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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

NASA Space Radiation Program Integrative Risk Model Toolkit

NASA Space Radiation Program Element scientists have been actively involved in development of an integrative risk models toolkit that includes models for acute radiation risk and organ dose projection (ARRBOD), NASA space radiation cancer risk projection (NSCR), hemocyte dose estimation (HemoDose), GCR event-based risk model code (GERMcode), and relativistic ion tracks (RITRACKS), NASA radiation track image (NASARTI), and the On-Line Tool for the Assessment of Radiation in Space (OLTARIS). This session will introduce the components of the risk toolkit with opportunity for hands on demonstrations. The brief descriptions of each tools are: ARRBOD for Organ dose projection and acute radiation risk calculation from exposure to solar particle event; NSCR for Projection of cancer risk from exposure to space radiation; HemoDose for retrospective dose estimation by using multi-type blood cell counts; GERMcode for basic physical and biophysical properties for an ion beam, and biophysical and radiobiological properties for a beam transport to the target in the NASA Space Radiation Laboratory beam line; RITRACKS for simulation of heavy ion and delta-ray track structure, radiation chemistry, DNA structure and DNA damage at the molecular scale; NASARTI for modeling of the effects of space radiation on human cells and tissue by incorporating a physical model of tracks, cell nucleus, and DNA damage foci with image segmentation for the automated count; and OLTARIS, an integrated tool set utilizing HZETRN (High Charge and Energy Transport) intended to help scientists and engineers study the effects of space radiation on shielding materials, electronics, and biological systems.

Kim, Myung-Hee Y.↗
DOE OSTI2015

THE ANALYTICAL STRUCTURE OF THE PRIMARY INTERSTELLAR HELIUM DISTRIBUTION FUNCTION IN THE HELIOSPHERE

A new analytical model based on the previous work of Lee et al. is presented for the distribution of interstellar helium in the heliosphere. The model is tailored for comparison with the IBEX-Lo observations in order to determine the bulk velocity and temperature of helium in the local interstellar cloud. The model includes solar gravity, spherically symmetric stationary ionization rates, transformation to the Earth/IBEX frame of reference, the IBEX viewing geometry with small spin-axis tilt, and integration of the atom differential intensity over energy and the instrument collimator solid angle. The analysis employs an expansion of the count rate about the peak of the velocity distribution to second order in the magnitudes of several small quantities: the ratio of the helium thermal speed to its bulk speed, the angle between the bulk velocity and the ecliptic, the two angles describing the tilt of the IBEX spin-axis away from Sun-pointing, the collimator angular width, and the angular difference between the observing longitude and the longitude where the projection of the bulk velocity onto the ecliptic is tangential to Earth's orbit. The model reveals the evolving ellipsoidal shape of the helium distribution as it moves along its average hyperbolic orbit. For specified interstellar parameters, the model predicts the latitudinal and longitudinal structure of the helium distribution. The model is in reasonable agreement with IBEX observations and the predictions of the other available models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Vaccination compartmental epidemiological models for the delta and omicron SARS-CoV-2 variants

We explore the inclusion of vaccination in compartmental epidemiological models concerning the delta and omicron variants of the SARS-CoV-2 virus that caused the COVID-19 pandemic. We expand on our earlier compartmental-model work by incorporating vaccinated populations. We present two classes of models that differ depending on the immunological properties of the variant. The first one is for the delta variant, where we do not follow the dynamics of the vaccinated individuals since infections of vaccinated individuals were rare. The second one for the far more contagious omicron variant incorporates the evolution of the infections within the vaccinated cohort. We explore comparisons with available data involving two possible classes of counts, fatalities and hospitalizations. We present our results for two regions, Andalusia and Switzerland (including the Principality of Liechtenstein), where the necessary data are available. In the majority of the considered cases, the models are found to yield good agreement with the data and have a reasonable predictive capability beyond their training window, rendering them potentially useful tools for the interpretation of the COVID-19 and further pandemic waves, and for the design of intervention strategies during these waves.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Development of Automated Pipeline for Time-Resolved Link-Wise Vehicular Energy Consumption in the Chattanooga, TN Road Network

