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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Frequency Domain Methodology for Quantitative Evaluation of Diffuse Wavefield With Applications to Seismic Imaging

Abstract Ambient Noise Imaging (ANI) of subsurface structures relies on seismic interferometry of diffuse seismic wavefields. However, the lack of effective methods to quantify and identify highly diffuse waves hampers applications of ANI, particularly in evaluating seismic attenuation and monitoring structural changes with high temporal resolution. Conventional ANI approaches require data normalization, which effectively suppresses the non‐diffuse component with large amplitude but also results in significant loss of amplitude and phase information in the continuous seismic records. In this study, we propose a frequency domain method to quantitatively evaluate the degree of diffuseness of seismic wavefields by analyzing their statistical characteristics of modal amplitudes for stationarity and randomness. Tests on synthetic waveform and field nodal records show that the proposed method can effectively distinguish between diffuse and non‐diffuse waveforms for either single‐ or three‐component data. As an application, we identify a 60‐s‐long diffuse coda of a local M 2.2 earthquake recorded by a dense nodal array on the San Jacinto Fault Zone, and successfully extract high‐quality dispersion curve andQ‐value without performing data normalization. These results are consistent with those obtained by conventional methods that assess the correlation between coherency and the Green's function, and by modeling ballistic waves generated by road traffic. Our proposed method can advance the imaging of subsurface velocity and attenuation structures as well as monitoring temporal changes for scientific studies and engineering applications.

Geochemistry & Geophysics↗
NASA NTRS2002

The Development and Application of a Method to Quantify the Quality of Cryoprotectant Conditions Using Standard Area Detector X-Ray Images

An X-ray based method for determining cryoprotectant concentrations necessary to protect solutions from crystalline ice formation was developed. X-ray images from a CCD area detector were integrated as powder patterns and quantified by determining the standard deviation of the slope of the normalized intensity curve in the resolution range where ice rings are known to occur. The method was tested determining the concentrations of glycerol, PEG400, ethylene glycol and 1,2-propanediol necessary to form an amorphous glass at 1OOK with each of the 98 crystallization solutions of Crystal Screens I and II (Hampton Research, Laguna Hills, California, USA). For conditions that required glycerol concentrations of 35% or above cryoprotectant conditions using 2,3-butanediol were determined. The method proved to be remarkably accurate. The results build on the work of [Garman and Mitchell] and extend the number, of suitable starting conditions to alternative cryoprotectants. In particular, 1,2-propanediol has emerged as a particularly good additive for glass formation upon flash cooling.

McFerrin, Michael↗
DOE OSTI2024

Anisotropic physics-regularized interpretable machine learning of microstructure evolution

Anisotropic Physics-Regularized Interpretable Machine Learning Microstructure Evolution (APRIMME) is a general-purpose machine learning solution for grain growth simulations. In prior work, PRIMME employed a deep neural network to predict site-specific migration as a function of its neighboring sites to model normal, isotropic, grain growth behavior. This work aims to extend this method by incorporating grain boundary misorientation-based grain growth behavior. APRIMME is trained on anisotropic simulations created using the Monte Carlo-Potts (MCP) model. Furthermore, the results of this work are compared statistically using grain radius, number of sides per grain, mean neighborhood misorientations, and the standard deviation of triple junction dihedral angles, and are found to match in most cases. The exceptions are small and seem to be related to two causes: (1) the deterministic model of APRIMME is learning from the stochastic simulations of MCP, which seems to accentuate triple junction behaviors; and, (2) a bias against very small grains is made evident in a quicker decrease in grains than expected at the beginning of an APRIMME simulation. APRIMME is also evaluated for its general ability to capture anisotropic grain growth behavior by first investigating different test case initial conditions, including a circle grain, three grain, and hexagonal grain microstructures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Block Design with Common Reference Samples Enables Robust Large-Scale Label-Free Quantitative Proteome Profiling

