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All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Multiparameter fiber optic sensing system for monitoring enhanced geothermal systems

The goal of this project was to design, fabricate and test an optical fiber cable which supports multiple sensing modalities for measurements in the harsh environment of enhanced geothermal systems. To accomplish this task, optical fiber was tested at both high temperatures and strains for mechanical integrity, and in the presence of hydrogen for resistance to darkening. Both single mode (SM) and multimode (MM) commercially available optical fiber were identified and selected for the cable based on the results of these tests. The cable was designed and fabricated using a tube-within-tube construction containing two MM fibers and one SM fiber, and without supporting gel that is not suitable for high temperature environments. Commercial fiber optic sensing instruments using Raman DTS (distributed temperature sensing), Brillouin DTSS (distributed temperature and strain sensing), and Raleigh COTDR (coherent optical time domain reflectometry) were selected for field testing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Do You See What I See? Exploring the Consequences of Luminosity Limits in Black Hole–Galaxy Evolution Studies

In studies of the connection between active galactic nuclei (AGNs) and their host galaxies, there is widespread disagreement on some key aspects of the connection. These disagreements largely stem from a lack of understanding of the nature of the full underlying AGN population. Recent attempts to probe this connection utilize both observations and simulations to correct for a missed population, but presently are limited by intrinsic biases and complicated models. We take a simple simulation for galaxy evolution and add a new prescription for AGN activity to connect galaxy growth to dark matter halo properties and AGN activity to star formation. We explicitly model selection effects to produce an “observed” AGN population for comparison with observations and empirically motivated models of the local universe. This allows us to bypass the difficulties inherent in models that attempt to infer the AGN population by inverting selection effects. We investigate the impact of selecting AGNs based on thresholds in luminosity or Eddington ratio on the “observed” AGN population. By limiting our model AGN sample in luminosity, we are able to recreate the observed local AGN luminosity function and specific star formation-stellar mass distribution, and show that using an Eddington ratio threshold introduces less bias into the sample by selecting the full range of growing black holes, despite the challenge of selecting low-mass black holes. We find that selecting AGNs using these various thresholds yield samples with different AGN host galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

TU-D-209-06: Head and Neck Tissue Dose From X-Ray Scatter to Physicians Performing Cardiovascular Procedures

Purpose: The purpose of this work was to characterize the spatial distribution of scatter radiation to the head and neck of a physician performing an x-ray interventional procedure and assess brain, eye lens, and carotid artery dose. Methods: Radiographic x-ray beams were tuned to match the peak energy (56 to 106 keV) and HVL (3.5 to 6.5 mm Al) of x-ray scatter originating from a patient during a fluoroscopic procedure. The radiographic beam was directed upon a Rando phantom from an inferior-left location to mimic a typical patient-operator geometric relationship. A lead-equivalent protective garment was secured to the phantom. Direct exposure Gafchromic film (XRQA2) was placed between the transverse plane layers of the head and neck region of the phantom and exposed with 4 scatter-equivalent radiographic beams. A 3×3 cm{sup 2} film placed at the left collar of the phantom was used to monitor incident dose in the position of a radiation monitoring badge. The films were converted to 2D dose distribution maps using FilmQA Pro software and an Epson 11000-XL scanner. The 2D dose distributions maps were normalized by the left collar dose and the percent of left collar dose (%LCD) was calculated for select tissues. Results: The dose maps had high dynamic range (10{sub 4}) and spatial detail. Considering all transverse planes and 4 scatter beam qualities, the median %LCD values were: whole brain 8.5%, left brain 13%, right brain 5.4%, left eye lens 67%, right eye lens 25%, left carotid artery 72%, and right carotid artery 28%. Conclusion: Scatter radiation dose to an operator can be simulated using a tuned radiographic beam and used to expose a phantom and Gafchromic film, thereby creating detailed 2D dose distribution maps. This work facilitates individualized estimation of dose to select head and neck tissues based on an operator’s radiation monitoring badge value.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

