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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 OSTI2017

Multilevel Sequential Monte Carlo Samplers for Normalizing Constants

This article considers the sequential Monte Carlo (SMC) approximation of ratios of normalizing constants associated to posterior distributions which in principle rely on continuum models. Therefore, the Monte Carlo estimation error and the discrete approximation error must be balanced. A multilevel strategy is utilized to substantially reduce the cost to obtain a given error level in the approximation as compared to standard estimators. Two estimators are considered and relative variance bounds are given. The theoretical results are numerically illustrated for two Bayesian inverse problems arising from elliptic partial differential equations (PDEs). The examples involve the inversion of observations of the solution of (i) a 1-dimensional Poisson equation to infer the diffusion coefficient, and (ii) a 2-dimensional Poisson equation to infer the external forcing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Quantum Stochastic Programming [SWR-26-040]

The Quantum Stochastic Programming tool contains quantum computing algorithms for two-stage stochastic optimization, with a focus on the Unit Commitment (UC) problem in power systems. The algorithms combine Discrete Quantum Annealing (DQA) with Quantum Amplitude Estimation (QAE) to compute expected-value objective functions over a probability distribution of wind-power scenarios. Based on: arXiv 2402.15029 - "Quantum algorithms for the two-stage stochastic unit commitment problem"

Maack, Jonathan [National Laboratory of the Rockie↗
DOE OSTI2024

Environmental associations of Ophidiomyces ophidiicola , the causative agent of ophidiomycosis in snakes

Emerging pathogenic fungi have become a topic of conservation concern due to declines observed in several host taxa. One emerging fungal pathogen, Ophidiomyces ophidiicola, is well documented as the causative agent of ophidiomycosis, otherwise known as snake fungal disease (SFD). O. ophidiicola has been found to cause disease in a variety of snake species across the United States, including the eastern massasauga (Sistrurus catenatus), a federally threatened rattlesnake species. Most work to date has involved detecting O. ophidiicola for diagnosis of infection through direct sampling of snakes, and attempts to detect O. ophidiicola in the abiotic environment to better understand its distribution, seasonality, and habitat associations are lacking. We collected topsoil and groundwater samples from four macrohabitat types across multiple seasons in northern Michigan at a site where Ophidiomyces infection has been confirmed in eastern massasauga. Using a quantitative PCR (qPCR) assay developed for O. ophidiicola, we detected Ophidiomyces DNA in topsoil but observed minimal to no detection in groundwater samples. Detection frequency did not differ between habitats, but samples grouped seasonally showed higher detection during mid-summer. We found no relationships of detection with hypothesized environmental correlates such as soil pH, temperature, or moisture content. Furthermore, the distribution of Ophidiomyces positive samples across the site was not linked to estimated space use of massasaugas. Our data suggests that season has some effect on the presence of Ophidiomyces. Differences in presence between habitats may exist but are likely more dependent on the time of sampling and currently uninvestigated soil or biotic parameters. These findings build on our understanding of Ophidiomyces ecology and epidemiology to help inform where and when snakes may be exposed to the fungus in the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Drinking Water Consequences Tools. A Literature Review

In support of the goals of Department of Homeland Security’s (DHS) National Protection and Programs Directorate and the Federal Emergency Management Agency, the DHS Office of Science and Technology is seeking to develop and/or modify consequence assessment tools to enable drinking water systems owner/operators to estimate the societal and economic consequences of drinking water disruption due to the threats and hazards. This work will expand the breadth of consequence estimation methods and tools using the best-available data describing water distribution infrastructure, owner/assetlevel economic losses, regional-scale economic activity, and health. In addition, this project will deploy the consequence methodology and capability within a Web-based platform. This report is intended to support DHS effort providing a review literature review of existing assessment tools of water and wastewater systems consequences to disruptions. The review includes tools that assess water systems resilience, vulnerability, and risk. This will help to understand gaps and limitations of these tools in order to plan for the development of the next-generation consequences tool for water and waste water systems disruption.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration (Final Report)