Label-free quantitative proteomics has become an increasingly popular tool for profiling global protein abundances. However, one major weakness is the potential performance drift of the LC-MS platform over time, which in turn limits its utility for analyzing large-scale sample sets. To address this, in this work we introduce an experimental and data analysis scheme based on a block-design with common controls within each block for enabling LC-MS-based large-scale label-free quantification. In this scheme, a large number of samples (e.g., >100 samples) are analyzed in smaller, and more manageable blocks, minimizing instrument drift and variability within a block. Furthermore, each designated block also contains common controls (or reference) samples for normalization within and across blocks. We demonstrated the effectiveness of this method by profiling the proteome response of human macrophage THP-1 cells to 11 engineered nanomaterials (ENMs) at two different doses. A total of 116 samples were analyzed in six blocks, yielding an average coverage of 4500 proteins per sample. The data revealed consistent quantification of proteins across all six blocks, as shown by highly stable quantification of house-keeping proteins in all samples and high levels of quantification correlation among samples from different blocks. The data also demonstrated that label-free quantification is robust and accurate enough to quantify even very subtle abundance changes as well as large fold-changes without potential ratio compression as often encountered with isobaric labeling. Our streamlined workflow is easy to implement and can be readily adapted to other large cohort studies for reproducible label-free proteome quantification.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Strain-Induced Lateral Heterostructures in Patterned Semiconductor Nanomembranes for Micro- and Optoelectronics

The ability to tailor the energy band lineup of semiconductor materials plays a key role in the development of many electronic and optoelectronic devices and normally relies on heteroepitaxy. In this work, we report a different method, based on strain engineering, for the controlled introduction of variations in bandgap energy with lateral position in thin films. External stress is applied on Ge nanomembranes stacked with an array of amorphous-Si pillars in order to create a non-uniform strain (and therefore bandgap energy) distribution commensurate with the sample thickness variations. The resulting strain profiles are mapped using Bragg diffraction with a hard X-ray probe featuring nanoscale spatial resolution. Compared with traditional heterostructures grown by epitaxial techniques, these strain-engineered samples involve a single chemical composition and are not limited in the choice of compatible materials by any restriction imposed by lattice-matching requirements. Furthermore, their energy band lineups can be patterned in nearly arbitrary shapes using nanolithography to control the thickness profile and can be tuned actively by varying the applied stress. As a result, these structures are attractive for a wide range of device applications (including lasers, LEDs, solar cells, and thermoelectrics) that require complex heterostructure lineups with multiple bandgap energies.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Neutrino-induced charged-current coherent pion production for constraining the muon neutrino flux at DUNE

We study neutrino-induced charged-current coherent pion production ( ν μ CC - Coh π ) as a tool for constraining the neutrino flux at the Deep Underground Neutrino Experiment (DUNE). The neutrino energy and flavor in the process can be directly reconstructed from the outgoing particles, making it especially useful to specifically constrain the muon neutrino component of the total flux. The cross section of this process can be obtained using the Adler relation with the π -Ar elastic scattering cross section taken either from external data or, as we explore, from a simultaneous measurement in the DUNE near detector. We develop a procedure that leverages ν μ CC - Coh π events to fit for the neutrino flux while simultaneously accounting for relevant effects in the cross section. We project that this method has the statistical power to constrain the uncertainty on the normalization of the flux at its peak to a few percent. This study demonstrates the potential utility of a ν μ CC - Coh π flux constraint, though further work will be needed to determine the range of validity and precision of the Adler relation upon which it relies, as well as to measure the π -Ar elastic scattering cross section to the requisite precision. We discuss the experimental and phenomenological developments necessary to unlock the ν μ CC - Coh π process as a “standard candle” for neutrino experiments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Towards scanning nanostructure X-ray microscopy

