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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 1,441 records · Page 80
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Development and validation of an automatic method to detect the latest contracting viable left ventricular segments to assist guide CRT therapy from gated SPECT myocardial perfusion imaging

Objectives: The purpose of this study is to use ECG-gated SPECT MPI to detect the latest contracting viable left ventricular (LV) segments to help guide the LV probe placement used in CRT therapy and to validate segment selection against the visual integration method by experts. Methods: For each patient, the resting ECG-gated SPECT MPI short-axis images were sampled in 3D to generate a polar map of the perfusion distribution used to determine LV myocardial viability, and to measure LV synchronicity using our phase analysis tool. In the visual integration method, two experts visually interpreted the LV viability and mechanical dyssynchrony from the short-axis images and polar maps of viability and phase, to determine the latest contracting viable segments using the 17-segment model. In the automatic method, the apical segments, septal segments, and segments with more than 50% scar were excluded as these are not candidates for CRT LV probe placement. Amongst the remaining viable segments, the segments, whose phase angles were within 10° of the latest phase angle (the most delayed contracting segment), were identified for potential CRT LV probe placement and ranked based on the phase angles of the segments. Both methods were tested in 36 pre-CRT patients who underwent ECG-gated SPECT MPI. The accuracy was determined as the percent agreement between the visual integration and automatic methods. The automatic method was performed by a second independent operator to evaluate the inter-operator processing reproducibility. Results: In all the 36 patients, the LV lead positions of the 1st choices recommended by the automatic and visual integration methods were in the same segments in 35 patients, which achieved an agreement rate of 97.2%. In the inter-operator reproducibility test, the LV lead positions of the 1st choices recommended by the two operators were in the same segments in 25 patients, and were in the adjacent segments in 7 patients, which achieved an overall agreement of 88.8%. Conclusions: An automatic method has been developed to detect the latest contracting viable LV segments to help guide the LV probe placement used in CRT therapy. The retrospective clinical study with 36 patients suggests that this method has high agreement against the visual integration method by experts and good inter-operator reproducibility. Consequently, this method is promising to be a clinical tool to recommend the CRT LV lead positions.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2003

Preparation of Regular Specimens for Atom Probes

A method of preparation of specimens of non-electropolishable materials for analysis by atom probes is being developed as a superior alternative to a prior method. In comparison with the prior method, the present method involves less processing time. Also, whereas the prior method yields irregularly shaped and sized specimens, the present developmental method offers the potential to prepare specimens of regular shape and size. The prior method is called the method of sharp shards because it involves crushing the material of interest and selecting microscopic sharp shards of the material for use as specimens. Each selected shard is oriented with its sharp tip facing away from the tip of a stainless-steel pin and is glued to the tip of the pin by use of silver epoxy. Then the shard is milled by use of a focused ion beam (FIB) to make the shard very thin (relative to its length) and to make its tip sharp enough for atom-probe analysis. The method of sharp shards is extremely time-consuming because the selection of shards must be performed with the help of a microscope, the shards must be positioned on the pins by use of micromanipulators, and the irregularity of size and shape necessitates many hours of FIB milling to sharpen each shard. In the present method, a flat slab of the material of interest (e.g., a polished sample of rock or a coated semiconductor wafer) is mounted in the sample holder of a dicing saw of the type conventionally used to cut individual integrated circuits out of the wafers on which they are fabricated in batches. A saw blade appropriate to the material of interest is selected. The depth of cut and the distance between successive parallel cuts is made such that what is left after the cuts is a series of thin, parallel ridges on a solid base. Then the workpiece is rotated 90 and the pattern of cuts is repeated, leaving behind a square array of square posts on the solid base. The posts can be made regular, long, and thin, as required for samples for atom-probe analysis. Because of their small volume and regularity, the amount of FIB-milling time can be much less than that of the method of sharp shards. Individual posts can be broken off for mounting in a manner similar to that of the method of sharp shards. Alternatively, the posts can be left intact on the base and the base can be cut to a small square (e.g., 3 by 3 mm) suitable for mounting in an atom probe of a type capable of accepting multiple-tip specimens. The advantage of multiple-tip specimens is the possibility of analyzing many tips without the time-consuming interchange of specimens.