The Galaxy–Halo Connection of DESI Luminous Red Galaxies with Subhalo Abundance Matching

Abstract We use subhalo abundance and age distribution matching to create magnitude-limited mock galaxy catalogs at z ∼ 0.43, 0.52, and 0.63 with z -band and 3.4 μ m W 1-band absolute magnitudes and r − z and r − W 1 colors. From these magnitude-limited mocks, we select mock luminous red galaxy (LRG) samples according to the ( r − z )-based (optical) and ( r − W 1)-based (infrared) selection criteria for the LRG sample of the Dark Energy Spectroscopic Instrument (DESI) survey. Our models reproduce the number densities, luminosity functions, color distributions, and projected clustering of the DESI Legacy Surveys that are the basis for DESI LRG target selection. We predict the halo occupation statistics of both optical and IR DESI LRGs at fixed cosmology and assess the differences between the two LRG samples. We find that IR-based SHAM modeling represents the differences between the optical and IR LRG populations better than using the z band and that age distribution matching overpredicts the clustering of LRGs, implying that galaxy color is uncorrelated with halo age in the LRG regime. Both the optical and IR DESI LRG target selections exclude some of the most luminous galaxies that would appear to be LRGs based on their position on the red sequence in optical color–magnitude space. Both selections also yield populations with a nontrivial LRG–halo connection that does not reach unity for the most massive halos. We find that the IR selection achieves greater completeness (≳90%) than the optical selection across all redshift bins studied.

Berti, Angela M. (ORCID:0000000335826649)↗
NASA NTRS1997

Rapid Temporal Changes of Midtropospheric Winds

The statistical distribution of the magnitude of the vector wind change over 0.25-, 1-, 2-. and 4-h periods based on data from October 1995 through March 1996 over central Florida is presented. The wind changes at altitudes from 6 to 17 km were measured using the Kennedy Space Center 50-MHz Doppler radar wind profiler. Quality controlled profiles were produced every 5 min for 112 gates, each representing 150 m in altitude. Gates 28 through 100 were selected for analysis because of their significance to ascending space launch vehicles. The distribution was found to be lognormal. The parameters of the lognormal distribution depend systematically on the time interval. This dependence is consistent with the behavior of structure functions in the f(exp 5/3) spectral regime. There is a small difference between the 1995 data and the 1996 data, which may represent a weak seasonal effect.

Merceret, Francis J.↗
DOE OSTI2025

Resilient Entanglement Distribution in a Multihop Quantum Network

The evolution of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions. We introduce multihop quantum networks to improve network reach and resilience by enabling quantum communications across intermediate nodes, thus broadening network connectivity and increasing scalability. We present multihop two-qubit polarization-entanglement distribution within a quantum network at the Oak Ridge National Laboratory campus. Our system uses wavelength-selective switches for adaptive bandwidth management on a software-defined quantum network that integrates a quantum data plane with classical data and control planes, creating a flexible, reconfigurable mesh. Our network distributes entanglement across six nodes within three subnetworks, each located in a separate building, optimizing quantum state fidelity and transmission rate through adaptive resource management. Additionally, we demonstrate the network's resilience by implementing a link recovery approach that monitors and reroutes quantum resources to maintain service continuity despite link failures—paving the way for scalable and reliable quantum networking infrastructures.