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗
DOE OSTI2022

IMoFi (Intelligent Model Fidelity): Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration Updated Accomplishments

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO), including some updates from the previous report SAND2022-0215, to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗
DOE OSTI2024

Design Methods, Tools, and Data for Ceramic Solar Receivers

This report presents the development of tools and methods for evaluating the reliability and performance of ceramic materials in high temperature solar receivers. As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat requirements, current high temperature metallic materials face challenges in maintaining structural integrity. This report explores advanced ceramics as a promising alternative, given their superior high temperature strength and lower thermal expansion, compared to metals. To address the need for effective ceramic receiver design tools, this report integrates statistical failure models of ceramics into the existing srlife tool: an open-source software package designed to estimate the life of high temperature CSP components. These failure models account for the inherent variability and flaw distribution in ceramics, as well as the impact of subcritical crack growth under high temperature cyclic loads. The report also presents experimental data collected for a commercially available ceramic material, SiC, and details the process of estimating reliability model parameters from these data. A comparative design analysis is then performed between ceramic (SiC) and metallic (current nickel-based superalloys A740H and A282) receiver. This comparison demonstrates that SiC receivers can achieve service life exceeding 30 years under high incident heat flux conditions, compared to just a few years for metallic receivers.

14 SOLAR ENERGY↗
DOE OSTI2026

Spatially Resolved Domicile Charging Demands for Light-, Medium-, and Heavy-Duty Electric Vehicles in Virginia

The use of plug-in electric vehicles (PEVs) and resulting grid impacts are likely to grow rapidly, and evaluation of optimal smart charge management and grid integration strategies is warranted now. Evaluating distribution grid impacts requires fine-grained models of PEV operations to estimate charging loads across diverse vehicles at high spatial resolution. We propose such a model and consider a high-electrification scenario in Richmond and Newport News, Virginia. Our framework considers four categories of vehicle that are amenable to early aggressive electrification: light-duty passenger vehicles (LDV), trucks and vans with a focus on delivery or other local operations, school buses, and transit buses. These vehicles have a relatively consistent domicile, reducing the need for public charging infrastructure rollout to electrify. We apply a recent LDV model and propose new models for each vocation of medium- and heavy-duty vehicle, leveraging telematics data. We demonstrate our framework in Virginia and find energy demands in the region may total 15 GWh day, with most consumed by LDV. However, considering power demand at high spatial resolution reveals a different trend: LDVs have relatively small peak loads at specific sites (peak site demand around 800 kW) compared to average and high demand medium- and heavy-duty vehicle charging sites (peak site demand around 6,000 kW at a transit bus depot, 1,500 kW at a local freight hub, and 1,000 kW at a school). Our framework yields insights on the relative impacts of each vocation and enables future work to tailor grid integration strategies to each vehicle category.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Point Cloud Based Approach to Stem Width Extraction of Sorghum

A revolution in the field of genomics has produced vast amounts of data and furthered our understanding of the genotypephenotype map, but is currently constrained by manually intensive or limited phenotype data collection. We propose an algorithm to estimate stem width, a key characteristic used for biomass potential evaluation, from 3D point cloud data collected by a robot equipped with a depth sensor in a single pass in a standard field. The algorithm applies a two step alignment to register point clouds in different frames, a Frangi filter to identify stemlike objects in the point cloud and an orientation based filter to segment out and refine individual stems for width estimation. Individually, detected stems which are split due to occlusions are merged and then registered with previously found stems in previous camera frames in order to track temporally. We then refine the estimates to produce an accurate histogram of width estimates per plot. Since the plants in each plot are genetically identical, distributions of the stem width per plot can be useful in identifying genetically superior sorghum for biofuels.