This article demonstrates spatial mapping of the local and nanoscale structure of thin film objects using spatially resolved pair distribution function (PDF) analysis of synchrotron X-ray diffraction data. This is exemplified in a lab-on-chip combinatorial array of sample spots containing catalytically interesting nanoparticles deposited from liquid precursors using an ink-jet liquid-handling system. A software implementation is presented of the whole protocol, including an approach for automated data acquisition and analysis using the atomic PDF method. The protocol software can handle semi-automated data reduction, normalization and modeling, with user-defined recipes generating a comprehensive collection of metadata and analysis results. By slicing the collection using included functions, it is possible to build images of different contrast features chosen by the user, giving insights into different aspects of the local structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Wassersplines for Neural Vector Field-Controlled Animation

Much of computer-generated animation is created by manipulating meshes with rigs. While this approach works well for animating articulated objects like animals, it has limited flexibility for animating less structured free-form objects. Here we introduce Wassersplines, a novel trajectory inference method for animating unstructured densities based on recent advances in continuous normalizing flows and optimal transport. The key idea is to train a neurally-parameterized velocity field that represents the motion between keyframes. Trajectories are then computed by advecting keyframes through the velocity field. We solve an additional Wasserstein barycenter interpolation problem to guarantee strict adherence to keyframes. Our tool can stylize trajectories through a variety of PDE-based regularizers to create different visual effects. We demonstrate our tool on various keyframe interpolation problems to produce temporally-coherent animations without meshing or rigging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Activated KCNQ1 channel promotes fibrogenic response in hereditary gingival fibromatosis via clustering and activation of Ras

Abstract Background and Objective Activated potassium channels were found to be strongly correlated with gingival overgrowth (GO) phenotype as we reviewed syndromic hereditary gingival fibromatosis (HGF). Nevertheless, the functional roles of potassium channels in gingival fibrosis or gingival overgrowth remained uncovered. The aim of the present study was to explore the pathogenic role of aberrantly activated potassium channel in Hereditary Gingival Fibromatosis (HGF). Methods Gingival tissues were collected from 9 HGF patients and 15 normal controls. Expression of KCNQ1 was detected by immunohistochemistry. Gingival fibroblasts were isolated, and outward K + currents were detected by whole‐cell patch‐clamp analysis, transmembrane potential was determined by flow cytometry. Normal human gingival fibroblasts (NHGFs) were transfected with KCNQ1 adenovirus or treated with KCNQ1 selective agonist ML277 and antagonist chromanol 293B. Accumulation of Extracellular Matrix (ECM) was measured by Western blotting and Sircol Soluble Collagen Assay. Content of secreted TGF‐β1 was measured by ELISA. Active RAS pull‐down assay and cell immunofluorescence were utilized to verify RAS activation. Results KCNQ1 was upregulated in gingival tissues derived from HGF patients and HGF gingival fibroblasts presented increased outward K + currents than NHGFs. Overexpression of KCNQ1, or KCNQ1 agonist ML277, promoted fibrotic responses of NHGFs. TGF‐β1 and KCNQ1 channels formed a positive feed‐back loop. ML277 generated lateral clustering and activation of Ras on plasma membrane, followed by augmented MAPK/AP‐1 signaling pathway output. JNK or ERK1/2 inhibitors suppressed ML277‐induced AP‐1 and ECM upregulation. Conclusion Activation of KCNQ1 potassium channel promoted fibrogenic responses in NHGFs via Ras/MAPK/AP‐1 signaling.

Gao, Qian↗
DOE OSTI2023

Aspects of scaling and scalability for flow-based sampling of lattice QCD

Recent applications of machine-learned normalizing flows to sampling in lattice field theory suggest that such methods may be able to mitigate critical slowing down and topological freezing. However, these demonstrations have been at the scale of toy models, and it remains to be determined whether they can be applied to state-of-the-art lattice quantum chromodynamics calculations. Assessing the viability of sampling algorithms for lattice field theory at scale has traditionally been accomplished using simple cost scaling laws, but as we discuss in this work, their utility is limited for flow-based approaches. We conclude that flow-based approaches to sampling are better thought of as a broad family of algorithms with different scaling properties, and that scalability must be assessed experimentally.

