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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Integrating Public Health Surveillance and Environmental Data to Model Presence of Histoplasma in the United States

In the United States, the true geographic distribution of the environmental fungus Histoplasma capsulatum remains poorly understood but appears to have changed since it was first characterized. Histoplasmosis is caused by inhalation of the fungus and can range in severity from asymptomatic to life-threatening. Due to limited public health surveillance and under detection of infections, it is challenging to directly use reported case data to characterize spatial risk. Using monthly and yearly county-level public health surveillance data and various environmental and socioeconomic characteristics, we use a spatio-temporal occupancy model to estimate latent, or unobserved, presence of H. capsulatum , accounting for imperfect detection of histoplasmosis cases. We estimate areas with higher probabilities of the presence of H. capsulatum in the East North Central states around the Great Lakes, reflecting a shift of the endemic region to the north from previous estimates. The presence of H. capsulatum was strongly associated with higher soil nitrogen levels. In this investigation, we were able to mitigate challenges related to reporting and illustrate a shift in the endemic region from historical estimates. This work aims to help inform future surveillance needs, clinical awareness, and testing decisions for histoplasmosis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The MIGDAL experiment: Measuring a rare atomic process to aid the search for dark matter

We present the Migdal In Galactic Dark mAtter expLoration (MIGDAL) experiment aiming at the unambiguous observation and study of the so-called Migdal effect induced by fast-neutron scattering. It is hoped that this elusive atomic process can be exploited to enhance the reach of direct dark matter search experiments to lower masses, but it is still lacking experimental confirmation. Our goal is to detect the predicted atomic electron emission which is thought to accompany nuclear scattering with low, but calculable, probability, by deploying an Optical Time Projection Chamber filled with a low-pressure gas based on CF 4 . Initially, pure CF 4 will be used, and then in mixtures containing other elements employed by leading dark matter search technologies — including noble species, plus Si and Ge. High resolution track images generated by a Gas Electron Multiplier stack, together with timing information from scintillation and ionisation readout, will be used for 3D reconstruction of the characteristic event topology expected for this process — an arrangement of two tracks sharing a common vertex, with one belonging to a Migdal electron and the other to a nuclear recoil. Different energy-loss rate distributions along both tracks will be used as a powerful discrimination tool against background events. In this article we present the design of the experiment, informed by extensive particle and track simulations and detailed estimations of signal and background rates. In pure CF 4 we expect to observe 8.9 (29.3) Migdal events per calendar day of exposure to an intense D–D (D–T) neutron generator beam at the NILE facility located at the Rutherford Appleton Laboratory (UK). With our nominal assumptions, 5σ median discovery significance can be achieved in under one day with either generator.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Magic state distillation from entangled states

We report that magic can be distributed non-locally in many-body entangled states, such as the low energy states of condensed matter systems. Using the Bravyi-Kitaev magic state distillation protocol, we find that non-local magic is distillable and can improve the distillation outcome. We analyze a few explicit examples and show that spin squeezing can be used to convert non-distillable states into distillable ones. Our analysis also suggests that the conventional product input states assumed by magic distillation protocols are extremely atypical among general states with distillable magic. It further justifies the need for studying a diverse range of entangled inputs that yield magic states with high probability.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Initial development of a high temperature life prediction method directly accounting for variability in material properties

This report presents the initial development of a life prediction method that accounts for the variability of the material properties in Grade 91 steel. We account for material variability by both fitting a variable 3-parameter Weibull distribution to the rupture data of the material and by quantifying the effect that the creep deformation properties have on stresses via a Monte Carlo approach. To ensure a reasonable time frame when applying Monte Carlo to the creep stress, we propose a methodology that models the material as an extremely viscous Stokes flow with a non-Newtonian viscosity, therefore solving the problem in a single step. We use the final probabilistic model for structural failure developed in this document to evaluate a Flat Head Vessel designed with the Section III, Division 5 ASME Boiler Pressure and Vessel Code rules with a 100,000h design life and assess its probability of premature failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Predicting distribution of malaria vector larval habitats in Ethiopia by integrating distributed hydrologic modeling with remotely sensed data