09 BIOMASS FUELS↗
DOE OSTI2024

Epidemiological investigation of coccidiosis and associated risk factors in broiler chickens immunized with live anticoccidial vaccines in China

Coccidiosis is a costly intestinal disease of chickens caused by Eimeria species. This infection is associated with high mortality, reduced feed efficiency, and slowed body weight gain. The diagnosis and control of coccidiosis becomes challenging due to the fact that chickens can be infected by seven different Eimeria species and often occur mixed-species co-infections. Grasping the epidemiology of Eimeria species is crucial to estimate the efficiency of poultry management. This study aimed to explore the distribution of Eimeria species in broiler chickens in China after administering live anticoccidial vaccines. A total of 634 samples were obtained, and the survey results showed that the prevalence of Eimeria was 86.12% (546/634), and the most common species were E. acervulina (65.62%), E. necatrix (50.95%), E. mitis (50.79%), E. tenella (48.42%), and E. praecox (41.80%). Most samples indicated mixed-species infections (an average of 3.29 species per positive sample). Notably, 63.98% of samples contain 3 to 5 Eimeria species within a single fecal sample. The most prevalent combinations were E. acervulina – E. tenella (38.96%) and E. acervulina – E. necatrix (37.22%). Statistical analysis showed that flocks vaccinated with trivalent vaccines were significantly positive for E. necatrix in grower chickens (OR = 3.30, p < 0.05) compared with starter chickens, and tetravalent vaccinated flocks showed that starter chickens demonstrated a higher susceptibility to E. tenella – E. brunetti (OR = 2.03, p < 0.05) and E. acervulina – E. maxima (OR = 2.05, p < 0.05) compared with adult chickens. Geographically, in the case of tetravalent vaccine-immunized flocks, a substantial positive association was observed between E. necatrix infection rates and flocks from eastern (OR = 3.88, p < 0.001), central (OR = 2.65, p = 0.001), and southern China (OR = 3.17, p < 0.001) compared with southwestern China. This study also found a positive association between E. necatrix (OR = 1.64, p < 0.05), E. acervulina (OR = 1.59, p < 0.05), and E. praecox (OR = 1.81, p < 0.05) infection and coccidiosis occurrence compared with non-infected flocks in tetravalent vaccinated flocks. This molecular epidemiological investigation showed a high prevalence of Eimeria species in the field. The emergent species, E. brunetti and E. praecox , might be incorporated into the widely-used live vaccines in the future. These insights could be useful in refining coccidiosis control strategies in the poultry industry.

Liao, Shenquan↗
DOE OSTI2016

STATISTICALLY DETERMINED DISPERSION RELATIONS OF MAGNETIC FIELD FLUCTUATIONS IN THE TERRESTRIAL FORESHOCK

We obtain dispersion relations of magnetic field fluctuations for two crossings of the terrestrial foreshock by Cluster spacecraft. These crossings cover plasma conditions that differ significantly in their plasma β and in the density of the reflected ion beam, but not in the properties of the encountered ion population, both showing shell-like distribution function. Dispersion relations are reconstructed using two-point instantaneous wave number estimations from pairs of Cluster spacecraft. The accessible range of wave vectors, limited by the available spacecraft separations, extends to ≈2 × 10{sup 4} km. Results show multiple branches of dispersion relations, associated with different powers of magnetic field fluctuations. We find that sunward propagating fast magnetosonic waves and beam resonant modes are dominant for the high plasma β interval with a dense beam, while the dispersions of the interval with low beam density include Alfvén and fast magnetosonic modes propagating sunward and anti-sunward.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

SICK: THE SPECTROSCOPIC INFERENCE CRANK

There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal-to-noise ratio spectra of M67 stars reveals atomic diffusion processes on the order of 0.05 dex, previously only measurable with differential analysis techniques in high-resolution spectra. sick is easy to use, well-tested, and freely available online through GitHub under the MIT license.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Spectroscopic and Photometric Monitoring of a Poorly Known Highly Luminous OH/IR Star: IRAS 18278+0931