Alshowkan, Muneer [Oak Ridge National Laboratory (↗
DOE OSTI2021

Redshift evolution of the underlying type Ia supernova stretch distribution

The detailed nature of type Ia supernovae (SNe Ia) remains uncertain, and as survey statistics increase, the question of astrophysical systematic uncertainties arises, notably that of the evolution of SN Ia populations. We study the dependence on redshift of the SN Ia SALT2.4 light-curve stretch, which is a purely intrinsic SN property, to probe its potential redshift drift. The SN stretch has been shown to be strongly correlated with the SN environment, notably with stellar age tracers. We modeled the underlying stretch distribution as a function of redshift, using the evolution of the fraction of young and old SNe Ia as predicted using the SNfactory dataset, and assuming a constant underlying stretch distribution for each age population consisting of Gaussian mixtures. We tested our prediction against published samples that were cut to have marginal magnitude selection effects, so that any observed change is indeed astrophysical and not observational in origin. In this first study, there are indications that the underlying SN Ia stretch distribution evolves as a function of redshift, and that the age drifting model is a better description of the data than any time-constant model, including the sample-based asymmetric distributions that are often used to correct Malmquist bias at a significance higher than 5σ. The favored underlying stretch model is a bimodal one, composed of a high-stretch mode shared by both young and old environments, and a low-stretch mode that is exclusive to old environments. The precise effect of the redshift evolution of the intrinsic properties of a SN Ia population on cosmology remains to be studied. The astrophysical drift of the SN stretch distribution does affect current Malmquist bias corrections, however, and thereby the distances that are derived based on SN that are affected by observational selection effects. We highlight that this bias will increase with surveys covering increasingly larger redshift ranges, which is particularly important for the Large Synoptic Survey Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Ion Exchange Column Tests Supporting Technetium Removal Resin Maturation

The primary treatment of the tank waste at the DOE Hanford site will be done in the Waste Treatment and Immobilization Plant, currently under construction. The baseline plan for this facility is to treat the waste, splitting it into High Level Waste (HLW) and Low Activity Waste (LAW). Both waste streams are then separately vitrified as glass and sealed in canisters. The LAW glass will be disposed on site. There are currently no plans to treat the waste to remove technetium, so its disposition path is the LAW glass. Due to the soluble properties of pertechnetate and long half-life of 99 Tc, effective management of 99 Tc is important. Options are being explored to immobilize the supplemental LAW portion of the tank waste, as well as to examine the volatility of 99 Tc during the vitrification process. Removal of 99 Tc, followed by off-site disposal has potential to reduce treatment and disposal costs. A conceptual flow sheets for supplemental LAW treatment and disposal that could benefit from technetium removal will specifically examine removing 99 Tc from the LAW feed stream to supplemental immobilization. SuperLig® 639 is an elutable ion exchange resin. In the tank waste, 99 Tc is predominantly found in the tank supernate as pertechnetate (TcO 4 - ). Perrhenate (ReO 4 - ) has been shown to be a good non-radioactive surrogate for pertechnetate in laboratory testing for this ion exchange resin. This report contains results of experimental ion exchange distribution coefficient and column resin maturation kinetics testing using the resin SuperLig® 639a to selectively remove perrhenate from simulated LAW. This revision includes results from testing to determine effective resin operating temperature range. Loading tests were performed at 45°C, and the computer modeling was updated to include the temperature effects. Equilibrium contact testing indicated that this batch of SuperLig® 639 resin has good performance, with an average perrhenate distribution coefficient of 291 mL/g at a 100:1 phase ratio. This slightly exceeds the computer-modeled equilibrium distribution. The modeling agreed well with the experimental data for perrhenate removal with minor adjustments. Predicted breakthrough performance was on average within about 20% of measured values.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

What Are the Similarities and Differences in Marine Boundary Layer Cloud and Drizzle Microphysical Properties During the ACE–ENA and MARCUS Field Campaigns?

This study compares macrophysical and microphysical properties of single-layered, liquid-dominant MBL clouds from the Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) (above 60°S) and the ARM East North Atlantic (ENA) site during the Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) field campaign. A total of 1,136 (16.5% of clouds) and 6,034 5-min cloud samples are selected from MARCUS and ARM ENA in this study. MARCUS clouds have higher cloud-top heights, thicker cloud layers, larger liquid water path, and colder cloud temperatures than ENA. Thinner, warmer MBL clouds at ENA can contain higher layer-mean liquid water content due to higher cloud and ocean surface temperatures along with greater precipitable water vapor (PWV). MARCUS has a higher drizzle frequency rate (71.8%) than ENA (45.1%). Retrieved cloud and drizzle microphysical properties from each field campaign show key differences. MARCUS clouds feature smaller cloud droplets, whereas ENA clouds have larger cloud droplets, especially at the upper region of the cloud. From cloud top to cloud base, drizzle drop sizes increase while number concentrations decrease. Drizzle drop radius and number concentration decrease from cloud base to drizzle base due to net evaporation, and MARCUS' lower specific humidity leads to a higher drizzle base than ENA. In conclusion, the broader surface pressure and lower tropospheric stability (LTS) distributions during MARCUS have demonstrated that there are different synoptic patterns for selected cases during MARCUS with less PWV, while ENA is dominated by high pressure systems with nearly doubled PWV.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Recent Progress on the Stochastic Objective Decision Aide (SODA) Application