Kuhlman, Kim↗
DOE OSTI2016

DETECTING RELATIVISTIC X-RAY JETS IN HIGH-REDSHIFT QUASARS

We analyze Chandra X-ray images of a sample of 11 quasars that are known to contain kiloparsec scale radio jets. The sample consists of five high-redshift ( z ≥ 3.6) flat-spectrum radio quasars, and six intermediate redshift (2.1 < z < 2.9) quasars. The data set includes four sources with integrated steep radio spectra and seven with flat radio spectra. A total of 25 radio jet features are present in this sample. We apply a Bayesian multi-scale image reconstruction method to detect and measure the X-ray emission from the jets. We compute deviations from a baseline model that does not include the jet, and compare observed X-ray images with those computed with simulated images where no jet features exist. This allows us to compute p -value upper bounds on the significance that an X-ray jet is detected in a pre-determined region of interest. We detected 12 of the features unambiguously, and an additional six marginally. We also find residual emission in the cores of three quasars and in the background of one quasar that suggest the existence of unresolved X-ray jets. The dependence of the X-ray to radio luminosity ratio on redshift is a potential diagnostic of the emission mechanism, since the inverse Compton scattering of cosmic microwave background photons (IC/CMB) is thought to be redshift dependent, whereas in synchrotron models no clear redshift dependence is expected. We find that the high-redshift jets have X-ray to radio flux ratios that are marginally inconsistent with those from lower redshifts, suggesting that either the X-ray emissions are due to the IC/CMB rather than the synchrotron process, or that high-redshift jets are qualitatively different.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Studies of the muon momentum calibration and performance of the ATLAS detector with $pp$ collisions at $\sqrt{s}=13$ TeV

This paper presents the muon momentum calibration and performance studies for the ATLAS detector based on the $pp$ collisions data sample produced at $\sqrt{s}$ = 13 TeV at the LHC during Run 2 and corresponding to an integrated luminosity of 139 fb –1 . An innovative approach is used to correct for potential charge-dependent momentum biases related to the knowledge of the detector geometry, using the $Z$ → $μ^+$ $μ^–$ resonance. The muon momentum scale and resolution are measured using samples of $J/ψ$ → $μ^+$ $μ^–$ and $Z$ → $μ^+$ $μ^–$ events. A calibration procedure is defined and applied to simulated data to match the performance measured in real data. The calibration is validated using an independent sample of $Υ$ → $μ^+$ $μ^–$ events. At the Z ($J/ψ$) peak, the momentum scale is measured with an uncertainty at the 0.05% (0.1%) level, and the resolution is measured with an uncertainty at the 1.5% (2%) level. The charge-dependent bias is removed with a dedicated in situ correction for momenta up to 450 GeV with a precision better than 0.03 TeV –1 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRSDate not supplied

Multiscale Modeling of Reconstructed Tricalcium Silicate using NASA Multiscale Analysis Tool

To study microstructure characteristics of cementitious materials hydrated in space; previously, cement binder formations were processed under microgravity conditions and was further compared against ground-based experiments. For accurate estimation of process-structure-property linkage, particularly on samples hydrated in the microgravity environment, it is desired to have a high-fidelity volumetric representation of the microstructure. However, owing to small sample size and high porosity of the space-returned samples, conventional experimental characterization techniques are not viable. Hence, a deep learning-based reconstruction algorithm was employed to obtain high fidelity 3D volumes from sparse high resolution 2D Scanning Electron Microscopy (SEM) images, as inputs to micromechanics-based modeling. This machine learning-based reconstruction methodology validated against low-order statistical descriptors, captured the microstructural topology of both sample types (ground, 1g and microgravity, μg). Due to the lack of gravity, hydration products of the samples processed in space differed from those processed-on ground. Such AI-generated virtual samples were analyzed in a multiscale recursive micromechanics approach using the NASA Multiscale Analysis Tool (NASMAT). Here, we present a methodology to rapidly integrate and evaluate these AI-generated volumes in NASMAT. The synthesized microstructural volumes are directly employed as Representative Volume Elements (RVEs) to preserve the fidelity (1 pixel = 0.54 m). Invariably, analysis of such largescale problems (5123 voxels) requires huge amount of computational resources. By taking advantage of the NASMAT architecture, we also focused on systematic multiscale integration of these AI-reconstructed virtual volumes to reduce the computational demands. In this work, this methodology is demonstrated on the ground-based, 1g samples. The estimated stiffness value of 15.90 GPa is comparable to experimentally obtained modulus of hydrated tricalcium silicate sample. The workflow presented here paves the way for utilizing the NASMAT tool to perform multiscale analyses of other multi-phase material systems using either 3D virtual datasets synthesized using AI or obtained via micro-CT.