The Department of Energy (DOE) has shown strong interest in detecting energy inefficiencies in regional road networks, so as to derive energy consumed at a high spatial temporal resolution. We have developed a workflow to automate the estimation of time-resolved vehicular energy consumption over each link in a road network of interest. The road network used in the current work is centered around the city of Chattanooga, Tennessee and its bordering regions. Utilizing the most mature road network for the Chattanooga, TN region, vehicle speed & count data from TomTom in conjunction with machine learning methods, we have developed an automated pipeline to estimate energy consumption for every link in the network. The first step in the pipeline is ingesting vehicle probe counts and speed estimates from TomTom API. In the next step, the probe counts, speed profiles and other exogenous data (i.e. road types, weather data, ground-truth volume counts and more) were used as input to a supervised learning algorithm to estimate the number of vehicles throughout the entire region for each road segment. These volume estimates were then mapped to a unified road network that contained additional important information such as percentage change in gradient across a link, number of lanes and link lengths that are features in pre-trained single vehicle energy-consumption models available with the RouteE software developed at NREL. The per vehicle energy consumption on each road link predicted using appropriate RouteE vehicular models were multiplied by the volume estimate for the corresponding link over a given time period to predict energy consumed per link for the time interval of interest. Currently, work is underway to improve both the RouteE per vehicle energy estimate and the volume estimates derived from TomTom probe counts. We have also explored the correlation of the link-wise energy estimates with the features of the pre-trained RouteE machine learning model in order to gain insight into what factors contribute most to the link-wise energy consumption.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION,↗
DOE OSTI2015

CHARACTERIZING INTERMITTENCY OF 4-Hz QUASI-PERIODIC OSCILLATION IN XTE J1550–564 USING HILBERT–HUANG TRANSFORM

We present time-frequency analysis results based on the Hilbert–Huang transform (HHT) for the evolution of a 4-Hz low-frequency quasi-periodic oscillation (LFQPO) around the black hole X-ray binary XTE J1550–564. The origin of LFQPOs is still debated. To understand the cause of the peak broadening, we utilized a recently developed time-frequency analysis, HHT, for tracking the evolution of the 4-Hz LFQPO from XTE J1550–564. By adaptively decomposing the ∼4-Hz oscillatory component from the light curve and acquiring its instantaneous frequency, the Hilbert spectrum illustrates that the LFQPO is composed of a series of intermittent oscillations appearing occasionally between 3 and 5 Hz. We further characterized this intermittency by computing the confidence limits of the instantaneous amplitudes of the intermittent oscillations, and constructed both the distributions of the QPO’s high- and low-amplitude durations, which are the time intervals with and without significant ∼4-Hz oscillations, respectively. The mean high-amplitude duration is 1.45 s and 90% of the oscillation segments have lifetimes below 3.1 s. The mean low-amplitude duration is 0.42 s and 90% of these segments are shorter than 0.73 s. In addition, these intermittent oscillations exhibit a correlation between the oscillation’s rms amplitude and mean count rate. This correlation could be analogous to the linear rms-flux relation found in the 4-Hz LFQPO through Fourier analysis. We conclude that the LFQPO peak in the power spectrum is broadened owing to intermittent oscillations with varying frequencies, which could be explained by using the Lense–Thirring precession model.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2023

T-Cell Shenanigans: The Impact of MHC Pathway & Lipid Metabolism Genes on T-Cell Differentiation in the Thymus

Astronaut health and proper immune function are key to the success and sustainability of long term missions in space. While previous studies have observed adaptive immune dysfunction such as diminished WBC counts and cytokine production during spaceflight, the underlying mechanisms behind why immune function worsens are poorly understood. Using transcriptomic data analyzed from mouse thymus tissues available from the GLDS-421 experiment on the Rodent Research-9 mission, we used the GeneLab standardized RNA-Seq pipeline and identified four genes that were largely dysregulated (p<0.05): lipid metabolic genes Hpgd and Pgr and cell cycle regulator genes Cenpe and Kif11. We analyzed how these genes regulate the MHC-TCR interaction, and used this understanding to propose a novel mechanism for alterations to T-cell differentiation. In our experimental methodology, we propose to use 36 transgenic CD4-CD8 mice and 12 wild-type mice from the Jackson Lab to create a microgravity-simulating hindlimb unloading model and test our hypothesis. By silencing the aforementioned genes using custom siRNA based primers, we will use flow cytometry and RNA-Seq to quantify Treg counts in comparison to naive CD4+ cells, Alamar Blue assay for observing the metabolic activity in T-cells, and Enzyme-Linked Immunosorbent Assay (ELISA) to observe the general immune response in terms of T-cell differentiation. We hope this methodology will improve our knowledge of MHC-TCR interaction, contribute to a better understanding of the mechanisms of autoimmune diseases such as lupus, and improve the success rate of newer cancer treatments such as CAR-T cell therapy.

