isotope measurements associated with the 2013 DPRK announced UNE.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Investigation of the Effect of Framework Flexibility on CO 2 Adsorption in SIFSIX-3-Cu Using a Machine-Learned Force Field

Metal–organic frameworks (MOFs) offer promise as selective CO 2 sorbents, but successful MOF sorbent materials need high CO 2 binding affinity and selectivity for CO 2 over water. This work focuses on the use of machine-learned force fields (MLFFs) to model CO 2 adsorption in flexible MOFs, with a focus on SIFSIX-3-Cu, an anion-pillared MOF known for its high CO 2 affinity. A preliminary high-throughput screening of over 900 anion-pillared MOFs was performed using rigid UFF+DDEC6 force fields to predict zero-loading heats of adsorption for CO 2 and H 2 O. SIFSIX-3-Cu was selected for further computational study due to its predicted CO 2 heat of adsorption and experimental relevance. A DeePMD-based MLFF was trained to reproduce DFT (PBE+D3) energies and forces, with an iterative sampling scheme combining molecular dynamics, geometry optimization, random geometric insertion, and NVT Monte Carlo-based configuration generation to capture both attractive and repulsive regions of the potential energy surface. Flexibility of the MOF was explicitly included, contrasting with previous models that approximated the MOF as rigid. Hybrid Monte Carlo/molecular dynamics (MC/MD) simulations with the MLFF produced CO 2 adsorption isotherms in good agreement with experimental data at direct air capture (DAC) pressures (e.g., 40 Pa), in contrast to previous overestimations of CO 2 sorption by models with rigid structures. Bond and angle histogram analysis showed that MOF flexibility increased the variance of fluorine–fluorine diagonal distances at adsorption sites, resulting in a lower predicted sorption for flexible, asymmetric SIFSIX-3-Cu pore geometries compared to the rigid, symmetric DFT-optimized SIFSIX-3-Cu pore geometry. A detailed description of flexibility afforded by the MLFF resulted in an accurately predicted CO 2 uptake (0.88 mmol/g) at low pressure (40 Pa) compared to the experimentally measured value (1.24 mmol/g). In conclusion, these results underscore the importance of including framework flexibility when modeling adsorption phenomena in MOFs, particularly for low-pressure applications.

adsorption↗
DOE OSTI2019

Strain-fluctuation-induced near quantization of valley Hall conductivity in graphene systems

We develop a theory of the valley Hall effect in high-quality graphene samples, in which strain-fluctuation-induced random gauge potentials have been suggested as the dominant source of disorder. We find a near-quantized value of valley Hall conductivity in the band transport regime, which originates from an enhanced side jump of a Dirac electron when it scatters off the gauge potential. By assuming a small residue charge density our theory reproduces qualitatively the temperature and gap dependence of the observed valley Hall effect at the charge neutral point. Furthermore, our study suggests that the valley Hall effect in graphene systems represents a new paradigm for the anomalous Hall physics where gauge disorder plays an important role.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Removal of spurious data in Bragg coherent diffraction imaging: an algorithm for automated data preprocessing

Bragg coherent diffraction imaging (BCDI) provides a powerful tool for obtaining high-resolution structural information from nanocrystalline materials. Here a BCDI sample consisting of a large number of randomly oriented nanoscale crystals is considered. Ideally, only one crystal is oriented to produce a Bragg peak on the detector. However, diffraction from other crystals often produces additional signals on the detector. Before the measured diffraction patterns can be processed into structural images, scientists routinely need to manually identify and remove the `alien' intensities from sources other than the intended crystal. With the development of modern high-coherence storage rings, such as the upgraded Advanced Photon Source (APS), the already slow process of manual preprocessing will be untenable for the large volumes of data that will be produced. An automated method of identifying and deleting alien intensities is proposed. This method exploits the fact that BCDI of a perfect crystal produces diffraction data with inversion symmetry around the Bragg peak. This approach uses the machine learning clustering method DBSCAN to distinguish between diffraction from multiple sources, and then calculates cluster size and inversion symmetry to assess whether clusters of intensity belong to desired data or alien signals. This approach can dramatically reduce the amount of time spent manually processing data, allowing BCDI data processing capabilities to keep pace with the technological advances of fourth-generation synchrotron light sources.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Filters for Improvement of Multiscale Data from Atomistic Simulations