Machine Learning↗
NASA NTRS2016

Cyclotron Resonant Scattering Feature Simulations I. Thermally Averaged Cyclotron Scattering Cross Sections, Mean Free Photon-Path Tables, and Electron Momentum Sampling

Electron cyclotron resonant scattering features (CRSFs) are observed as absorption-like lines in the spectra of X-ray pulsars. A significant fraction of the computing time for Monte Carlo simulations of these quantum mechanical features is spent on the calculation of the mean free path for each individual photon before scattering, since it involves a complex numerical integration over the scattering cross section and the (thermal) velocity distribution of the scattering electrons. We aim to numerically calculate interpolation tables which can be used in CRSF simulations to sample the mean free path of the scattering photon and the momentum of the scattering electron. The tables also contain all the information required for sampling the scattering electron's final spin. The tables were calculated using an adaptive Simpson integration scheme. The energy and angle grids were refined until a prescribed accuracy is reached. The tables are used by our simulation code to produce artificial CRSF spectra. The electron momenta sampled during these simulations were analyzed and justified using theoretically determined boundaries. We present a complete set of tables suited for mean free path calculations of Monte Carlo simulations of the cyclotron scattering process for conditions expected in typical X-ray pulsar accretion columns (0.01 B/B(sub crit) is less than or equal to 0.12, where B(sub crit) = 4.413 x 1013 G, and 3 keV kBT 15 keV). The sampling of the tables is chosen such that the results have an estimated relative error of at most 1/15 for all points in the grid. The tables are available online (see link in footnote, page 1).

Schwarm, F.-W.↗
DOE OSTI2024

Integrated analysis of X-ray diffraction patterns and pair distribution functions for machine-learned phase identification

Abstract To bolster the accuracy of existing methods for automated phase identification from X-ray diffraction (XRD) patterns, we introduce a machine learning approach that uses a dual representation whereby XRD patterns are augmented with simulated pair distribution functions (PDFs). A convolutional neural network is trained directly on XRD patterns calculated using physics-informed data augmentation, which accounts for experimental artifacts such as lattice strain and crystallographic texture. A second network is trained on PDFs generated via Fourier transform of the augmented XRD patterns. At inference, these networks classify unknown samples by aggregating their predictions in a confidence-weighted sum. We show that such an integrated approach to phase identification provides enhanced accuracy by leveraging the benefits of each model’s input representation. Whereas networks trained on XRD patterns provide a reciprocal space representation and can effectively distinguish large diffraction peaks in multi-phase samples, networks trained on PDFs provide a real space representation and perform better when peaks with low intensity become important. These findings underscore the importance of using diverse input representations for machine learning models in materials science and point to new avenues for automating multi-modal characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nanostructure-specific X-ray tomography reveals myelin levels, integrity and axon orientations in mouse and human nervous tissue

Myelin insulates neuronal axons and enables fast signal transmission, constituting a key component of brain development, aging and disease. Yet, myelin-specific imaging of macroscopic samples remains a challenge. Here, we exploit myelin’s nanostructural periodicity, and use small-angle X-ray scattering tensor tomography (SAXS-TT) to simultaneously quantify myelin levels, nanostructural integrity and axon orientations in nervous tissue. Proof-of-principle is demonstrated in whole mouse brain, mouse spinal cord and human white and gray matter samples. Outcomes are validated by 2D/3D histology and compared to MRI measurements sensitive to myelin and axon orientations. Specificity to nanostructure is exemplified by concomitantly imaging different myelin types with distinct periodicities. Finally, we illustrate the method’s sensitivity towards myelin-related diseases by quantifying myelin alterations in dysmyelinated mouse brain. This non-destructive, stain-free molecular imaging approach enables quantitative studies of myelination within and across samples during development, aging, disease and treatment, and is applicable to other ordered biomolecules or nanostructures.

36 MATERIALS SCIENCE↗
NASA NTRS2007

Callable Virtual Observatory Functionality: Sample Use Cases

A virtual observatory with an Application Programming Interface (API) can become a powerful tool in analysis and modeling. In particular, an API that integrates time selection on such criteria as "most recent" and closest to a given absolute time simplifies the user-end programming considerably. We examine three types of use cases (nowcasting, data assimilation input, and user-defined sampling rates) for such functionality in the Virtual Solar Observatory (VSO).