Idaho State University, in collaboration with Idaho National Laboratory, is engaged in development of a simple to use software application that utilizes stochastic techniques for the calculation of radiation doses associated with hypothetical radioactive material releases. This work is being performed through a grant from the U.S. Department of Energy (DOE) Nuclear Safety Research and Development (NSR and D) Program. Initial progress on the application was reported previously. Recent additions to the application are reported here. The Stochastic Objective Decision Aide (SODA) provides an easy to use software application to help decision makers support their judgment about the need or lack of need for safety structures, systems, and components. SODA is not intended to replace traditional design basis accident dose calculation methodology, nor is it intended to replace existing software used to perform formal dose consequence calculations. Rather, SODA is intended to supplement information obtained from existing codes to give a decision maker more information about an accident scenario. SODA also provides a simple method to perform parametric or sensitivity studies on individual input parameters. Non-reactor nuclear facilities operated under the approval authority of the US DOE use unmitigated hazard evaluations to determine if potential radiological doses associated with design basis events challenge dose evaluation guidelines. Unmitigated events that sufficiently challenge dose evaluation guidelines merit the selection of safety structures, systems, or components (SSCs) to prevent or mitigate the hazard. Dose consequence calculations traditionally involve use of the 'five-factor' formula: ST = MAR.DR.ARF.RF.LPF where ST is the source term (Bq), MAR is the total available material-at-risk (Bq), DR is the damage ratio (no units), ARF is the airborne release fraction (no units), RF is the respirable fraction (no units), and LPF is the leak path factor (no units). Potential radiation doses are then calculated using: CED = χ/Q.BR.ST.DCF (2) where CED is the committed effective dose (Sv), χ/Q is the plume dispersion (s/m{sup 3}), BR is the breathing rate (m{sup 3}/s), ST is the source term (Bq), and DCF is the dose conversion factor (Sv/Bq). Conservative single value input parameters are typically used to represent ARF, RF, LPF and BR. The traditional methodology, while conservative, can lead to skewed conclusions in the balance between cost and risk reduction resulting in over engineered systems with greater design, construction and operating costs. Rather than using a bounding single point value for each parameter in the dose consequence calculation, SODA uses distributions for some or all of the parameters. Each input parameter distribution is stochastically sampled and the resulting dose consequence calculation is repeated many times to develop a dose consequence distribution. The resulting distribution provides more information for the decision maker to rely upon when determining the need for safety SSCs. The SODA application was developed using MATLAB and it incorporates the use of Monte Carlo techniques as well as a graphical user interface (GUI). The application includes user selection of the governing distribution for parameters such as the MAR, DR, ARF, RF, LPF,χ/Q, BR, and DCF. While MATLAB was used for the development work, the application is distributed as a self-contained executable program. Features of the application include pull down menus with available distributions for the various parameters. The user has the option to plot the input parameter distribution that results from the random sampling process. The resulting dose consequence distribution is automatically analyzed to determine its similarity to well know distributions. This was done using the Bayesian Information Criterion method. If the resulting distribution is sufficiently similar to a well-known distribution, the application provides information about the distributions such as the mean value and other parameters. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Mobility Selective Ion Soft-Landing and Characterization Enabled Using Structures for Lossless Ion Manipulation