Abstract Larval source management has gained renewed interest as a malaria control strategy in Africa but the widespread and transient nature of larval breeding sites poses a challenge to its implementation. To address this problem, we propose combining an integrated high resolution (50 m) distributed hydrological model and remotely sensed data to simulate potential malaria vector aquatic habitats. The novelty of our approach lies in its consideration of irrigation practices and its ability to resolve complex ponding processes that contribute to potential larval habitats. The simulation was performed for the year of 2018 using ParFlow-Common Land Model (CLM) in a sugarcane plantation in the Oromia region, Ethiopia to examine the effects of rainfall and irrigation. The model was calibrated using field observations of larval habitats to successfully predict ponding at all surveyed locations from the validation dataset. Results show that without irrigation, at least half of the area inside the farms had a 40% probability of potential larval habitat occurrence. With irrigation, the probability increased to 56%. Irrigation dampened the seasonality of the potential larval habitats such that the peak larval habitat occurrence window during the rainy season was extended into the dry season. Furthermore, the stability of the habitats was prolonged, with a significant shift from semi-permanent to permanent habitats. Our study provides a hydrological perspective on the impact of environmental modification on malaria vector ecology, which can potentially inform malaria control strategies through better water management.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Planets Across Space and Time (PAST). II. Catalog and Analyses of the LAMOST–Gaia–Kepler Stellar Kinematic Properties

The Kepler telescope has discovered over 4000 planets (candidates) by searching ~200,000 stars over a wide range of distance (order of kpc) in our Galaxy. Characterizing the kinematic properties (e.g., Galactic component membership and kinematic age) of these Kepler targets (including the planet candidate hosts) is the first step toward studying Kepler planets in the Galactic context, which will reveal fresh insights into planet formation and evolution. In this paper, the second part of the Planets Across the Space and Time (PAST) series, by combining the data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and Gaia and then applying the revised kinematic methods from PAST I, we present a catalog of kinematic properties (i.e., Galactic positions, velocities, and the relative membership probabilities among the thin disk, thick disk, Hercules stream, and the halo) as well as other basic stellar parameters for 35,835 Kepler stars. Further analyses of the LAMOST–Gaia–Kepler catalog demonstrate that our derived kinematic age reveals the expected stellar activity-age trend. Furthermore, we find that the fraction of thin (thick) disk stars increases (decreases) with the transiting planet multiplicity (N {sub p} = 0, 1, 2 and 3+) and the kinematic age decreases with N {sub p}, which could be a consequence of the dynamical evolution of planetary architecture with age. The LAMOST–Gaia–Kepler catalog will be useful for future studies on the correlations between the exoplanet distributions and the stellar Galactic environments as well as ages.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

The Extension of the Hauser-Feshbach Fission Fragment Decay Model to Multi-chance Fission and its Application to 239 Pu

The Hauser-Feshbach fission fragment decay model, HF3D, calculates the statistical decay of fission fragments through both prompt and delayed neutron and γ-ray emissions in a deterministic manner. While previously limited to the calculation of only first-chance fission, the model has recently been extended to include multi-chance fission, up to neutron incident energies of 20 MeV. The deterministic decay takes as input prescission quantities–fission probabilities, pre-fission neutron energies, and the average energy causing fission– and post-scission quantities–yields in mass, charge, total kinetic energy, spin, and parity. From those fission fragment initial conditions, the full decay is followed through both prompt and delayed particle emissions. The evaporation of the prompt neutrons and γ rays is calculated through the Hauser-Feshbach statistical theory, taking into account the competition between neutron and γ-ray emission, conserving energy, spin, and parity. The delayed emission is taken into account using time-independent calculation using decay data. This whole formulation allows for the calculation of prompt neutron and γ-ray properties, such as multiplicities and energy distributions, both independent and cumulative fission yields, and delayed neutron observables, in a consistent framework. Here, we describe the implementation of multi-chance fission into the HF 3 D model, and show an example of prompt and delayed quantities beyond first-chance fission, using the example of neutron-induced fission on 239 Pu. This expansion represents significant progress in consistently modeling the emission of prompt and delayed particles from fissile systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Scalable Risk Assessment of Rare Events in Power Systems With Uncertain Wind Generation and Loads

