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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Bayesian analysis of rare events

In many areas of engineering and science there is an interest in predicting the probability of rare events, in particular in applications related to safety and security. Increasingly, such predictions are made through computer models of physical systems in an uncertainty quantification framework. Additionally, with advances in IT, monitoring and sensor technology, an increasing amount of data on the performance of the systems is collected. This data can be used to reduce uncertainty, improve the probability estimates and consequently enhance the management of rare events and associated risks. Bayesian analysis is the ideal method to include the data into the probabilistic model. It ensures a consistent probabilistic treatment of uncertainty, which is central in the prediction of rare events, where extrapolation from the domain of observation is common. We present a framework for performing Bayesian updating of rare event probabilities, termed BUS. It is based on a reinterpretation of the classical rejection-sampling approach to Bayesian analysis, which enables the use of established methods for estimating probabilities of rare events. By drawing upon these methods, the framework makes use of their computational efficiency. These methods include the First-Order Reliability Method (FORM), tailored importance sampling (IS) methods and Subset Simulation (SuS). In this contribution, we briefly review these methods in the context of the BUS framework and investigate their applicability to Bayesian analysis of rare events in different settings. We find that, for some applications, FORM can be highly efficient and is surprisingly accurate, enabling Bayesian analysis of rare events with just a few model evaluations. In a general setting, BUS implemented through IS and SuS is more robust and flexible.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Planck 2015 results: XVI. Isotropy and statistics of the CMB

In this paper, we test the statistical isotropy and Gaussianity of the cosmic microwave background (CMB) anisotropies using observations made by the Planck satellite. Our results are based mainly on the full Planck mission for temperature, but also include some polarization measurements. In particular, we consider the CMB anisotropy maps derived from the multi-frequency Planck data by several component-separation methods. For the temperature anisotropies, we find excellent agreement between results based on these sky maps over both a very large fraction of the sky and a broad range of angular scales, establishing that potential foreground residuals do not affect our studies. Tests of skewness, kurtosis, multi-normality, N-point functions, and Minkowski functionals indicate consistency with Gaussianity, while a power deficit at large angular scales is manifested in several ways, for example low map variance. The results of a peak statistics analysis are consistent with the expectations of a Gaussian random field. The “Cold Spot” is detected with several methods, including map kurtosis, peak statistics, and mean temperature profile. We thoroughly probe the large-scale dipolar power asymmetry, detecting it with several independent tests, and address the subject of a posteriori correction. Tests of directionality suggest the presence of angular clustering from large to small scales, but at a significance that is dependent on the details of the approach. We perform the first examination of polarization data, finding the morphology of stacked peaks to be consistent with the expectations of statistically isotropic simulations. Finally, where they overlap, these results are consistent with the Planck 2013 analysis based on the nominal mission data and provide our most thorough view of the statistics of the CMB fluctuations to date.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Investigation on Physical Properties of Sn-Modified Cubic Cu{sub 2}O Nanostructures

Cubic Cu{sub 2−x} Sn{sub x}O (0 ≤ x ≤ 0.4) nanostructures have been developed with the solvothermal method. X-ray diffraction data analysis confirms the formation of a pristine Cu{sub 2}O phase below x=0.3 Sn{sup 2+} substitution, and SnO-related phases appear in 0.3 substitute sample indicating phase segregation starts at x≥0.3. The magnetization versus applied field (M − H) curves have been determined using a vibrating sample magnetometer at 300 K which reveals that ferromagnetic behavior of synthesized nanomaterials is reliant on the substituent concentration and enhanced gradually with its addition in the material. Photoluminescence spectra show that ferromagnetism originates from the induced magnetic moment in defects created as cation vacancies in the host material. Beside these, the dielectric measurements were performed at various frequencies (20 Hz–1 MHz) and in the temperature range of 100 to 350 K.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