Abbott, Ryan↗
DOE OSTI2021

Demonstration of MELCOR and MACCS Capabilities for Molten Salt Reactor Decay Heat Removal During both Normal Operations and Salt Spill Scenarios

This report provides a demonstration of MELCOR and MELCOR Accident Consequence Code System (MACCS) capabilities to perform a dose assessment for a Molten Salt Reactor (MSR) off-gas system. A primary containment system salt spill is used as the off-normal scenario, along with a normal operation dose assessment for comparison. This report discusses the tools, methods, and information used in this assessment so that it may be utilized as a starting point for future advanced reactor consequence analyses. This report also highlights several gaps, to include the need for reactor inventory information specific to advanced reactors, and the need for specific atmospheric transport models that take into account the unique deposition behaviors of tritium and carbon-14, and makes recommendations for closing these gaps. This report satisfies the DOE NE Milestone M4RD-21SN0601062.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Application of Shift Ex-Core Calculations to a Detailed MSR Model

This report documents the collaborative research conducted between Argonne National Laboratory (ANL) and Oak Ridge National Laboratory (ORNL) on applying the Monte Carlo neutronics code Shift to calculate the radiation dose rates for a detailed molten salt reactor (MSR) model based on the Molten Salt Breeder Reactor (MSBR). In this work scope, the ANL and ORNL teams worked together and applied Shift to calculate the radiological environments of this detailed MSR facility modeled with explicit geometries. The radiological conditions within the MSR facility were modeled for when the reactor is at two different operation modes: normal full power and drained state. The FW-CADIS hybrid method in Shift was applied successfully to calculate the ex-core neutron and gamma dose rates for the MSBR at full power. Dose rate maps showed that in the current MSBR numerical model, potential pathways exist for neutrons and gammas to stream through the 8-foot concrete shield to reach the top of the MSBR reactor cell. Neutron and gamma dose rates within the drain cell were also calculated for the MSBR at the drained state by integrating the source terms obtained from an ORIGEN-S depletion calculation into the Shift simulation. The results indicate that in the drained state, the delayed gammas from the depleted fuel salt are the main contributors to the dose rates, which suggests that a steel liner in the tank model must be added for calculating the dose rates in the drain cell.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Neutrino Induced Charged Current Coherent Pion Production for Constraining the Muon Neutrino Flux at DUNE

We study neutrino induced charge current coherent pion production (νμ CC-Coh π) as a tool for constraining the neutrino flux at the Deep Underground Neutrino Experiment (DUNE). The neutrino energy and flavor in the process can be directly reconstructed from the outgoing particles, making it especially useful to specifically constrain the muon neutrino component of the total flux. The cross section of this process can be obtained using the Adler relation with the π-Ar elastic scattering cross section, taken either from external data or, as we explore, from a simultaneous measurement in the DUNE near detector. We develop a procedure that leverages νμ CC-Coh π events to fit for the neutrino flux while simultaneously accounting for relevant effects in the cross section. We project that this method has the statistical power to constrain the uncertainty on the normalization of the flux at its peak to a few percent. This study demonstrates the potential utility of aνμ CC-Coh π flux constraint, though further work will be needed to determine the range of validity and precision of the Adler relation upon which it relies, as well as to measure the π-Ar elastic scattering cross section to the requisite precision. We discuss the experimental and phenomenological developments necessary to unlock the νμ CC-Coh π process as a "standard candle'' for neutrino experiments.

Putnam, Gray [Fermilab]↗
DOE OSTI2023

Physics guided machine learning for multi-material decomposition of tissues from dual-energy CT scans of simulated breast models with calcifications

We introduce a physics guided data-driven method for image-based multi-material decomposition for dual-energy computed tomography (CT) scans. The method is demonstrated for CT scans of virtual human phantoms containing more than two types of tissues. The method is a physics-driven supervised learning technique. We take advantage of the mass attenuation coefficient of dense materials compared to that of muscle tissues to perform a preliminary extraction of the dense material from the images using unsupervised methods. We then perform supervised deep learning on the images processed by the extracted dense material to obtain the final multi-material tissue map. The method is demonstrated on simulated breast models with calcifications as the dense material placed amongst the muscle tissues. The physics-guided machine learning method accurately decomposes the various tissues from input images, achieving a normalized root-mean-squared error of 2.75%.