In this study, while conventional ion-soft landing uses the mass-to-charge (m/z) ratio to achieve molecular selection for deposition, here we demonstrate the use of Structures for Lossless Ion Manipulation (SLIM) for mobility-based ion selection and deposition. The dynamic rerouting capabilities of SLIM were leveraged to enable the rerouting of a selected range of mobilities to a different SLIM path (rather than MS) that terminated at a deposition surface. A selected mobility range from a phosphazene ion mixture was rerouted and deposited with a current pulse (~150 pA) resembling its mobility peak. In addition, from a mixture of tetra-alkyl ammonium (TAA) ions containing chain lengths of C5–C8, selected chains (C6, C7) were collected on a surface, reconstituted into solution-phase, and subsequently analyzed with a SLIM-qToF to obtain an IMS/MS spectrum, confirming the identity of the selected species. Further, this method was used to characterize triply charged tungsten-polyoxometalate anions, PW 12 O 40 3– (WPOM). The arrival time distribution of the IMS/MS showed multiple peaks associated with the triply charged anion (PW 12 O 40 3– ), of which a selected ATD was deposited and imaged using TEM. Additionally, the identity of the deposited WPOM was ascertained using energy-dispersive (EDS) spectroscopy. Further, we present theory and computations that reveal ion landing energies, the ability to modulate the energies, and deposition spot sizes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

DIMPLES: Distributed Influence Maximization for Pandemic pLanning on Exascale Systems

We study exascale parallel algorithms for the selection of intervention or monitoring strategies in massive realistic socio-technical networks through scalable Influence Maximization (InfMax) algorithms. We employ novel techniques to enable efficient scaling on up to 8k nodes of OLCF Frontier, with 65k AMD GPUs and 458k AMD CPU cores. Current state-of-the-art InfMax tools are limited to networks with only a few million actors (vertices) and a few hundred million interactions (edges). By overcoming these limitations, we show that our approach is capable of processing a realistic social contact network of the United States with 285 million nodes and about 8 billion edges. This two orders-of-magnitude improvement over the previous state-of-the-art is obtained by leveraging algorithmic advancements for the InfMax problem and designing several problem-specific approaches to overlap communication with computation, improve GPU efficiency, and lower the application’s memory requirements. We evaluate strong scaling for computing 10k most influential seeds using up to 8k nodes of an exascale system, and weak scaling from 128 to 8k system nodes for seed sets ranging from 625 to 40k seeds. We achieve the fastest-known runtime of 25 minutes while performing 48 million diffusion simulations totaling 2.31 petabytes to identify 40k influential seeds using 8k nodes, and take 5.75 minutes to identify 10k seeds while using 4k nodes.

Minutoli, Marco [Pacific Northwest National Labora↗
DOE OSTI2015

Gonadal transcriptomics elucidate patterns of adaptive evolution within marine rockfishes (Sebastes)

Background: The genetic mechanisms of speciation and adaptation in the marine environment are not well understood. The rockfish genus Sebastes provides a unique model system for studying adaptive evolution because of the extensive diversity found within this group, which includes morphology, ecology, and a broad range of life spans. Examples of adaptive radiations within marine ecosystems are considered an anomaly due to the absence of geographical barriers and the presence of gene flow. Using marine rockfishes, we identified signatures of natural selection from transcriptomes developed from gonadal tissue of two rockfish species (Sebastes goodei and S. saxicola). We predicted orthologous transcript pairs, and estimated their distributions of nonsynonymous (Ka) and synonymous (Ks) substitution rates. Results: We identified 144 genes out of 1079 orthologous pairs under positive selection, of which 11 are functionally annotated to reproduction based on gene ontologies (GOs). One orthologous pair of the zona pellucida gene family, which is known for its role in the selection of sperm by oocytes, out of ten was identified to be evolving under positive selection. In addition to our results in the protein coding-regions of transcripts, we found substitution rates in 3’ and 5’ UTRs to be significantly lower than Ks substitution rates implying negative selection in these regions. Conclusions: We were able to identify a series of candidate genes that are useful for the assessment of the critical genes that diverged and are responsible for the radiation within this genus. Genes associated with longevity hold potential for understanding the molecular mechanisms that have contributed to the radiation within this genus.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