High-Content Clonogenic Survival Screen to Identify Chemoradiation Sensitizers

The combination of cytotoxic chemotherapy with radiation therapy (CRT) has resulted in significant improvements in clinical outcomes for patients with many locally advanced unresectable cancers. Only a small proportion of patients achieve pathologic complete responses to CRT; combination of CRT with targeted agents offers the promise of further improving treatment responses. However, numerous clinical trials have failed to show an improvement in clinical outcomes with the addition of targeted agents. To increase the accessibility of our screening method and accelerate the pace at which novel combinations with CRT are identified and incorporated into standard practices for treatments, we report details on screening method optimization, data generation, and downstream data analysis.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

Synthesis, characterization and thermochemistry of Cs-, Rb- and Sr-substituted barium aluminium titanate hollandites

Titanate hollandites are of considerable interest for immobilization of radioactive Cs, its daughter product Ba and related radionuclides Rb and Sr. In this work, we synthesized three hollandites, Ba 1.18 Cs 0.21 Al 2.44 Ti 5.53 O 16 , Ba 1.17 Rb 0.19 Al 2.46 Ti 5.53 O 16 and Ba 1.14 Sr 0.10 Al 2.38 Ti 5.59 O 16 , using sol–gel methods. Rietveld analysis of synchrotron XRD data shows that they adopt the tetragonal structure (space group I4/m ), and their cell parameters increase with increasing cation size (Sr 2+ → Rb + → Cs + ). Standard enthalpies of formation of these hollandites were determined from drop solution calorimetric measurements with lead borate as the solvent at 973 K. Their formation enthalpies are similar, consistent with the occurrence of extensive cation substitutions in hollandites. Further energetic analysis with respect to BaTiO 3 and SrTiO 3 perovskites and other oxides reveals decreased thermodynamic stability from Cs- to Rb- to Sr-hollandite. Lastly, this trend is consistent with the phase assemblage observed in Synroc, where Cs + , Rb + and Ba 2+ enter into hollandite, whereas Sr 2+ occurs in perovskite.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Structural analysis of Fe–Mn–O nanoparticles in glass ceramics by small angle scattering

Magnetic nanocrystals containing Fe and Mn were obtained by annealing of silicate glasses with the composition 13.6Na{sub 2}O–62.9SiO{sub 2}–8.5MnO–15.0Fe{sub 2}O{sub 3−x} (mol%) at 580 °C for different periods of time. Here, we present Small Angle Neutron Scattering using Polarized neutrons (SANSPOL) and Anomalous Small Angle X-ray Scattering (ASAXS) investigation on these glass ceramic samples. Analysis of scattering data from both methods reveals the formation of spherical core–shell type of nanoparticles with mean sizes between 10 nm and 100 nm. ASAXS investigation shows the particles have higher concentration of iron atoms and the shell like region surrounding the particles is enriched in SiO{sub 2}. SANSPOL investigation shows the particles are found to be magnetic and are surrounded by a non-magnetic shell-like region. - Graphical abstract: Magnetic spherical core–shell nanoparticles in glass ceramics: SANSPOL and ASAXS investigations. - Highlights: • Formation and growth mechanisms of magnetic nanoparticles in silicate glass. • SANSPOL and ASAXS methods employed to evaluate quantitative information. • Analyses showed formation of nanoparticles with spherical core–shell structures. • Core of the particle is magnetic and surrounded by weak magnetic shell like region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Statistical characterization of experimental magnetized liner inertial fusion stagnation images using deep-learning-based fuel–background segmentation

Significant variety is observed in spherical crystal x-ray imager (SCXI) data for the stagnated fuel–liner system created in Magnetized Liner Inertial Fusion (MagLIF) experiments conducted at the Sandia National Laboratories Z-facility. As a result, image analysis tasks involving, e.g., region-of-interest selection (i.e. segmentation), background subtraction and image registration have generally required tedious manual treatment leading to increased risk of irreproducibility, lack of uncertainty quantification and smaller-scale studies using only a fraction of available data. We present a convolutional neural network (CNN)-based pipeline to automate much of the image processing workflow. This tool enabled batch preprocessing of an ensemble of N scans = 139 SCXI images across N exp = 67 different experiments for subsequent study. The pipeline begins by segmenting images into the stagnated fuel and background using a CNN trained on synthetic images generated from a geometric model of a physical three-dimensional plasma. The resulting segmentation allows for a rules-based registration. Our approach flexibly handles rarely occurring artifacts through minimal user input and avoids the need for extensive hand labelling and augmentation of our experimental dataset that would be needed to train an end-to-end pipeline. Here we also fit background pixels using low-degree polynomials, and perform a statistical assessment of the background and noise properties over the entire image database. Our results provide a guide for choices made in statistical inference models using stagnation image data and can be applied in the generation of synthetic datasets with realistic choices of noise statistics and background models used for machine learning tasks in MagLIF data analysis. We anticipate that the method may be readily extended to automate other MagLIF stagnation imaging applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Machine learning of high dimensional data on a noisy quantum processor