Risk assessment of rare events has become increasingly important in power system planning and operation with the increasing integration of renewable energy and the presence of system uncertainties. However, quantifying the risk posed by rare events via the traditional method, i.e., Monte Carlo sampling (MCS), incurs substantial computational expense stemming from the vast ensemble of power flow simulations. To accelerate the assessment, this paper proposes a Deep Neural Network (DNN)-kernelized vector-valued Gaussian Process (VVGP) approach with excellent computational efficiency while maintaining high accuracy. Consequently, serving as a surrogate model for the power flow solver, the DNN-kernelized VVGP enables significantly faster but accurate risk assessment compared to the power flow solver. The developed surrogate model evaluates low-order N - k events that contain more than 90% instances by adeptly capturing the topological features while the high-order N - k events are assessed via a power flow solver, thereby striking a balance between computational efficiency and uncertainty quantification accuracy. Moreover, the model incorporates a Support Vector Machine (SVM) classifier to resample concerning low-probability tail events to counteract the biases potentially introduced during the DNN-kernelized VVGP evaluations. Simulations conducted on the modified IEEE 24-bus, 118-bus, and European 1354-bus systems demonstrate that the proposed method maintains the accuracy benchmark set by MCS while significantly reducing computational demands in large-scale power systems as compared to other state-of-the-art methods.

17 WIND ENERGY↗
DOE OSTI2020

Connecting Risk and Resilience for a Power System Using the Portland Hills Fault Case Study

Active seismic faults in the Pacific Northwest area have encouraged electric utilities in the region to deeply contemplate and proactively intervene to support grid resilience. To further this effort this research introduces Monte Carlo (MC)-based power system modeling as a means to inform the Performance Based Earthquake Engineering method and simulates 100,000 sample earthquakes of a 6.8 magnitude (M6.8) Portland Hills Fault (PHF) scenario in the Portland General Electric (PGE) service territory as a proof of concept. This paper also proposes the resilience metric Seismic Load Recovery Factor (SLRF) to quantify the recovery of a downed power system and thus can be used to quantify earthquake economic risk. Using MC results, the SLRF was evaluated to be 19.7 h and the expected economic consequence cost of a M6.8 PHF event was found to be $\$180$ million with an annualized risk of $\$90,000$ given the event’s 1 in 2000 year probability of occurrence. The MC results also identified the eight most consequential substations in the PGE system—i.e., those that contributed to maximum load loss. This paper concludes that retrofitting these substations reduced the expected consequence cost of a M6.8 PHF event to $117 million.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Experimental study of vorticity-strain interactions in turbulent premixed counterflow flames

