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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Anharmonic Bloch oscillations of electrons in electrically biased superlattices

The phenomenon of anharmonic Bloch oscillations (i.e., oscillations with a frequency which is a multiple of the Bloch frequency) is considered. The energy-band structure of silicon-carbide polytypes where these oscillations are observed is calculated ab initio. A one-dimensional model potential making it possible to calculate the Stark wave functions in a biased superlattice is constructed for these polytypes. The transfer matrix method is used to find the set of energy levels (the so-called Stark ladder) and calculate the electron wave functions. It is shown that both radiative transitions between neighboring Stark levels (at the Bloch frequency) and transitions in the form of jumps via several levels, accompanied by emission at frequencies that are multiples of the Bloch frequency, may occur. The calculated probabilities of transitions between Stark-ladder levels increase with increasing applied field strength.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Judgments of eye level in light and in darkness

Subjects judged eye level in the light and in the dark by raising and lowering themselves in a dental chair until a stationary target appeared to be at the level of their eyes. This method reduced the possibility of subjects' using visible landmarks as reference points for setting eye level during lighted trials, which may have contributed to artificially low estimates of the variability of this judgment in previous studies. Chair settings were 2.5 deg higher in the dark than in the light, and variability was approximately 66 percent greater in the dark than in the light. These results are discussed in terms of possible interactions of two separate systems, one sensitive to the orientations of visible surfaces and the other sensitive to bodily and gravitational information.

Stoper, Arnold E.↗
DOE OSTI2015

SU-F-207-16: CT Protocols Optimization Using Model Observer

Purpose: To quantitatively evaluate the performance of different CT protocols using task-based measures of image quality. This work studies the task of size and the contrast estimation of different iodine concentration rods inserted in head- and body-sized phantoms using different imaging protocols. These protocols are designed to have the same dose level (CTDIvol) but using different X-ray tube voltage settings (kVp). Methods: Different concentrations of iodine objects inserted in a head size phantom and a body size phantom are imaged on a 64-slice commercial CT scanner. Scanning protocols with various tube voltages (80, 100, and 120 kVp) and current settings are selected, which output the same absorbed dose level (CTDIvol). Because the phantom design (size of the iodine objects, the air gap between the inserted objects and the phantom) is not ideal for a model observer study, the acquired CT images are used to generate simulation images with four different sizes and five different contracts iodine objects. For each type of the objects, 500 images (100 x 100 pixels) are generated for the observer study. The observer selected in this study is the channelized scanning linear observer which could be applied to estimate the size and the contrast. The figure of merit used is the correct estimation ratio. The mean and the variance are estimated by the shuffle method. Results: The results indicate that the protocols with 100 kVp tube voltage setting provides the best performance for iodine insert size and contrast estimation for both head and body phantom cases. Conclusion: This work presents a practical and robust quantitative approach using channelized scanning linear observer to study contrast and size estimation performance from different CT protocols. Different protocols at same CTDIvol setting could Result in different image quality performance. The relationship between the absorbed dose and the diagnostic image quality is not linear.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

First model-independent Dalitz analysis of B 0 → DK* 0 , D→K$^{0}_{S}$π + π – decay

We report a measurement of the amplitude ratio r S of B 0 → D 0 K* 0 and B 0 → D 0 ¯K* 0 decays with a Dalitz analysis of D → K$^{0}_{S}$π + π – decays, for the first time using a model-independent method. We set an upper limit rS<0.87 at the 68\% confidence level, using the full data sample of 772×10 6 BB¯ pairs collected at the Υ(4S) resonance with the Belle detector at the KEKB e + e – collider. This result is obtained from observables x–= +0.4$^{+1.0+0.0}_{–0.6–0.1}$ ± 0.0, y– = –0.6$^{+0.8+0.1}_{–1.0–0.0}$ ± 0.1, x + = +0.1$^{+0.7+0.0}_{–0.4–0.1}$ ± 0.1 and y + = +0.3$^{+0.5+0.0}_{–0.8–0.1}$ ± 0.1, where x ± = r S cos(δ S ± Φ 3 ), y ± = r S sin(δ S ± Φ 3 ) and Φ 3 (δ S ) is the weak (strong) phase difference between B 0 → D 0 K* 0 and B 0 → D¯ 0 K* 0 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Generalized conditional symmetries and related solutions of the Grad-Shafranov equation

The generalized conditional symmetry (GCS) method is applied to a specific case of the Grad–Shafranov (GS) equation, in cylindrical geometry assuming the existence of an axial symmetry. We investigate the conditions that yield the GS equation admitting a special class of second-order GCSs. The determining system for the unknown arbitrary functions is solved in several special cases and new exact solutions, including solitary waves, different in form and structure from the ones obtained using other nonclassical symmetry methods, are pointed out. Several plots of the level sets or flux surfaces of the new solutions as well as surfaces with vanishing flow are displayed. The obtained solutions can be useful for studying plasma equilibrium, transport phenomena, and magnetohydrodynamic stability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Multiclass Classification Using Bayesian Multivariate Adaptive Regression Splines