Abstract Quantum kernel methods show promise for accelerating data analysis by efficiently learning relationships between input data points that have been encoded into an exponentially large Hilbert space. While this technique has been used successfully in small-scale experiments on synthetic datasets, the practical challenges of scaling to large circuits on noisy hardware have not been thoroughly addressed. Here, we present our findings from experimentally implementing a quantum kernel classifier on real high-dimensional data taken from the domain of cosmology using Google’s universal quantum processor, Sycamore. We construct a circuit ansatz that preserves kernel magnitudes that typically otherwise vanish due to an exponentially growing Hilbert space, and implement error mitigation specific to the task of computing quantum kernels on near-term hardware. Our experiment utilizes 17 qubits to classify uncompressed 67 dimensional data resulting in classification accuracy on a test set that is comparable to noiseless simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Temperature Dependence in Heterogeneous Nucleation with Application to the Direct Determination of Cluster Energy on Nearly Molecular Scale

A re-examination of measurements of heterogeneous nucleation of water vapor on silver nanoparticles is presented here using a model-free framework that derives the energy of critical cluster formation directly from measurements of nucleation probability. Temperature dependence is correlated with cluster stabilization by the nanoparticle seed and previously found cases of unusual increasing nucleation onset saturation ratio with increasing temperature are explained. A necessary condition for the unusual positive temperature dependence is identified, namely that the critical cluster be more stable, on a per molecule basis, than the bulk liquid to exhibit the effect. Temperature dependence is next examined in the classical Fletcher model, modified here to make the energy of cluster formation explicit in the model. The contact angle used in the Fletcher model is identified as the microscopic contact angle, which can be directly obtained from heterogeneous nucleation experimental data by a recently developed analysis method. Here an equivalent condition, increasing contact angle with temperature, is found necessary for occurrence of unusual temperature dependence. Our findings have immediate applications to atmospheric particle formation and nanoparticle detection in condensation particle counters (CPCs).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Designing optical metamaterial with hyperbolic dispersion based on Al:ZnO/ZnO nano-layered structure using Atomic Layer Deposition technique

In this study, nano-layered Al:ZnO/ZnO hyperbolic dispersion metamaterial with a large number of layers was fabricated using the atomic layer deposition (ALD) technique. Experimental dielectric functions for Al:ZnO/ZnO structures are obtained by an ellipsometry technique in the visible and near-infrared spectral ranges. The theoretical modeling of the Al:ZnO/ZnO dielectric permittivity is done using effective medium approximation. A method for analysis of spectroscopic ellipsometry data is demonstrated to extract the optical permittivity for this highly anisotropic nano-layered metamaterial. The results of the ellipsometry analysis show that Al:ZnO/ZnO structures with a 1:9 ALD cycle ratio exhibit hyperbolic dispersion transition change near 1.8 μm wavelength.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2016

Permafrost Active Layer Seismic Interferometry Experiment (PALSIE).