We present the time-dependent properties of a poorly known OH/IR star, IRAS 18278+0931 (hereafter IRAS 18+09), toward the Ophiuchus constellation. We have carried out long-term optical/near-infrared photometric and spectroscopic observations to study the object. From optical R- and I-band light curves, the period of IRAS 18+09 is estimated to be 575 ± 30 days and the variability amplitudes range from ΔR ∼ 4.0 mag to ΔI ∼ 3.5 mag. From the standard period–luminosity relations, the distance (D) to the object, 4.0 ± 1.3 kpc, is estimated. Applying this distance in the radiative transfer model, the spectral energy distribution is constructed from multiwavelength photometric and IRAS-LRS spectral data, which provide the luminosity, optical depth, and gas mass-loss rate of the object to be 9600 ± 500 L {sub ⊙}, 9.1 ± 0.6 at 0.55 μm, and 1.0 × 10{sup −6} M {sub ⊙} yr{sup −1}, respectively. The current mass of the object is inferred to be in the range 1.0−1.5 M {sub ⊙} assuming solar metallicity. Notably, the temporal variation of atomic and molecular features (e.g., TiO, Na i, Ca i, CO, H{sub 2}O) over the pulsation cycle of the OH/IR star illustrates the sensitivity of the spectral features to the dynamical atmosphere as observed in pulsating AGB stars.

36 MATERIALS SCIENCE↗
DOE OSTI2016

ON HELIUM MIXING IN QUASI-GLOBAL SIMULATIONS OF THE INTRACLUSTER MEDIUM

The assumption of a spatially uniform helium distribution in the intracluster medium (ICM) can lead to biases in the estimates of key cluster parameters if composition gradients are present. The helium concentration profile in galaxy clusters is unfortunately not directly observable. Current models addressing the putative sedimentation are one-dimensional and parametrize the presence of magnetic fields in a crude way, ignoring the weakly collisional, magnetized nature of the medium. When these effects are considered, a wide variety of instabilities can play an important role in the plasma dynamics. In a series of recent papers, we have developed the local, linear theory of these instabilities and addressed their nonlinear development with a modified version of Athena. Here, we extend our study by developing a quasi-global approach that we use to simulate the mixing of helium as induced by generalizations of the heat-flux-driven buoyancy instability (HBI) and the magnetothermal instability, which feed off thermal and composition gradients. In the inner region of the ICM, mixing can occur over a few gigayears, after which the average magnetic field inclination angle is ∼30°–50°, resulting in an averaged Spitzer parameter higher by about 20% than the value obtained in homogeneous simulations. In the cluster outskirts the instabilities are rather inefficient, due to the shallow gradients. This suggests that composition gradients in cluster cores might be shallower than one-dimensional models predict. More quantitative statements demand more refined models that can incorporate the physics driving the sedimentation process and simultaneously account for the weakly collisional nature of the plasma.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

The HDUV Survey: Six Lyman Continuum Emitter Candidates at z ∼ 2 Revealed by HST UV Imaging

We present six galaxies at z∼2 that show evidence of Lyman continuum (LyC) emission based on the newly acquired UV imaging of the Hubble Deep UV legacy survey (HDUV) conducted with the WFC3/UVIS camera on the Hubble Space Telescope (HST). At the redshift of these sources, the HDUV F275W images partially probe the ionizing continuum. By exploiting the HST multiwavelength data available in the HDUV/GOODS fields, models of the UV spectral energy distributions, and detailed Monte Carlo simulations of the intergalactic medium absorption, we estimate the absolute ionizing photon escape fractions of these galaxies to be very high—typically >60% (>13% for all sources at 90% likelihood). Our findings are in broad agreement with previous studies that found only a small fraction of galaxies with high escape fraction. These six galaxies compose the largest sample yet of LyC leaking candidates at z∼2 whose inferred LyC flux has been observed at HST resolution. While three of our six candidates show evidence of hosting an active galactic nucleus, two of these are heavily obscured and their LyC emission appears to originate from star-forming regions rather than the central nucleus. Extensive multiwavelength data in the GOODS fields, especially the near-IR grism spectra from the 3D-HST survey, enable us to study the candidates in detail and tentatively test some recently proposed indirect methods to probe LyC leakage. High-resolution spectroscopic follow-up of our candidates will help constrain such indirect methods, which are our only hope of studying f {sub esc} at z∼5−9 in the JWST era.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