Gopalakrishnan Meena, Murali↗
DOE OSTI2024

Estimating snow cover from high-resolution satellite imagery by thresholding blue wavelengths: Supporting Data

The extent and duration of snow cover is predicted to be altered as the climate changes. Developing high-resolution estimates of snow cover change is crucial for estimating changes in snow cover and the effects of these changes on watershed and ecosystems processes. Remote sensing tools have been a common method for rapidly mapping snow covered area (SCA) across a landscape. The most common remote sensing method for estimating SCA uses satellite-based calculations of the normalized difference snow index (NDSI), which relies on spectral measurements in the shortwave-infrared wavelengths (SWIR). NDSI is effective at catchment- to regional-scale estimates of SCA, but due to spatial resolution limitations of SWIR measurements, NDSI cannot be used to assess fine-scale SCA. In this work, we develop a new algorithm, called the Blue Snow Threshold (BST) algorithm, that maps high-resolution SCA by calculating a threshold on the blue wavelengths from high-resolution satellite imagery. This data package includes Orthorectified IKONOS-2 imagery (IkonosTestImage.tif) from August 14, 2004 at 1.00 meters Ground Sample Distance for Cook Inlet, Alaska (59.966414 , -152.982975). The Blue Snow Threshold algorithm (BST.py) was then used to produce a snow cover estimate (IkonosTestImage_BST.tif) for this study area. Additional imagery metadata is included in the ImageInfo.txt file. See Thaler et al., 2023 (https://doi.org/10.1016/j.rse.2022.113403) for more information about the BST algorithm.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

On pursuit with curvature constraints.

A theorem is proved extending results of Cockayne on pursuit with curvature constraints. Let two points (pursuer and evader) move in Euclidean 3-space with constant speeds. Provided the pursuer has greater speed and greater normal acceleration, it is shown that pursuit is always successful. The methods used are similar to Cockayne's. The pursuer, by some preliminary maneuvers, sets up a condition where he is leaving the line of sight in the same direction and with the same speed as the evader. It is shown that from this instant, the pursuer can, without violating constraints, keep the line of sight parallel to the original and ultimately collide with the evader.

Rublein, G. T.↗
NASA NTRS1973

Breeding monkeys for biomedical research

Captive bred rhesus monkeys show much less pathology than wild born animals. The monkeys may be bred in cages or in an outdoor compound. Cage bred animals are not psychologically normal which makes then unsuited for some types of space related research. Compound breeding provides contact between mother and infant and an opportunity for the infants to play with their peers which are important requirements to help maintain their behavioral integrity. Offspring harvested after a year in the compound appear behaviorally normal and show little histopathology. Compound breeding is also an economical method for the rapid production of young animals. The colony can double its size about every two and a half years.

Bourne, G. H.↗
NASA NTRS1974

Experimental determination of the principal moments of inertia of the Helios prototype spacecraft

The moment of inertia of the Helios Spacecraft about its spin axis was determined by use of a roll-fixture using two sets of crossed flexure pivots as elastic constraints. The test procedure entailed measurement of a system oscillation period with each of a set of added moment-of-inertia increments. The tare effect of the fixture was determined by a like process and was subtracted from the gross value to yield the spacecraft roll moment of inertia to an estimated accuracy of 0.2%. Lateral moments of inertia (i.e., about each of three axes normal to the spin axis) were determined by a gravity pendulum method that makes use of the fact that any physical pendulum has a minimum period of oscillation determined by a particular distance from the axis of rotation to the system center of gravity.

Gayman, W. H.↗