We present findings from a novel field experiment conducted at Poker Flat Research Range in Fairbanks, Alaska that was designed to monitor changes in active layer thickness in real time. Results are derived primarily from seismic data streaming from seven Nanometric Trillium Posthole seismometers directly buried in the upper section of the permafrost. The data were evaluated using two analysis methods: Horizontal to Vertical Spectral Ratio (HVSR) and ambient noise seismic interferometry. Results from the HVSR conclusively illustrated the method's effectiveness at determining the active layer's thickness with a single station. Investigations with the multi-station method (ambient noise seismic interferometry) are continuing at the University of Florida and have not yet conclusively determined active layer thickness changes. Further work continues with the Bureau of Land Management (BLM) to determine if the ground based measurements can constrain satellite imagery, which provide measurements on a much larger spatial scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Distributed Acoustic Sensing (DAS) on Opportunistic Networks_ A Feasibility Study Utilizing Fiber Optic Infrastructure at NEON Sites for DAS

This study demonstrates the feasibility of using Distributed Acoustic Sensing (DAS) on the opportunistic optical fiber infrastructure presented by NEON (National Ecological Observatory Network) sites. The test took place at the NEON Terrestrial Site designated D10 CPER. Unlit portions of the local fiber network were successfully spliced together and optimized for length and a Silixa iDAS sensor was installed. The resulting array (composed of 12 spliced fiber runs) totaled 875m in length. Over a period of 2 weeks, we gathered a high spatial and temporal resolution data set to characterize discernable signals and understand background noise. The data set was reviewed to extract wave signatures of identifiable origin, both anthropogenic and otherwise. Continent wide distribution of these sites makes them an interesting candidate for DAS and identifying measurable signal sources informs future DAS application on opportunistic fiber networks. These observations validate the utility of both the NEON and similarly small fiber networks (<1km) for geoscience, environmental, and security DAS applications and indicate possibilities for further inquiry in methods for DAS data collection and analysis.

42 ENGINEERING↗
DOE OSTI2021

Critical Infrastructure Decision-Making under Long-Term Climate Hazard Uncertainty: The Need for an Integrated, Multidisciplinary Approach

U.S. critical infrastructure assets are often designed to operate for decades, and yet long-term planning practices have historically ignored climate change. With the current pace of changing operational conditions and severe weather hazards, research is needed to improve our ability to translate complex, uncertain risk assessment data into actionable inputs to improve decision-making for infrastructure planning. Decisions made today need to explicitly account for climate change – the chronic stressors, the evolution of severe weather events, and the wide-ranging uncertainties. If done well, decision making with climate in mind will result in increased resilience and decreased impacts to our lives, economies, and national security. We present a three-tier approach to create the research products needed in this space: bringing together climate projection data, severe weather event modeling, asset-level impacts, and contextspecific decision constraints and requirements. At each step, it is crucial to capture uncertainties and to communicate those uncertainties to decision-makers. While many components of the necessary research are mature (i.e., climate projection data), there has been little effort to develop proven tools for long-term planning in this space. The combination of chronic and acute stressors, spatial and temporal uncertainties, and interdependencies among infrastructure sectors coalesce into a complex decision space. By applying known methods from decision science and data analysis, we can work to demonstrate the value of an interdisciplinary approach to climate-hazard decision making for longterm infrastructure planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Comprehensive Chemical Fingerprinting by Multidimensional GC and Supervised Machine Learning

This project leveraged advances in machine learning based data analysis techniques and untargeted analytical methods for organic analysis to progress nuclear nonproliferation technologies beyond current capabilities. The developed approaches can be used to detect and identify complex chemical fingerprints of facilities of interest. These techniques have been developed for fields such as metabolomics and genomics but have not been applied to nuclear nonproliferation applications. Adaptation of these techniques for volatile organic compound analysis has far reaching application within the scientific community including environmental chemistry, atmospheric physics, and climate sciences.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

First Experimental Test of the Ratio Method

The ratio is a new reaction observable suggested to extract accurately structure information on halo nuclei. It corresponds to the ratio of differential cross sections for scattering and breakup, which is predicted to remove the uncertainty related to the reaction dynamics. We present here the first experimental test of the method for the 11 Be + 12 C collision at E Lab = 20A MeV performed at Texas A&M University. Differential cross sections for scattering and inclusive one-neutron breakup have been measured with the new detector array BlueSTEAl. The ratio of cross sections is very smooth and independent of the projectile-target interaction, which demonstrates the validity of the ratio method. We extend our analysis to existing 11 Be + 208 Pb data, confirming that the method works well on any target.

11Be↗