Here, the effects of heat release on interactions between vorticity (ω) and strain rate (s) in turbulent premixed CH 4 /O 2 /N 2 counterflow flames are investigated using simultaneous OH laser-induced fluorescence (LIF) and tomographic particle image velocimetry (TPIV) measurements. A comparison between the flames and a corresponding turbulent non-reacting variable density N 2 -vs-products counterflow reveals the impact of heat release on vorticity-strain rate alignment statistics. Vorticity and strain rate statistics in the flames and non-reacting flow are conditioned on distance from the local flame front and gas mixing layer interface (GMLI) contours, respectively. The magnitude, alignment, and spatial distribution of the vorticity and principal strain rates (s 1 , s 2 , s 3 ) are rather different when heat release is present. Density variations without heat release enhance the ω-s 2 alignment while significantly reducing the ω-s 3 alignment and modestly reducing the ω-s 1 alignment. In contrast, heat release at the flame front further reduces the ω-s 1 alignment but increases the ω-s 3 alignment and suppresses the preferential ω-s 2 alignment. Furthermore, increasing turbulence diminishes the effect of heat release on this preferential alignment. In regions with the largest vorticities, both the reacting and non-reacting counterflows show an increase in the probability of ω-s 2 alignment. All counterflow cases have a net positive vortex-stretching contribution to the enstrophy production with a peak production rate at the flame front or GMLI, but the peak values depend on the density variation, heat release, and turbulence level. Elucidation of the complex interplay between these factors contributes to the understanding of the dynamics of turbulence-flame interactions.

42 ENGINEERING↗
DOE OSTI2020

Angular distribution of neutron production by proton and carbon-ion therapeutic beams

Carbon-ion beams are increasingly used in the clinical practice for external radiotherapy treatments of deep-seated tumors. At therapeutic energies, carbon ions yield significant secondary products, including neutrons, which may be of concern for the radiation protection of the patient and personnel. We simulated the neutron yield produced by proton and carbon-ion pencil beams impinging on a clinical phantom at three different angles: 15°, 45° and 90°, with respect to the beam axis. We validated the simulated results using the measured response of organic scintillation detectors. We compared the results obtained with FLUKA 2011.2 and MCNPX 2.7.0 based on three different physics models: Bertini, Isabel, and CEM. Over the different ions, energies, and angles, the FLUKA simulation results agree better with the measured data, compared to the MCNPX results. Simulations of carbon ions at low angles exhibit both the highest deviation from measured data and inter-model discrepancy, which is probably due to the different treatment of the pre-equilibrium stage. The reported neutron yield results could help in the comparison of carbon-ion and proton treatments in terms of secondary neutron production for radiation protection applications.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

The Aemulus Project. VI. Emulation of Beyond-standard Galaxy Clustering Statistics to Improve Cosmological Constraints

Abstract There is untapped cosmological information in galaxy redshift surveys in the nonlinear regime. In this work, we use the Aemulus suite of cosmological N -body simulations to construct Gaussian process emulators of galaxy clustering statistics at small scales (0.1–50 h −1 Mpc) in order to constrain cosmological and galaxy bias parameters. In addition to standard statistics—the projected correlation function w p ( r p ), the redshift-space monopole of the correlation function ξ 0 ( s ), and the quadrupole ξ 2 ( s )—we emulate statistics that include information about the local environment, namely the underdensity probability function P U ( s ) and the density-marked correlation function M ( s ). This extends the model of Aemulus III for redshift-space distortions by including new statistics sensitive to galaxy assembly bias. In recovery tests, we find that the beyond-standard statistics significantly increase the constraining power on cosmological parameters of interest: including P U ( s ) and M ( s ) improves the precision of our constraints on Ω m by 27%, σ 8 by 19%, and the growth of structure parameter, f σ 8 , by 12% compared to standard statistics. We additionally find that scales below ∼6 h −1 Mpc contain as much information as larger scales. The density-sensitive statistics also contribute to constraining halo occupation distribution parameters and a flexible environment-dependent assembly bias model, which is important for extracting the small-scale cosmological information as well as understanding the galaxy–halo connection. This analysis demonstrates the potential of emulating beyond-standard clustering statistics at small scales to constrain the growth of structure as a test of cosmic acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Quantifying the Solar Energy Resource for Puerto Rico