Gurman, Joseph B.↗
NASA NTRS1993

Cat Mountain: A meteoritic sample of an impact-melted chondritic asteroid

Although impact cratering and collisional disruption are the dominant geologic processes affecting asteroids, samples of impact melt breccias comprise less than 1 percent of ordinary chondritic material and none exist among enstatite and carbonaceous chondrite groups. Because the average collisional velocity among asteroids is sufficiently large to produce impact melts, this paucity of impact-melted material is generally believed to be a sampling bias, making it difficult to determine the evolutionary history of chondritic bodies and how impact processes may have affected the physical properties of asteroids (e.g., their structural integrity and reflectance spectra). To help address these and related issues, the first petrographic description of a new chondritic impact melt breccia sample, tentatively named Cat Mountain, is presented.

Kring, David A.↗
DOE OSTI2021

Systematic characterization of human gut microbiome-secreted molecules by integrated multi-omics

The human gut microbiome produces a complex mixture of biomolecules that interact with human physiology and play essential roles in health and disease. Crosstalk between micro-organisms and host cells is enabled by different direct contacts, but also by the export of molecules through secretion systems and extracellular vesicles. The resulting molecular network, comprised of various biomolecular moieties, has so far eluded systematic study. Here we present a methodological framework, optimized for the extraction of the microbiome-derived, extracellular biomolecular complement, including nucleic acids, (poly)peptides, and metabolites, from flash-frozen stool samples of healthy human individuals. Our method allows simultaneous isolation of individual biomolecular fractions from the same original stool sample, followed by specialized omic analyses. The resulting multi-omics data enable coherent data integration for the systematic characterization of this molecular complex. Our results demonstrate the distinctiveness of the different extracellular biomolecular fractions, both in terms of their taxonomic and functional composition. This highlights the challenge of inferring the extracellular biomolecular complement of the gut microbiome based on single-omic data. The developed methodological framework provides the foundation for systematically investigating mechanistic links between microbiome-secreted molecules, including those that are typically vesicle-associated, and their impact on host physiology in health and disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

In situ Stripline Electrochemical NMR for Batteries

Here, there exist some long outstanding technical challenges that continue to be of hindrance to fully harnessing the unique investigative advantages of nuclear magnetic resonance (NMR) spectroscopy in the in situ investigation of rechargeable battery chemistry. For instance, the conducting materials and circuitry necessary for an operational battery always deteriorate the coil–based NMR sensitivity when placed inside the coil, and the shape mismatch between them leads to low sample filling factors and even higher detection limits. We report herein a novel and successful adaptation of stripline NMR detection that integrates seamlessly the NMR detection with construction of an electro–chemical device in general (or a battery in particular) which leads to a technique with much higher detection sensitivity, higher sample filling factors, and which is particularly suitable for mass–limited samples.

25 ENERGY STORAGE↗
DOE OSTI2025

Development and Demonstration of a Prototype Molten Salt Sampling System

Molten salt reactors (MSRs) offer potential operability and safety advantages when compared to commercial light water reactors (LWRs). However, operating experience with MSRs is sparse in comparison to what exists for LWRs. Further, the chemical and isotopic composition of the fuel and/or coolant salt is dynamic and difficult to characterize continuously, posing potential safety, operability, and safeguards unknowns that need to be addressed. A molten salt sampling system (MSSS) is regarded as a necessary subsystem within first generation MSRs used to obtain samples of salt for chemical and isotopic analysis in support of the need to monitor and control salt composition during operation. The MSSS is being developed using the Safety-in-Design (SiD) methodology, which incorporates incremental integration of safety analysis into the design process. The MSSS conceptual design emerging from the application of the early stages of the SiD methodology consists of a sample collection system and its housing, a freeze port, and inert gas control and delivery systems. This article describes the prototypes developed to test the functions of these MSSS subsystems, presents the results of testing in both dry and molten salt environments (including reliability data collection performed in accordance with the principles of SiD and the development of a semiquantitative fault tree model), and summarizes the opportunities for future design and testing enhancements based on the results of prototype testing.

molten salt reactor↗
NASA NTRS1980

Problems of sampling and radiation balances: Their problematics

Problems associated with the measurement of the Earth radiation balances are addressed. It is demonstrated that the knowledge of the different radiation budgets with their components is largely dependent on the space time sampling of the radiation field of the Earth atmosphere system. Whichever instrumental approach is adopted (wide angle view of high resolution) it affects the space time integration of the fluxes measured directly or calculated. In this case the necessary knowledge of the reflection pattern depends in addition on the angular sampling of the radiances. A series of questions is considered, the answers of which are a prerequisite to the the organization of a global observation system.