Multiscale computational models strive to produce accurate and efficient numerical simulations of systems involving interactions across multiple spatial and temporal scales that typically differ by several orders of magnitude. Some such models utilize a hybrid continuum-atomistic approach combining continuum approximations with first-principles-based atomistic models to capture multiscale behavior. By following the heterogeneous multiscale method framework for developing multiscale computational models, unknown continuum scale data can be computed from an atomistic model. Concurrently coupling the two models requires performing numerous atomistic simulations which can dominate the computational cost of the method. Furthermore, when the resulting continuum data is noisy due to sampling error, stochasticity in the model, or randomness in the initial conditions, filtering can result in significant accuracy gains in the computed multiscale data without increasing the size or duration of the atomistic simulations. In this work, we demonstrate the effectiveness of spectral filtering for increasing the accuracy of noisy multiscale data obtained from atomistic simulations. Moreover, we present a robust and automatic method for closely approximating the optimum level of filtering in the case of additive white noise. By improving the accuracy of this filtered simulation data, it leads to a dramatic computational savings by allowing for shorter and smaller atomistic simulations to achieve the same desired multiscale simulation precision.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition

Over the past decade, the machine learning security community has developed a myriad of defenses for evasion attacks. An understudied question in that community is: for whom do these defenses defend? This work considers common approaches to defending learned systems and how security defenses result in performance inequities across different sub-populations. We outline appropriate parity metrics for analysis and begin to answer this question through empirical results of the fairness implications of machine learning security methods. We find that many methods that have been proposed can cause direct harm, like false rejection and unequal benefits from robustness training. The framework we propose for measuring defense equality can be applied to robustly trained models, preprocessing-based defenses, and rejection methods. We identify a set of datasets with a user-centered application and a reasonable computational cost suitable for case studies in measuring the equality of defenses. In our case study of speech command recognition, we show how such adversarial training and augmentation have non-equal but complex protections for social subgroups across gender, accent, and age in relation to user coverage. We present a comparison of equality between two rejection-based defenses: randomized smoothing and neural rejection, finding randomized smoothing more equitable due to the sampling mechanism for minority groups. This represents the first work examining the disparity in the adversarial robustness in the speech domain and the fairness evaluation of rejection-based defenses.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2020

Single-frame far-field diffractive imaging with randomized illumination

We introduce a single-frame diffractive imaging method called randomized probe imaging (RPI). In RPI, a sample is illuminated by a structured probe field containing speckles smaller than the sample’s typical feature size. Quantitative amplitude and phase images are then reconstructed from the resulting far-field diffraction pattern. The experimental geometry of RPI is straightforward to implement, requires no near-field optics, and is applicable to extended samples. When the resulting data are analyzed with a complimentary algorithm, reliable reconstructions which are robust to missing data are achieved. To realize these benefits, a resolution limit associated with the numerical aperture of the probe-forming optics is imposed. RPI therefore offers an attractive modality for quantitative X-ray phase imaging when temporal resolution and reliability are critical but spatial resolution in the tens of nanometers is sufficient. We discuss the method, introduce a reconstruction algorithm, and present two proof-of-concept experiments: one using visible light, and one using soft X-rays.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

RCT: Module 2.03, Counting Errors and Statistics, Course 8768

Radiological sample analysis involves the observation of a random process that may or may not occur and an estimation of the amount of radioactive material present based on that observation. Across the country, radiological control personnel are using the activity measurements to make decisions that may affect the health and safety of workers at those facilities and their surrounding environments. This course will present an overview of measurement processes, a statistical evaluation of both measurements and equipment performance, and some actions to take to minimize the sources of error in count room operations. This course will prepare the student with the skills necessary for radiological control technician (RCT) qualification by passing quizzes, tests, and the RCT Comprehensive Phase 1, Unit 2 Examination (TEST 27566) and by providing in the field skills.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