After Hurricane Maria, multiple U.S. Department of Energy laboratories studied the state of the electric grid in Puerto Rico and analyzed grid resilience and grid integration of renewable energy. As part of the work done at the National Renewable Energy Laboratory, researchers created new solar resource data, conducted a technical potential and supply curve analysis, and studied the interannual variability of the solar resource. A new methodology was developed to downscale solar resource data from the National Solar Radiation Data Base (NSRDB) from a 4-km x 4-km spatial and 30-minute temporal resolution to a 2 km x 2 km and 5-minute resolution. This methodology primarily used simple physical principles to develop high-resolution cloud properties which were then used to compute solar radiation. The high-resolution datasets were validated against ground measurements and the error metrics were found to be similar to the original lower resolution dataset. Using 20 years of downscaled data from the NSRDB multi-year capacity factors for photovoltaics (PV) were developed for both single-axis tracking and fixed latitude-tilt configurations. Use of the multi-year data provides the ability to understand variability in capacity factors due to variability in weather over a long period of time. For Puerto Rico the coastal regions were found to have significant higher capacity factors than inland. Using land-use and terrain information a technical potential analysis was conducted for Puerto Rico. This analysis restricted single PV plant development to a maximum of 100 MW nameplate capacity. The nameplate capacity for each municipality were then determined. Based on our assumptions, 56 of the 78 total municipalities of Puerto Rico contain some level of solar capacity. Most of the interior municipalities did not have any capacity because of the geographic exclusions used in this study. The lowest capacity for a PV plant observed in a municipality was 10 MW. The maximum capacity within a county was 2,000 MW. Further a supply curve analysis was conducted by taking the results of the technical potential and quantifying system and transmission costs. The levelized cost of energy (LCOE) was calculated for each theoretical PV plant site, and the levelized cost of transmission was added to the LCOE to produce a total cost estimate for each site. The results of the supply curve analysis allow for a relative comparison of the cost for integrating new PV capacity into the grid. This analysis indicates that cheaper total LCOE sites tend to be larger in capacity. The total capacity in this study was found to be far beyond the maximum peak load for the island. However, this study does not consider the economic and market potential for development. The cumulative capacity presented in this study assumes that the best locations are developed first and ignores the complex decision paths for new power plant development. Therefore, this analysis can only be treated as illustrative. Finally this study investigates the impact of inter-annual variability of resource using a variety of metrices including probability of exceedance and variation in capacity factor and LCOE. This study demonstrates that the capacity factor or LCOE could vary by over 10% year to year. This clearly indicates the risks involved in using any particular year of data and clearly points to the use of multi-year data to reduce some of the risks related to variability in weather.

14 SOLAR ENERGY↗
DOE OSTI2025

Correlation Between Weather Alerts and Grid Component Failures for Grid Alert

Weather events cause most grid failures. Often, we even get notifications on our phones to take cover or be prepared for an imminent event. If electric grid utilities had a similar warning that also included probable scenarios and the equipment involved, they could prepare and minimize the effects. Recent research at Idaho National Laboratory into electric grid risk analysis methods resulted in a tool that allows for the development of the most likely scenarios given failure probabilities of grid components. INL has a project with the U.S. Department of Energy’s Cybersecurity, Energy Security, and Emergency Response (CESER) program to develop a Grid Alert application that receives messages from the existing emergency alert system, filters and determines components possibly affected by the emergency event, calculates probable scenarios uses MASTERRI and then notifies the utility if there is significant risk. Historical failure data of elements that comprise the U.S. electric grid have been compiled by utilities and organizations such as the international regulatory body North American Electric Reliability Corporation (NERC). Nominal failure rates are obtained from this data. To make this tool possible, estimated failure rates are needed for different component types given the alert type, severity, and location. Historic weather-related grid element failures are correlated with historic weather events from Integrated Public Alert & Warning System (IPAWS). These correlated events and failures are used along with Bayesian updates from the historical norms to provide a modified failure rate for grid elements in the alert areas and calculate probable scenarios. This discusses the Grid Alert project plan but focuses on the data gathered and process used in determining failure rates for possible grid failure scenarios.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Synchrotron x-ray fluorescence analysis reveals diagenetic alteration of fossil melanosome trace metal chemistry