We present a new Bayesian model for the problem of multiclass classification. In this model, the probabilities of class membership of a given observation are determined by the mean of a latent Gaussian distribution. The mean functions of this latent distribution consist of combinations of highly flexible basis functions of the inputs: multivariate adaptive regression splines (MARS), first developed for multiple regression. We use reversible jump Markov chain Monte Carlo to make inference on the classification model, including the number of basis functions. We compare the probabilistic classification performance of our proposed approach to existing methods on simulated and benchmark data, and compare uncertainty estimates on simulated data. Our proposed method compares favorably with existing Bayesian and frequentist multiclass classification methods in out-of-sample probabilistic classification, and uncertainty estimation of these probabilistic classifications. We examine the fit of the proposed method to a data set of hurricane storm surge levels near Delaware Bay, US, and conclude that sea level rise is a key contributor to damage delivered by storm surge.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1972

The Valuation of Scientific and Technical Experiments

Rational selection of scientific and technical experiments for space missions is studied. Particular emphasis is placed on the assessment of value or worth of an experiment. A specification procedure is outlined and discussed for the case of one decision maker. Experiments are viewed as multi-attributed entities, and a relevant set of attributes is proposed. Alternative methods of describing levels of the attributes are proposed and discussed. The reasonableness of certain simplifying assumptions such as preferential and utility independence is explored, and it is tentatively concluded that preferential independence applies and utility independence appears to be appropriate.

Williams, F. E.↗
DOE OSTI2016

Generic and robust method for automatic segmentation of PET images using an active contour model

Purpose: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an active contour model and to evaluate its performance using phantom and clinical studies. Methods: MASAC, a method for automatic segmentation using an active contour model, incorporates the histogram fuzzy C-means clustering, and localized and textural information to constrain the active contour to detect boundaries in an accurate and robust manner. Moreover, the lattice Boltzmann method is used as an alternative approach for solving the level set equation to make it faster and suitable for parallel programming. Twenty simulated phantom studies and 16 clinical studies, including six cases of pharyngolaryngeal squamous cell carcinoma and ten cases of nonsmall cell lung cancer, were included to evaluate its performance. Besides, the proposed method was also compared with the contourlet-based active contour algorithm (CAC) and Schaefer’s thresholding method (ST). The relative volume error (RE), Dice similarity coefficient (DSC), and classification error (CE) metrics were used to analyze the results quantitatively. Results: For the simulated phantom studies (PSs), MASAC and CAC provide similar segmentations of the different lesions, while ST fails to achieve reliable results. For the clinical datasets (2 cases with connected high-uptake regions excluded) (CSs), CAC provides for the lowest mean RE (−8.38% ± 27.49%), while MASAC achieves the best mean DSC (0.71 ± 0.09) and mean CE (53.92% ± 12.65%), respectively. MASAC could reliably quantify different types of lesions assessed in this work with good accuracy, resulting in a mean RE of −13.35% ± 11.87% and −11.15% ± 23.66%, a mean DSC of 0.89 ± 0.05 and 0.71 ± 0.09, and a mean CE of 19.19% ± 7.89% and 53.92% ± 12.65%, for PSs and CSs, respectively. Conclusions: The authors’ results demonstrate that the developed novel PET segmentation algorithm is applicable to various types of lesions in the authors’ study and is capable of producing accurate and consistent target volume delineations, potentially resulting in reduced intraobserver and interobserver variabilities observed when using manual delineation and improved accuracy in treatment planning and outcome evaluation.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1986

Accelerated Stress-Corrosion Testing

Test procedures for accelerated stress-corrosion testing of high-strength aluminum alloys faster and provide more quantitative information than traditional pass/fail tests. Method uses data from tests on specimen sets exposed to corrosive environment at several levels of applied static tensile stress for selected exposure times then subsequently tensile tested to failure. Method potentially applicable to other degrading phenomena (such as fatigue, corrosion fatigue, fretting, wear, and creep) that promote development and growth of cracklike flaws within material.