GL4HS↗
DOE OSTI2017

A fast integrated mobility spectrometer for rapid measurement of sub-micrometer aerosol size distribution, Part I: Design and model evaluation

This study discusses, a fast integrated mobility spectrometer (FIMS) was previously developed to characterize submicron aerosol size distributions at a frequency of 1 Hz and with high size resolution and counting statistics. However, the dynamic size range of the FIMS was limited to one decade in particle electrical mobility. It was proposed that the FIMS dynamic size range can be greatly increased by using a spatially varying electric field. This electric field creates regions with drastically different field strengths in the separator, such that particles of a wide diameter range can be simultaneously classified and subsequently measured. A FIMS incorporating this spatially varying electric field is developed. This paper describes the theoretical frame work and numerical simulations of the FIMS with extended dynamic size range, including the spatially varying electric field, particle trajectories, activation of separated particles in the condenser, and the transfer function, transmission efficiency, and mobility resolution. The influences of the particle Brownian motion on FIMS transfer function and mobility resolution are examined. The simulation results indicate that the FIMS incorporating the spatially varying electric field is capable of measuring aerosol size distribution from 8 to 600 nm with high time resolution. As a result, the experimental characterization of the FIMS is presented in an accompanying paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cosmological constraints from DES Y1 cluster abundances and SPT multiwavelength data

We perform a joint analysis of the counts of redMaPPer clusters selected from the Dark Energy Survey (DES) year 1 data and multiwavelength follow-up data collected within the 2500 deg2 South Pole Telescope (SPT) Sunyaev-Zel’dovich (SZ) survey. The SPT follow-up data, calibrating the richness-mass relation of the optically selected redMaPPer catalog, enable the cosmological exploitation of the DES cluster abundance data. To explore possible systematics related to the modeling of projection effects, we consider two calibrations of the observational scatter on richness estimates: a simple Gaussian model which account only for the background contamination (BKG), and a model which further includes contamination and incompleteness due to projection effects (PRJ). Assuming either a ΛCDM+∑mν or wCDM+∑mν cosmology, and for both scatter models, we derive cosmological constraints consistent with multiple cosmological probes of the low and high redshift Universe, and in particular with the SPT cluster abundance data. This result demonstrates that the DES Y1 and SPT cluster counts provide consistent cosmological constraints, if the same mass calibration data set is adopted. It thus supports the conclusion of the DES Y1 cluster cosmology analysis which interprets the tension observed with other cosmological probes in terms of systematics affecting the stacked weak lensing analysis of optically selected low–richness clusters. Finally, we analyze the first combined optically SZ selected cluster catalog obtained by including the SPT sample above the maximum redshift probed by the DES Y1 redMaPPer sample (z=0.65). Besides providing a mild improvement of the cosmological constraints, this data combination serves as a stricter test of our scatter models: the PRJ model, providing scaling relations consistent between the two abundance and multiwavelength follow-up data, is favored over the BKG model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

β -delayed neutron emission of Mn 64 , Cr 62 , and Fe 65

The β-decay properties of nuclei near the second nuclear “island of inversion” around neutron rich nuclei with neutron number 40 are important tests of nuclear structure models and interactions. In particular, the β-delayed neutron emission branch (Ρ n ), is useful for investigating β-strength and neutron-γ competition above the neutron separation energies of the daughter nuclei. We report new constraints for Ρ n values for three nuclei in the region: 62 Cr (Ρ n <1%), 64 Mn (Ρ n = 1.5⁢(6)%), and 65 Fe (Ρ n < 1%), measured with the Neutron Emission Ratio Observer (NERO) neutron long counter system and the Beta Counting Station (BCS) at the National Superconducting Cyclotron Laboratory (NSCL). Our results resolve the large discrepancy between previous direct and indirect measurements for 64 Mn and confirm the predictions of global theoretical models when a statistical treatment of the γ and neutron decays of the daughter states is included. Here we also obtain improved half-lives for 62 Cr [206(5) ms] and the short-lived isomer in the 62 Fe daughter [112(7) ms] from β-delayed γ emission data obtained in the same experiment with the Summing NaI (SuN) total absorption spectrometer. Finally, we use γ emission data to obtain a new upper limit for the 62 Cr β-decay population of the long-lived isomeric state in 62 Mn.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