A key feature of the pigment melanin is its high binding affinity for trace metal ions. In modern vertebrates trace metals associated with melanosomes, melanin-rich organelles, can show tissue-specific and taxon-specific distribution patterns. Such signals preserve in fossil melanosomes, informing on the anatomy and phylogenetic affinities of fossil vertebrates. Fossil and modern melanosomes, however, often differ in trace metal chemistry; in particular, melanosomes from fossil vertebrate eyes are depleted in Zn and enriched in Cu relative to their extant counterparts. Whether these chemical differences are biological or taphonomic in origin is unknown, limiting our ability to use melanosome trace metal chemistry to test palaeobiological hypotheses. Here, we use maturation experiments on eye melanosomes from extant vertebrates and synchrotron rapid scan-x-ray fluorescence analysis to show that thermal maturation can dramatically alter melanosome trace element chemistry. In particular, maturation of melanosomes in Cu-rich solutions results in significant depletion of Zn, probably due to low pH and competition effects with Cu. These results confirm fossil melanosome chemistry is susceptible to alteration due to variations in local chemical conditions during diagenesis. Maturation experiments can provide essential data on melanosome chemical taphonomy required for accurate interpretations of preserved chemical signatures in fossils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Globular Cluster Candidates in the Sagittarius Dwarf Galaxy

Recently, new Sagittarius (Sgr) dwarf-galaxy globular clusters were discovered, which opens the question of the actual size of the Sgr globular cluster population, and therefore on our understanding of the Sgr galaxy formation and accretion history of the Milky Way. Based on Gaia EDR3 and SDSS IV DR16 (APOGEE-2) data sets, we performed an analysis of the color–magnitude diagrams (CMDs) of the eight new Sgr globular clusters found by Minniti et al. from a sound cleaning of the contamination of Milky Way and Sgr field stars, complemented by available kinematic and metal abundance information. The cleaned CMDs and spatial stellar distibutions reveal the presence of stars with a wide range of cluster membership probabilities. Minni 332 turned out to be a younger (<9 Gyr) and more metal-rich ([M/H] ≳ -1.0 dex) globular cluster than M54, the nuclear Sgr globular cluster; as could also be the case of Minni 342, 348, and 349, although their results are less convincing. Minni 341 could be an open cluster candidate (age < 1 Gyr, [M/H] ~ -0.3 dex), while the analyses of Minni 335, 343, and 344 did not allow us to confirm their physical reality. We also built the Sgr cluster frequency (CF) using available ages of the Sgr globular clusters and compared it with that obtained from the Sgr star formation history. Both CFs are in excellent agreement. However, the addition of eight new globular clusters with ages and metallicities distributed according to the Sgr age–metallicity relationship turns out in a remarkably different CF.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Convergence acceleration of Monte Carlo many-body perturbation methods by direct sampling

In the Monte Carlo many-body perturbation (MC-MP) method, the conventional correlation-correction formula, which is a long sum of products of low-dimensional integrals, is first recast into a short sum of high-dimensional integrals over electron-pair and imaginary-time coordinates. These high-dimensional integrals are then evaluated by the Monte Carlo method with random coordinates generated by the Metropolis–Hasting algorithm according to a suitable distribution. The latter algorithm, while advantageous in its ability to sample nearly any distribution, introduces autocorrelation in sampled coordinates, which in turn increases the statistical uncertainty of the integrals and thus the computational cost. It also involves wasteful rejected moves and an initial “burn-in” step as well as displays hysteresis. Here, an algorithm is proposed that directly produces a random sequence of electron-pair coordinates for the same distribution used in the MC-MP method, which is free from autocorrelation, rejected moves, a burn-in step, or hysteresis. Furthermore, this direct-sampling algorithm is shown to accelerate second- (MC-MP2) and third-order Monte Carlo many-body perturbation (MC-MP3) calculations by up to 222% and 38%, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