An Update on Monitoring Stellar Orbits in the Galactic Center

Using 25 years of data from uninterrupted monitoring of stellar orbits in the Galactic Center, we present an update of the main results from this unique data set: a measurement of mass and distance to Sgr A*. Our progress is not only due to the eight-year increase in time base, but also to the improved definition of the coordinate system. The star S2 continues to yield the best constraints on the mass of and distance to Sgr A*; the statistical errors of 0.13×10{sup 6} M{sub ⊙} and 0.12 kpc have halved compared to the previous study. The S2 orbit fit is robust and does not need any prior information. Using coordinate system priors, the star S1 also yields tight constraints on mass and distance. For a combined orbit fit, we use 17 stars, which yields our current best estimates for mass and distance: M=4.28±0.10|{sub stat.}±0.21|{sub sys}×10{sup 6} M{sub ⊙} and R{sub 0}=8.32±0.07|{sub stat.}±0.14|{sub sys} kpc. These numbers are in agreement with the recent determination of R {sub 0} from the statistical cluster parallax. The positions of the mass, of the near-infrared flares from Sgr A*, and of the radio source Sgr A* agree to within 1 mas. In total, we have determined orbits for 40 stars so far, a sample which consists of 32 stars with randomly oriented orbits and a thermal eccentricity distribution, plus eight stars that we can explicitly show are members of the clockwise disk of young stars, and which have lower-eccentricity orbits.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The Galah Survey: Classification and Diagnostics with t-SNE Reduction of Spectral Information

Galah is an ongoing high-resolution spectroscopic survey with the goal of disentangling the formation history of the Milky Way using the fossil remnants of disrupted star formation sites that are now dispersed around the Galaxy. It is targeting a randomly selected magnitude-limited ( V ≤ 14) sample of stars, with the goal of observing one million objects. To date, 300,000 spectra have been obtained. Not all of them are correctly processed by parameter estimation pipelines, and we need to know about them. We present a semi-automated classification scheme that identifies different types of peculiar spectral morphologies in an effort to discover and flag potentially problematic spectra and thus help to preserve the integrity of the survey results. To this end, we employ the recently developed dimensionality reduction technique t-SNE ( t -distributed stochastic neighbor embedding), which enables us to represent the complex spectral morphology in a two-dimensional projection map while still preserving the properties of the local neighborhoods of spectra. We find that the majority (178,483) of the 209,533 Galah spectra considered in this study represents normal single stars, whereas 31,050 peculiar and problematic spectra with very diverse spectral features pertaining to 28,579 stars are distributed into 10 classification categories: hot stars, cool metal-poor giants, molecular absorption bands, binary stars, H α /H β emission, H α /H β emission superimposed on absorption, H α /H β P-Cygni, H α /H β inverted P-Cygni, lithium absorption, and problematic. Classified spectra with supplementary information are presented in the catalog, indicating candidates for follow-up observations and population studies of the short-lived phases of stellar evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

POF-Darts: Geometric adaptive sampling for probability of failure

We introduce a novel technique, POF-Darts, to estimate the Probability Of Failure based on random disk-packing in the uncertain parameter space. POF-Darts uses hyperplane sampling to explore the unexplored part of the uncertain space. We use the function evaluation at a sample point to determine whether it belongs to failure or non-failure regions, and surround it with a protection sphere region to avoid clustering. We decompose the domain into Voronoi cells around the function evaluations as seeds and choose the radius of the protection sphere depending on the local Lipschitz continuity. As sampling proceeds, regions uncovered with spheres will shrink, improving the estimation accuracy. After exhausting the function evaluation budget, we build a surrogate model using the function evaluations associated with the sample points and estimate the probability of failure by exhaustive sampling of that surrogate. In comparison to other similar methods, our algorithm has the advantages of decoupling the sampling step from the surrogate construction one, the ability to reach target POF values with fewer samples, and the capability of estimating the number and locations of disconnected failure regions, not just the POF value. Furthermore, we present various examples to demonstrate the efficiency of our novel approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Multi-scale investigation on mechanical behavior and microstructural alteration of C-S-H in carbonated Alite paste