The Discovery of a Gravitationally Lensed Supernova Ia at Redshift 2.22

Here, we present the discovery and measurements of a gravitationally lensed supernova (SN) behind the galaxy cluster MOO J1014+0038. Based on multi-band Hubble Space Telescope and Very Large Telescope (VLT) photometry of the supernova, and VLT spectroscopy of the host galaxy, we find a 97.5% probability that this SN is a SN Ia, and a 2.5% chance of a CC SN. Our typing algorithm combines the shape and color of the light curve with the expected rates of each SN type in the host galaxy. With a redshift of 2.2216, this is the highest redshift SN Ia discovered with a spectroscopic host-galaxy redshift. A further distinguishing feature is that the lensing cluster, at redshift 1.23, is the most distant to date to have an amplified SN. The SN lies in the middle of the color and light-curve shape distributions found at lower redshift, disfavoring strong evolution to z = 2.22. We estimate an amplification due to gravitational lensing of 2.8 +0.6 -0.5 (1.10 ± 0.23 mag)---compatible with the value estimated from the weak-lensing-derived mass and the mass-concentration relation from LambdaCDM simulations---making it the most amplified SN Ia discovered behind a galaxy cluster.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

NuSTAR Survey of Obscured Swift/BAT-selected Active Galactic Nuclei. II. Median High-energy Cutoff in Seyfert II Hard X-Ray Spectra

Broadband X-ray spectroscopy of the X-ray emission produced in the coronae of active galactic nuclei (AGNs) can provide important insights into the physical conditions very close to their central supermassive black holes. The temperature of the Comptonizing plasma that forms the corona is manifested through a high-energy cutoff that has been difficult to directly constrain even in the brightest AGN because it requires high-quality data at energies above 10 keV. In this paper we present a large collection of coronal cutoff constraints for obscured AGNs based on a sample of 130 AGNs selected in the hard X-ray band with Swift/BAT and observed nearly simultaneously with NuSTAR and Swift/XRT. Additionally, we find that under a reasonable set of assumptions regarding partial constraints the median cutoff is well constrained to 290 ± 20 keV, where the uncertainty is statistical and given at the 68% confidence level. We investigate the sensitivity of this result to our assumptions and find that consideration of various known systematic uncertainties robustly places the median cutoff between 240 and 340 keV. The central 68% of the intrinsic cutoff distribution is found to be between about 140 and 500 keV, with estimated uncertainties of 20 and 100 keV, respectively. In comparison with the literature, we find no clear evidence that the cutoffs in obscured and unobscured AGNs are substantially different. Our analysis highlights the importance of carefully considering partial and potentially degenerate constraints on the coronal high-energy cutoff in AGNs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Quantum communications system with integrated photonic devices

Security is increased in quantum communication (QC) systems lacking a true single-photon laser source by encoding a transmitted optical signal with two or more decoy-states. A variable attenuator or amplitude modulator randomly imposes average photon values onto the optical signal based on data input and the predetermined decoy-states. By measuring and comparing photon distributions for a received QC signal, a single-photon transmittance is estimated. Fiber birefringence is compensated by applying polarization modulation. A transmitter can be configured to transmit in conjugate polarization bases whose states of polarization (SOPs) can be represented as equidistant points on a great circle on the Poincare sphere so that the received SOPs are mapped to equidistant points on a great circle and routed to corresponding detectors. Transmitters are implemented in quantum communication cards and can be assembled from micro-optical components, or transmitter components can be fabricated as part of a monolithic or hybrid chip-scale circuit.

36 MATERIALS SCIENCE↗