Source record↗
NASA NTRS2005

Effective Radius of Ice Cloud Particle Populations Derived from Aircraft Probes

The effective radius(r(sub e)) is a crucial variable in representing the radiative properties of cloud layers in general circulation models. This parameter is proportional to the condensed water content (CWC) divided by the extinction (sigma). For ice cloud layers, parameterizations for r(sub e), have been developed from aircraft in-situ measurements 1) indirectly, using data obtained from particle spectrometer probes and assumptions or observations about particle shape and mass to get the ice water content (IWC) and area to get sigma, and recently 2) from probes that measure IWC and sigma directly. This study compares [IWC/sigma] derived from the two methods using data sets acquired from comparable instruments on two aircraft, one sampling clouds at mid-levels and the other at upper-levels during the CRYSTAL-FACE field program in Florida in 2002. The sigma and IWC derived by each method are compared and evaluated in different ways for each aircraft data set. Direct measurements of sigma exceed those derived indirectly by a factor of two to two and a half. The IWC probes, relying on ice sublimation, appear to measure accurately except when the IWC is high or the particles too large to sublimate completely during the short transit time through the probe. The IWC estimated from the particle probes are accurate when direct measurements are available to provide constraints and useful information in high IWC/large particle situations. Because of the discrepancy in sigma estimates between the direct and indirect approaches, there is a factor of 2 to 3 difference in [IWC/sigma] between them. Although there are significant uncertainties involved in its use, comparisons with several independent data sources suggest that the indirect method is the more accurate of the two approaches. However, experiments are needed to resolve the source of the discrepancy in sigma.

Heymsfield, Andrew J.↗
DOE OSTI2020

Digital zero noise extrapolation for quantum error mitigation

Zero-noise extrapolation (ZNE) is an increasingly popular technique for mitigating errors in noisy quantum computations without using additional quantum resources. We review the fundamentals of ZNE and propose several improvements to noise scaling and extrapolation, the two key components in the technique. We introduce unitary folding and parameterized noise scaling. Furthermore, these are digital noise scaling frameworks, i.e. one can apply them using only gate-level access common to most quantum instruction sets. We also study different extrapolation methods, including a new adaptive protocol that uses a statistical inference framework. Benchmarks of our techniques show error reductions of 18X to 24X over non-mitigated circuits and demonstrate ZNE effectiveness at larger qubit numbers than have been tested previously. In addition to presenting new results, this work is a self-contained introduction to the practical use of ZNE by quantum programmers.

quantum computing↗
DOE OSTI2012

Aerial Scene Recognition using Efficient Sparse Representation

Advanced scene recognition systems for processing large volumes of high-resolution aerial image data are in great demand today. However, automated scene recognition remains a challenging problem. Efficient encoding and representation of spatial and structural patterns in the imagery are key in developing automated scene recognition algorithms. We describe an image representation approach that uses simple and computationally efficient sparse code computation to generate accurate features capable of producing excellent classification performance using linear SVM kernels. Our method exploits unlabeled low-level image feature measurements to learn a set of basis vectors. We project the low-level features onto the basis vectors and use simple soft threshold activation function to derive the sparse features. The proposed technique generates sparse features at a significantly lower computational cost than other methods~\cite{Yang10, newsam11}, yet it produces comparable or better classification accuracy. We apply our technique to high-resolution aerial image datasets to quantify the aerial scene classification performance. We demonstrate that the dense feature extraction and representation methods are highly effective for automatic large-facility detection on wide area high-resolution aerial imagery.

Computer Vision↗
DOE OSTI2021

Extending quantum probabilistic error cancellation by noise scaling

Here, we propose a general framework for quantum error mitigation that combines and generalizes two techniques: probabilistic error cancellation (PEC) and zero-noise extrapolation (ZNE). Similar to PEC, the proposed method represents ideal operations as linear combinations of noisy operations that are implementable on hardware. However, instead of assuming a fixed level of hardware noise, we extend the set of implementable operations by noise scaling. By construction, this method encompasses both PEC and ZNE as particular cases and allows us to investigate a larger set of hybrid techniques. For example, gate extrapolation can be used to implement PEC without requiring knowledge of the device’s noise model, e.g., avoiding gate-set tomography. Alternatively, probabilistic error reduction can be used to estimate expectation values at intermediate virtual noise strengths (below the hardware level), leading to partially mitigated results at a lower sampling cost. Moreover, multiple results obtained with different noise-reduction factors can be further postprocessed with ZNE to better approximate the zero-noise limit.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Enhanced Uranium Ore Concentrate Analysis by Handheld Raman Sensor: FY15 Status Report

High-purity uranium ore concentrates (UOC) represent a potential proliferation concern. A cost-effective, “point and shoot” in-field analysis capability to identify ore types, phases of materials present, and impurities, as well as estimate the overall purity would be prudent. Handheld, Raman-based sensor systems are capable of identifying chemical properties of liquid and solid materials. While handheld Raman systems have been extensively applied to many other applications, they have not been broadly studied for application to UOC, nor have they been optimized for this class of chemical compounds. PNNL was tasked in Fiscal Year 2015 by the Office of International Safeguards (NA-241) to explore the use of Raman for UOC analysis and characterization. This report summarizes the activities in FY15 related to this project. The following tasks were included: creation of an expanded library of Raman spectra of a UOC sample set, creation of optimal chemometric analysis methods to classify UOC samples by their type and level of impurities, and exploration of the various Raman wavelengths to identify the ideal instrument settings for UOC sample interrogation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Automatic microseismic event picking via unsupervised machine learning