Carbonation treatment is a promising option to enhance recycled concrete aggregate (RCA) quality and eventually improve concrete performance. This study investigated the multi-scale mechanical properties of calcium silicate hydrates (C-S-H) in a mature alite paste subjected to accelerated carbonation treatment by testing macro compressive strength, microhardness and nanoindentation. The results show that, carbonation treatment resulted in a heterogeneous distribution of carbonation products in the alite sample. Reinforcement of C-S-H by the randomly precipitated calcite and vaterite crystals prevailed over the nano-structural and compositional alteration of C-S-H induced by carbonation, leading to an increase of nano-indentation modulus at the edge of the sample. Also, the microhardness at the edge zone was markedly higher than that at the core of the carbonated sample. The carbonated peripheral zone with improved nano-scale modulus and microhardness was likely serving as a “hard shell”, contributing to the improved macro compressive strength. The new insights into the multi-scale mechanical properties of carbonated C-S-H contribute to further understanding of the enhanced properties of RCA after carbonation treatment.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Metallographic Characterization of Wrought Depleted Uranium

Metallographic characterization was performed on wrought depleted uranium (DU) samples taken from the longitudinal and transverse orientations from specific locations on two specimens. Characterization of the samples included general microstructure, inclusion analysis, grain size analysis, and microhardness testing. Comparisons of the characterization results were made to determine any differences based on specimen, sample orientation, or sample location. In addition, the characterization results for the wrought DU samples were also compared with data obtained from the metallographic characterization of cast DU samples previously characterized. No differences were observed in microstructure, inclusion size, morphology, and distribution, or grain size in regard to specimen, location, or orientation for the wrought depleted uranium samples. However, a small difference was observed in average hardness with regard to orientation at the same locations within the same specimen. The longitudinal samples were slightly harder than the transverse samples from the same location of the same specimen. This was true for both wrought DU specimens. Comparing the wrought DU sample data with the previously characterized cast DU sample data, distinct differences in microstructure, inclusion size, morphology and distribution, grain size, and microhardness were observed. As expected, the microstructure of the wrought DU samples consisted of small recrystallized grains which were uniform, randomly oriented, and equiaxed with minimal twinning observed in only a few grains. In contrast, the cast DU microstructure consisted of large irregularly shaped grains with extensive twinning observed in most grains. Inclusions in the wrought DU samples were elongated, broken and cracked and light and dark phases were observed in some inclusions. The mean inclusion area percentage for the wrought DU samples ranged from 0.08% to 0.34% and the average density from all wrought DU samples was 1.62E+04/cm 2 . Inclusions in the cast DU samples were equiaxed and intact with light and dark phases observed in some inclusions. The mean inclusion area percentage for the cast DU samples ranged from 0.93% to 1.00% and the average density from all wrought DU samples was 2.83E+04/cm 2 . The average mean grain area from all wrought DU samples was 141 μm 2 while the average mean grain area from all cast DU samples was 1.7 mm2. The average Knoop microhardness from all wrought DU samples was 215 HK and the average Knoop microhardness from all cast DU samples was 264 HK.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning

Abstract Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about bonding, distributions and locations of atoms, and their coordination numbers and oxidation states. However, analysis of XAS/EELS data often relies on matching an unknown experimental sample to a series of simulated or experimental standard samples. This limits analysis throughput and the ability to extract quantitative information from a sample. In this work, we have trained a random forest model capable of predicting the oxidation state of copper based on its L-edge spectrum. Our model attains an R 2 score of 0.85 and a root mean square error of 0.24 on simulated data. It has also successfully predicted experimental L-edge EELS spectra taken in this work and XAS spectra extracted from the literature. We further demonstrate the utility of this model by predicting simulated and experimental spectra of mixed valence samples generated by this work. This model can be integrated into a real-time EELS/XAS analysis pipeline on mixtures of copper-containing materials of unknown composition and oxidation state. By expanding the training data, this methodology can be extended to data-driven spectral analysis of a broad range of materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Binary pseudorandom array test standard optimized for characterization of large field-of-view optical interferometers