Gravitational lensing frequencies - Galaxy cross-sections and selection effects

Four issues - (1) the best currently available data on the galaxy velocity-dispersion distribution, (2) the effects of finite core radii potential ellipticity on lensing cross sections, (3) the predicted distribution of lens image separations compared to observational angular resolutions, and (4) the preferential inclusion of lens systems in flux limited samples - are considered in order to facilitate more realistic predictions of multiple image galaxy-quasar lensing frequencies. It is found that (1) the SIS lensing parameter F equals 0.047 +/-0.019 with almost 90 percent contributed by E and S0 galaxies, (2) observed E and S0 core radii are remarkably small, yielding a factor of less than about 2 reduction in total lensing cross sections, (3) 50 percent of galaxy-quasar lenses have image separations greater than about 1.3 arcsec, and (4) amplification bias factors are large and must be carefully taken into account. It is concluded that flat universe models excessively dominated by the cosmological constant are not favored by the small observed galaxy-quasar lensing rate.

Fukugita, Masataka↗
DOE OSTI2017

Local Error Analysis and Comparison of the Swept- and Intersection-Based Remapping Methods

Abstract In this paper, the numerical error of two widely used methods for remapping of discrete quantities from one computational mesh to another is investigated. We compare the intuitive, but resource intensive method utilizing intersections of computational cells with the faster and simpler swept-region-based method. Both algorithms are formally second order accurate, however, they are known to produce slightly different quantity profiles in practical applications. The second-order estimate of the error formula is constructed algebraically for both algorithms so that their local accuracy can be evaluated. This general estimate is then used to assess the dependence of the performance of both methods on parameters such as the second derivatives of the remapped distribution, mesh geometry or mesh movement. Due to the complexity of such analysis, it is performed on a set of simplified elementary mesh patterns such as cell corner expansion, rotation or shear. On selected numerical tests it is demonstrated that the swept-based method can distort a symmetric quantity distribution more substantially than the intersection-based approach when the computational mesh moves in an unsuitable direction.

Klima, Matej↗
DOE OSTI2016

Installation of spectrally selective imaging system in RF negative ion source

A spectrally selective imaging system has been installed in the RF negative ion source in the International Thermonuclear Experimental Reactor-relevant negative ion beam test facility ELISE (Extraction from a Large Ion Source Experiment) to investigate distribution of hydrogen Balmer-α emission (H{sub α}) close to the production surface of hydrogen negative ion. We selected a GigE vision camera coupled with an optical band-path filter, which can be controlled remotely using high speed network connection. A distribution of H{sub α} emission near the bias plate has been clearly observed. The same time trend on H{sub α} intensities measured by the imaging diagnostic and the optical emission spectroscopy is confirmed.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Model selection and signal extraction using Gaussian Process regression

We present a novel computational approach for extracting localized signals from smooth background distributions. We focus on datasets that can be naturally presented as binned integer counts, demonstrating our procedure on the CERN open dataset with the Higgs boson signature, from the ATLAS collaboration at the Large Hadron Collider. Our approach is based on Gaussian Process (GP) regression — a powerful and flexible machine learning technique which has allowed us to model the background without specifying its functional form explicitly and separately measure the background and signal contributions in a robust and reproducible manner. Unlike functional fits, our GP-regression-based approach does not need to be constantly updated as more data becomes available. We discuss how to select the GP kernel type, considering trade-offs between kernel complexity and its ability to capture the features of the background distribution. We show that our GP framework can be used to detect the Higgs boson resonance in the data with more statistical significance than a polynomial fit specifically tailored to the dataset. Finally, we use Markov Chain Monte Carlo (MCMC) sampling to confirm the statistical significance of the extracted Higgs signature.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