DETERMINING NEUTRON STAR MASSES AND RADII USING ENERGY-RESOLVED WAVEFORMS OF X-RAY BURST OSCILLATIONS

Simultaneous, precise measurements of the mass M and radius R of neutron stars can yield uniquely valuable information about the still uncertain properties of cold matter at several times the density of nuclear matter. One method that could be used to measure M and R is to analyze the energy-dependent waveforms of the X-ray flux oscillations seen during some thermonuclear bursts from some neutron stars. These oscillations are thought to be produced by X-ray emission from hotter regions on the surface of the star that are rotating at or near the spin frequency of the star. Here we explore how well M and R could be determined by generating and analyzing, using Bayesian techniques, synthetic energy-resolved X-ray data that we produce assuming a future space mission having 2-30 keV energy coverage and an effective area of 10 m{sup 2}, such as the proposed Large Observatory for X-Ray Timing or Advanced X-Ray Timing Array missions. We find that waveforms from hot spots within 10° of the rotation equator usually constrain both M and R with an uncertainty of about 10%, if there are 10{sup 6} total counts from the spot, whereas waveforms from spots within 20° of the rotation pole provide no useful constraints. The constraints we report can usually be achieved even if the burst oscillations vary with time and data from multiple bursts must be used to obtain 10{sup 6} counts from the hot spot. This is therefore a promising method to constrain M and R tightly enough to discriminate strongly between competing models of cold, high-density matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Residual Optically Stimulated Luminescent (OSL) Signals for Al 2 O 3 :C and a Readout System with Reproducible Partial Signal Clearance

Optically stimulated luminescent dosimeters (OSLDs) are devices that, when stimulated with light, emit light in proportion to the integrated ionizing radiation dose. The stimulation of OSL material results in the loss of a small fraction of signal stored within the dosimetric traps. Previous studies have investigated the signal loss due to readout stimulation, and the optical annealing of OSLDs. This study builds on former research by examining the behavior of OSL signal after annealing, exploring the functionality of a previously developed signal loss model, and comparing uncertainties for dosimeters reused with or without annealing. For a completely annealed dosimeter, the minimum signal level was 56 ± 8 counts, and readings followed a Gaussian distribution. For dosimeters above this signal level, the fractional signal loss due to the reading process has a linear relationship with the calculated signal. At low signal levels (below 20,000 counts), in this OSLD system,calculated signal percent errors increase significantly but otherwise are on average 0.72 ± 0.27%, 0.40 ± 0.19%, 0.33±0.12%, and 0.24±0.07% for 30, 75, 150, and 300 readings. Theoretical calculations of uncertainties showed that annealing before reusing dosimeters allows for dose errors below 1% with as few as 30 readings. Reusing dosimeters multiple times increases the dose errors especially with low numbers of readouts, so theoretically around 300 readings would be necessary to achieve errors around 1% or below in most scenarios. Note that these dose errors do not include the error associated with the signal-to-dose conversion factor.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Accurate U 238 ( n , 2 n ) U 237 reaction cross-section measurements from 6.5 to 14.8 MeV

In this study, the cross section for the 238 U(n,2n) 237 U reaction has been measured in the incident neutron energy range from 6.5 to 14.8 MeV in small energy steps using an activation technique. Monoenergetic neutron beams were produced via the 2 H( d,n ) 3 He and 3 H ( d,n ) 4 He reactions. 238 U targets were activated along with Au and Al monitor foils to determine the incident neutron flux. The activity of the reaction products was measured in TUNL's low-background counting facility using high-resolution γ-ray spectroscopy. The results are compared with previous measurements and latest data evaluations. Statistical-model calculations, based on the Hauser-Feshbach formalism, have been carried out using the CoH 3 code and are compared with the experimental results. Finally, the present self-consistent and high-quality data are important for stockpile stewardship and nuclear forensic purposes as well as for the design and operation of fast reactors.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2017

Measurement of the directional sensitivity of Dark Matter Time Projection Chamber detectors