Recently, a technique for calibrating the modulation transfer function (MTF) of a broad variety of metrology instrumentation has been demonstrated. This technique is based on test samples structured as one-dimensional binary pseudo-random (BPR) sequences and two-dimensional BPR arrays (BPRAs). The inherent power spectral density of BPR gratings (sequences) and arrays has a deterministic white-noise-like character that allows direct determination of the MTF with uniform sensitivity over the entire spatial frequency range and field-of-view of an instrument. As such, the BPR samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error. Here we discuss our recent developments directed to the optimization of the sample design, fabrication, application, and data processing procedures, suitable for thorough characterization of large aperture optical interferometers. Compared with the previous coded-aperture based design, the improved, 'highly randomized' BPRA pattern of the new test standard provides better accuracy and reliability of instrument MTF and aberration characterization, and enables operation optimization of large aperture optical interferometers. We describe the pattern generation algorithm and tests to verify the compliance to desired BPRA topography. The data acquisition and analysis procedures for different applications of the technique are also discussed.

Yashchuk, Valeriy V.↗
DOE OSTI2024

SDSS-IV MaNGA: calibration of astrophysical line-widths in the Hα region using HexPak observations

ABSTRACT We have re-observed $\rm \sim$40 low-inclination, star-forming galaxies from the MaNGA survey (σ ∼ 65 km s−1) at ∼6.5 times higher spectral resolution (σ ∼ 10 km s−1) using the HexPak integral field unit on the WIYN 3.5-m telescope. The aim of these observations is to calibrate MaNGA’s instrumental resolution and to characterize turbulence in the warm interstellar medium and ionized galactic outflows. Here we report the results for the Hα region observations as they pertain to the calibration of MaNGA’s spectral resolution. Remarkably, we find that the previously reported MaNGA line-spread-function (LSF) Gaussian width is systematically underestimated by only 1 per cent. The LSF increase modestly reduces the characteristic dispersion of H ii regions-dominated spectra sampled at 1–2 kpc spatial scales from 23 to 20 km s−1 in our sample, or a 25 per cent decrease in the random-motion kinetic energy. This commensurately lowers the dispersion zeropoint in the relation between line-width and star-formation rate surface-density in galaxies sampled on the same spatial scale. This modest zero-point shift does not appear to alter the power-law slope in the relation between line-width and star-formation rate surface-density. We also show that adopting a scheme whereby corrected line-widths are computed as the square root of the median of the difference in the squared measured line width and the squared LSF Gaussian avoids biases and allows for lower signal-to-noise data to be used reliably.

Chattopadhyay, Sabyasachi↗
DOE OSTI2016

Molecular organization in MAPLE-deposited conjugated polymer thin films and the implications for carrier transport characteristics

The morphological structure of poly(3-hexylthiophene) (P3HT) thin films deposited by both Matrix Assisted Pulsed Laser Evaporation (MAPLE) and solution spin-casting methods are investigated. We found that the MAPLE samples possessed a higher degree of disorder, with random orientations of polymer crystallites along the side-chain stacking, π-π stacking, and conjugated backbone directions. Furthermore, the average molecular orientations and relative degrees of crystallinity of MAPLE-deposited polymer films are insensitive to the chemistries of the substrates onto which they were deposited; this is in stark contrast to the films prepared by the conventional spin-casting technique. In spite of the seemingly unfavorable molecular orientations and the highly disordered morphologies, the in-plane charge carrier transport characteristics of the MAPLE samples are comparable to those of spin-cast samples, exhibiting similar transport activation energies (56 meV versus 54 meV) to those reported in the literature for high mobility polymers.

36 MATERIALS SCIENCE↗