Crommelynck, D.↗
DOE OSTI2020

Allocation and Operation of A Hydropneumatic Energy Storage with Building Microgrid

Behind-meter application for a recently invented hydropneumatic Ground-Level Integrated Diverse Energy Storage (GLIDES) is focused in this research. Considering possible uncertainties from solar radiation and electricity load in a building microgrid, two-stage stochastic programming is adopted for 15-min operation and a mixed-integer nonlinear stochastic model is built with integrated energy systems of GLIDES, solar panel and power generating unit. In order to make the model computationally tractable, we use sample average approximate method to decrease associated complexity with sample size and improve solving efficiency. The experimental results in deterministic and stochastic operation indicate that best candidate solution from SAA are superior to the solution from expected value problem in terms of optimality gap and variance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2019

Correlation between SFR Surface Density and Thermal Pressure of Ionized Gas in Local Analogs of High-redshift Galaxies

We explore the relation between the star formation rate (SFR) surface density (integration of SFR) and the interstellar gas pressure for nearby compact starburst galaxies. The sample consists of 17 green peas and 19 Lyman break analogs (LBAs). Green peas are nearby analogs of Ly alpha emitters at high redshift and LBAs are nearby analogs of Lyman break galaxies at high redshift. We measure the sizes of green peas using Hubble Space Telescope Cosmic Origins Spectrograph near-UV images with a spatial resolution of approximately 0.05 arcsec. We estimate the gas thermal pressure in H II regions by P equals N (sub total)Tk (sub B) approximately or equal to 2n (sub e)Tk (sub B). The electron density is derived using the [S II] doublet at 6716,6731 Angstroms and the temperature is calculated from the [O III] lines. The correlation is characterized by the integration of SFR equals 2.40 times 10 (sup -3) times solar mass per year per square kiloparsec times ((P divided by k (sub B)) divided by (10 ( sup 4) per cubic centimeter times K)) times (sup 1.33). Green peas and LBAs have high integration of SFR up to 1.2 solar masses per year per square kiloparsec and high thermal pressure in the H II region up to P divided by k (sub B) approximating 10 (sup 7.2) K cubic centimeters. These values are at the highest end of the range seen in nearby starburst galaxies. The high gas pressure and the correlation are in agreement with those found instar-forming galaxies at redshift approximating 2.5. These extreme pressures are shown to be responsible for driving galactic winds in nearby starbursts. These outflows may be crucial in enabling Ly alpha and Lyman-continuum to escape.

Galaxies: Evolution↗
DOE OSTI2024

A Pseudoreversible Normalizing Flow for Stochastic Dynamical Systems with Various Initial Distributions

Here, we present a pseudoreversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with various initial distributions. The primary objective is to construct an accurate and efficient sampler that can be used as a surrogate model for computationally expensive numerical integration of SDEs, such as those employed in particle simulation. After training, the normalizing flow model can directly generate samples of the SDE’s final state without simulating trajectories. The existing normalizing flow model for SDEs depends on the initial distribution, meaning the model needs to be retrained when the initial distribution changes. The main novelty of our normalizing flow model is that it can learn the conditional distribution of the state, i.e., the distribution of the final state conditional on any initial state, such that the model only needs to be trained once and the trained model can be used to handle various initial distributions. This feature can provide a significant computational saving in studies of how the final state varies with the initial distribution. Additionally, we propose to use a pseudoreversible network architecture to define the normalizing flow model, which has sufficient expressive power and training efficiency for a variety of SDEs in science and engineering, e.g., in particle physics. We provide a rigorous convergence analysis of the pseudoreversible normalizing flow model to the target probability density function in the Kullback–Leibler divergence metric. Numerical experiments are provided to demonstrate the effectiveness of the proposed normalizing flow model.

97 MATHEMATICS AND COMPUTING↗