The dark matter time projection chamber (DMTPC) is a direction-sensitive detector designed to measure the direction of recoiling 19 F and 12 C nuclei in low-pressure CF 4 gas using optical and charge readout systems. In this paper, we employ measurements from two DMTPC detectors, with operating pressures of 30–60 torr, to develop and validate a model of the directional response and performance of such detectors as a function of recoil energy. Using our model as a benchmark, we formulate the necessary specifications for a scalable directional detector with sensitivity comparable to that of current-generation counting (nondirectional) experiments, which measure only recoil energy. Furthermore assuming the performance of existing DMTPC detectors, as well as current limits on the spin-dependent WIMP-nucleus cross section, we find that a 10–20 kg scale direction-sensitive detector is capable of correlating the measured direction of nuclear recoils with the predicted direction of incident dark matter particles and providing decisive (3σ) confirmation that a candidate signal from a nondirectional experiment was indeed induced by elastic scattering of dark matter particles off of target nuclei.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Extending the Frontier of Quantum Computers with Qutrits

Here, we advocate for a fundamentally different way to perform quantum computation by using three-level qutrits instead of qubits. In particular, we substantially reduce the resource requirements of quantum computations by exploiting a third state for temporary variables (ancilla) in quantum circuits. Past work with qutrits has demonstrated only constant factor improvements, owing to the log 2 (3) binary-to-ternary compression factor. We present a novel technique using qutrits to achieve a logarithmic runtime decomposition of the Generalized Toffoli gate using no ancilla - an exponential improvement over the best qubit-only equivalent. Our approach features a 70× improvement in total two-qudit gate count over the qubit-only decomposition. This results in improvements for important algorithms for arithmetic and QRAM. Simulation results under realistic noise models indicate over 90% mean reliability (fidelity) for our circuit, versus under 30% for the qubit-only baseline. These results suggest that qutrits offer a promising path toward extending the frontier of quantum computers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Cloud Condensation Nuclei Particle Counter (CCN) Instrument Handbook

The Cloud Condensation Nuclei Counter—CCN (Figure 1) is a U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility instrument for measuring the concentration of aerosol particles that can act as cloud condensation nuclei [1, 2]. The CCN draws the sample aerosol through a column with thermodynamically unstable supersaturated water vapor that can condense onto aerosol particles. Particles that are activated, i.e., grown larger in this process, are counted (and sized) by an Optical Particle Counter (OPC). Thus, activated ambient aerosol particle number concentration as a function of supersaturation is measured. Models CCN-100 and CCN-200 differ only in the number of humidifier columns and related subsystems: CCN-100 has one column and CCN-200 has two columns along with dual flow systems and electronics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

FY2018 Report on Fission Chamber Development at LANL

This report provides a description of a subset of FY18 activities conducted by Los Alamos National Laboratory (LANL) as part of the Nuclear Physics: Cumulative Fission Product Yields (Fission R-values) task of the NA-22 sponsored F2016 Venture Project. Specifically, this report describes the design, fabrication and testing of the Mark II fission chamber that was fielded as part of fission R-value measurements on the Flattop critical assembly located at the National Criticality Experiments Research Center (NCERC). Historically, fission product R-value measurements were performed by chemical separation and beta counting of samples from carefully controlled fission chamber experiments. These measurements form the basis for reporting data used in debris diagnostics and subsequent modeling. It was also the means to extract absolute cumulative fission product yields (yield per fission or $Y_i/f$ for the $i_{th}$ fission product) that are included in the international nuclear data libraries, and ultimately used in diagnostic evaluations and device modeling. The challenge for this effort was to design a functional fission chamber given the harsh neutron and gamma fields and severe space limitations of the Flattop critical assembly.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Cloud Condensation Nuclei Particle Counter Instrument Handbook - Airborne Version

The cloud condensation nuclei counter (CCN) is a U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility instrument for measuring the concentration of aerosol particles that can act as cloud condensation nuclei. Note: ARM deploys both ground and airborne versions of this instrument. This handbook covers only the airborne instrument; the ground version is covered by DOE/SC-ARM-TR-168. The main differences between the two are that the airborne CCN operates at fixed supersaturation and adapts thermal efficiency calculation in the data process. The CCN draws sample aerosol through a column with thermodynamically unstable supersaturated water vapor that can condense onto aerosol particles. Particles that are activated, i.e., grown larger in this process, are counted (and sized) by an optical particle counter (OPC). Thus, activated ambient aerosol particle number concentration as a function of supersaturation is measured. Models CCN-100 and CCN- 200 differ only in the number of humidifier columns and related subsystems: CCN-100 has one column and CCN-200 has two columns along with dual flow systems and electronics.

54 ENVIRONMENTAL SCIENCES↗