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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

HEPfit: a code for the combination of indirect and direct constraints on high energy physics models

HEPfit is a flexible open-source tool which, given the Standard Model or any of its extensions, allows to (i) fit the model parameters to a given set of experimental observables; (ii) obtain predictions for observables. HEPfit can be used either in Monte Carlo mode, to perform a Bayesian Markov Chain Monte Carlo analysis of a given model, or as a library, to obtain predictions of observables for a given point in the parameter space of the model, allowing HEPfit to be used in any statistical framework. In the present version, around a thousand observables have been implemented in the Standard Model and in several new physics scenarios. In this paper, we describe the general structure of the code as well as models and observables implemented in the current release.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

A multiscale model of the action of a capsid assembly modulator for the treatment of chronic hepatitis B

Chronic hepatitis B virus (HBV) infection is strongly associated with increased risk of liver cancer and cirrhosis. While existing treatments effectively inhibit the HBV life cycle, viral rebound frequently occurs following treatment interruption. Consequently, functional cure rates of chronic HBV infection remain low and there is increased interest in a novel treatment modality, capsid assembly modulators (CAMs). Here, we develop a multiscale mathematical model of CAM treatment in chronic HBV infection. By fitting the model to participant data from a phase I trial of the first-generation CAM vebicorvir, we estimate the drug’s dose-dependent effectiveness and identify the physiological mechanisms that drive the observed biphasic decline in HBV DNA and RNA, and mechanistic differences between HBeAg-positive and negative infection. Finally, we demonstrate analytically and numerically that the relative change of HBV RNA more accurately reflects the antiviral effectiveness of a CAM than the relative change in HBV DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Publishing statistical models: Getting the most out of particle physics experiments

The statistical models used to derive the results of experimental analyses are of incredible scientific value and are essential information for analysis preservation and reuse. In this paper, we make the scientific case for systematically publishing the full statistical models and discuss the technical developments that make this practical. By means of a variety of physics cases - including parton distribution functions, Higgs boson measurements, effective field theory interpretations, direct searches for new physics, heavy flavor physics, direct dark matter detection, world averages, and beyond the Standard Model global fits - we illustrate how detailed information on the statistical modelling can enhance the short- and long-term impact of experimental results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

DISCOVERY OF BROAD MOLECULAR LINES AND OF SHOCKED MOLECULAR HYDROGEN FROM THE SUPERNOVA REMNANT G357.7+0.3: HHSMT, APEX, SPITZER , AND SOFIA OBSERVATIONS

We report a discovery of shocked gas from the supernova remnant (SNR) G357.7+0.3. Our millimeter and submillimeter observations reveal broad molecular lines of CO(2-1), CO(3-2), CO(4-3), {sup 13}CO (2-1), and {sup 13}CO (3-2), HCO{sup +}, and HCN using the Heinrich Hertz Submillimeter Telescope, the Arizona 12 m Telescope, APEX, and the MOPRA Telescope. The widths of the broad lines are 15–30 km s{sup −1}, and the detection of such broad lines is unambiguous, dynamic evidence showing that the SNR G357.7+0.3 is interacting with molecular clouds. The broad lines appear in extended regions (>4.′5 × 5′). We also present the detection of shocked H{sub 2} emission in the mid-infrared but lacking ionic lines using Spitzer /IRS observations to map a few-arcminute area. The H{sub 2} excitation diagram shows a best fit with a two-temperature local thermal equilibrium model with the temperatures of ∼200 and 660 K. We observed [C ii] at 158 μ m and high- J CO(11-10) with the German Receiver for Astronomy at Terahertz Frequencies (GREAT) on the Stratospheric Observatory for Infrared Astronomy. The GREAT spectrum of [C ii], a 3 σ detection, shows a broad line profile with a width of 15.7 km{sup −1} that is similar to those of broad CO molecular lines. The line width of [C ii] implies that ionic lines can come from a low-velocity C-shock. Comparison of H{sub 2} emission with shock models shows that a combination of two C-shock models is favored over a combination of C- and J-shocks or a single shock. We estimate the CO density, column density, and temperature using a RADEX model. The best-fit model with n (H{sub 2}) = 1.7 × 10{sup 4} cm{sup −3}, N(CO) = 5.6 × 10{sup 16} cm{sup −2}, and T = 75 K can reproduce the observed millimeter CO brightnesses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

A Comparison of Two Methods for Estimating Black Hole Spin in Active Galactic Nuclei

Angular momentum, or spin, is a fundamental property of black holes (BHs), yet it is much more difficult to estimate than mass or accretion rate (for actively accreting systems). In recent years, high-quality X-ray observations have allowed for detailed measurements of the Fe K α emission line, where relativistic line broadening allows constraints on the spin parameter (the X-ray reflection method). Another technique uses accretion disk models to fit the AGN continuum emission (the continuum-fitting, or CF, method). Although each technique has model-dependent uncertainties, these are the best empirical tools currently available and should be vetted in systems where both techniques can be applied. A detailed comparison of the two methods is also useful because neither method can be applied to all AGN. The X-ray reflection technique targets mostly local ( z ≲ 0.1) systems, while the CF method can be applied at higher redshift, up to and beyond the peak of AGN activity and growth. Here, we apply the CF method to two AGN with X-ray reflection measurements. For both the high-mass AGN, H1821+643, and the Seyfert 1, NGC 3783, we find a range in spin parameter consistent with the X-ray reflection measurements. However, the near-maximal spin favored by the reflection method for NGC 3783 is more probable if we add a disk wind to the model. Refinement of these techniques, together with improved X-ray measurements and tighter BH mass constraints, will permit this comparison in a larger sample of AGN and increase our confidence in these spin estimation techniques.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Source Characterization of the Declared North Korean Nuclear Tests From Regional Distance Coda Wave Spectral Ratios