SUMMARY Effective and efficient arrival picking plays an important role in microseismic and earthquake data processing and imaging. Widely used short-term-average long-term-average ratio (STA/LTA) based arrival picking algorithms suffer from the sensitivity to moderate-to-strong random ambient noise. To make the state-of-the-art arrival picking approaches effective, microseismic data need to be first pre-processed, for example, removing sufficient amount of noise, and second analysed by arrival pickers. To conquer the noise issue in arrival picking for weak microseismic or earthquake event, I leverage the machine learning techniques to help recognizing seismic waveforms in microseismic or earthquake data. Because of the dependency of supervised machine learning algorithm on large volume of well-designed training data, I utilize an unsupervised machine learning algorithm to help cluster the time samples into two groups, that is, waveform points and non-waveform points. The fuzzy clustering algorithm has been demonstrated to be effective for such purpose. A group of synthetic, real microseismic and earthquake data sets with different levels of complexity show that the proposed method is much more robust than the state-of-the-art STA/LTA method in picking microseismic events, even in the case of moderately strong background noise.

Chen, Yangkang↗
DOE OSTI2018

The clustering of theSDSS-IV extended Baryon Oscillation Spectroscopic Survey DR14 quasar sample: measuring the anisotropic baryon acoustic oscillations with redshift weights

We present an anisotropic analysis of baryon acoustic oscillation (BAO) signal from the Sloan Digital Sky Survey IV extended Baryon Oscillation Spectroscopic Survey Data Release 14 quasar sample. The sample consists of 147 000 quasars distributed over a redshift range of 0.8 < z < 2.2. We apply the redshift weights technique to the clustering of quasars in this sample and achieve a 4.6 per cent measurement of the angular distance measurement DM at z = 2.2 and Hubble parameter H at z = 0.8. We parametrize the distance-redshift relation, relative to a fiducial model, as a Taylor series. The coefficients of this expansion are used to reconstruct the distance-redshift relation and obtain distance and Hubble parameter measurements at all redshifts within the redshift range of the sample. Reporting the result at two characteristic redshifts, we determine DM(z = 1) = 3405 ± 305 (rd/rd, fid) Mpc, H(z=1) = 120.7± 7.3 (r_d,fid / r_d) km s^{-1} Mpc^{-1} and DM(z = 2) = 5325 ± 249 (rd/rd, fid) Mpc, H(z=2) = 189.9± 32.9 (r_d,fid / r_d) km s^{-1} Mpc^{-1}. These measurements are highly correlated. We assess the outlook of BAO analysis from the final quasar sample by testing the method on a set of mocks that mimic the noise level in the final sample. We demonstrate on these mocks that redshift weighting shrinks the measurement error by over 25 per cent on average. We conclude redshift weighting can bring us closer to the cosmological goal of the final quasar sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Population of the giant pairing vibration

Background: We present that the giant pairing vibration (GPV), a correlated two-nucleon mode in the second shell above the Fermi surface, has long been predicted and expected to be strongly populated in two-nucleon transfer cross sections similar to those of the normal pairing vibration. Recent experiments have provided evidence for this mode in 14,15 C but, despite sensitive studies, it has not been definitively identified in either Sn or Pb nuclei where pairing correlations are known to play a crucial role. Purpose: Our aim is to test whether features inherent to the mixing of bound and unbound levels might account for this and to study the effect in a simple and intuitively clear approach. Method: We study the mixing of unbound levels in a set of toy models that capture the essential physics of the GPV, along with a more realistic calculation including distorted-wave Born approximation transfer amplitudes. Results: The calculated (relative) cross section to populate a simulated GPV state is effectively low, compared to the case of bound levels with no widths Conclusions: The mixing turns out to be only a minor contributor to the weak population. Rather, the main reason is the melting of the GPV peak due to the width it acquires from the low orbital angular momentum single-particle states playing a dominant role in two-nucleon transfer amplitudes. Lastly, this effect, in addition to a severe Q-value mismatch, may account for the elusive nature of this mode in (t,p) and (p,t) reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1986

Improved Technique for Finding Vibration Parameters

Filtering and sample manipulation reduce noise effects. Analysis technique improves extraction of vibrational frequencies and damping rates from measurements of vibrations of complicated structure. Structural vibrations measured by accelerometers. Outputs digitized at frequency high enough to cover all modes of interest. Use of method on set of vibrational measurements from Space Shuttle, raised level of coherence from previous values below 50 percent to values between 90 and 99 percent

Andrew, L. V.↗