Abstract Seismic observations of underground nuclear explosions provide crucial data on source yield and depth that cannot easily be estimated from other geophysical methods. However, it is difficult to obtain reliable yield estimates for test sites for which we do not have direct seismic calibration experiments. To obtain source information from uncalibrated sites and paths, local and regional seismic records of six, proximal, declared underground nuclear explosions in North Korea are used to compute spectral ratios of narrow‐band waveform envelopes of body‐wave coda that remove path and site effects to reveal precise, relative source moment. The yields of these explosions are obtained from the observed source ratios by simultaneously fitting the classical source model of Mueller and Murphy (1971), https://doi.org/10.1785/bssa0610061675 to all event pairs. The source model provides an impressive fit to the observations considering that the P phase coda derived source spectral ratios did not require a prior knowledge of the source or regionally calibrated corrections to be applied to the data. However, the observed corner frequencies from S wave coda spectral ratios are lower than the source model predictions, but are well fit by models calculated using the corner frequency consistent with the Fisk conjecture. The results presented here provide novel constraints on the spectral distributions of the energy radiated by the sources of the DPRK test series, and allows for an independent evaluation of existing estimated source model parameters.

58 GEOSCIENCES↗
DOE OSTI2012

Measuring neutrino masses with a future galaxy survey

We perform a detailed forecast on how well a EUCLID-like photometric galaxy and cosmic shear survey will be able to constrain the absolute neutrino mass scale. Adopting conservative assumptions about the survey specifications and assuming complete ignorance of the galaxy bias, we estimate that the minimum mass sum of Σm{sub ν} ≅ 0.06 eV in the normal hierarchy can be detected at 1.5σ to 2.5σ significance, depending on the model complexity, using a combination of galaxy and cosmic shear power spectrum measurements in conjunction with CMB temperature and polarisation observations from PLANCK. With better knowledge of the galaxy bias, the significance of the detection could potentially reach 5.4σ. Interestingly, neither PLANCK+shear nor PLANCK+galaxy alone can achieve this level of sensitivity; it is the combined effect of galaxy and cosmic shear power spectrum measurements that breaks the persistent degeneracies between the neutrino mass, the physical matter density, and the Hubble parameter. Notwithstanding this remarkable sensitivity to Σm{sub ν}, EUCLID-like shear and galaxy data will not be sensitive to the exact mass spectrum of the neutrino sector; no significant bias ( < 1σ) in the parameter estimation is induced by fitting inaccurate models of the neutrino mass splittings to the mock data, nor does the goodness-of-fit of these models suffer any significant degradation relative to the true one (Δχ{sub eff}{sup 2} < 1)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Contrasts in compliant fault zone properties inferred from geodetic measurements in the San Francisco Bay area

In crustal fault zones, regions of damaged rock characterized by reduced elastic shear modulus can influence patterns of near-field interseismic deformation. In order to study these compliant fault zones (CFZs) and how they might develop over the lifetimes of faults, we compare two fault segments with contrasting fault age and lithology along the San Andreas Fault in the San Francisco Bay Area. New geodetic measurements of the interseismic velocity fields at each location are used to constrain fault zone parameters through a Markov chain Monte Carlo method. At Black Mountain, in the Santa Cruz Mountains of the San Francisco Peninsula, we do not find evidence for a compliant fault zone; instead, we find that the geodetic data are more consistent with a model of a single fault in a homogeneous elastic half-space. At Lake San Andreas, a younger fault segment 35 km farther north, we find evidence for a compliant fault zone about 3.4 +1.1/-1.4 km wide, containing a shear modulus of about 40% of the shear modulus of the surrounding rock. We also find that the best fitting CFZ model at this location, unlike the best fitting homogeneous half-space model, has a locking depth that agrees well with the observed depth of microseismicity. Based on differences in fault age, cumulative displacement, and lithology between Black Mountain and Lake San Andreas, we infer that lithology plays an important and, in this case, perhaps a dominant role in the accumulation of fault zone damage structures and the development of CFZs over the lifetime of a fault.

58 GEOSCIENCES↗
DOE OSTI2023

Scalable computations for nonstationary Gaussian processes

Nonstationary Gaussian process models can capture complex spatially varying dependence structures in spatial datasets. However, the large number of observations in modern datasets makes fitting such models computationally intractable with conventional dense linear algebra. In addition, derivative-free or even first-order optimization methods can be very slow to converge when estimating many spatially varying parameters. In this paper, we present a computational framework which couples an algebraic block diagonal plus low-rank covariance matrix approximation with stochastic trace estimation to facilitate the efficient use of second-order solvers for maximum likelihood estimation of Gaussian process models with many parameters. We demonstrate the effectiveness of these methods by simultaneously fitting 192 parameters in the popular nonstationary model of Paciorek and Schervish using 107,600 sea surface temperature anomaly measurements.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Solid and gas thermal conductivity models improvement and validation in various porous insulation materials

In the past few decades, significant efforts have been made to improve the theoretical understanding of thermal transport mechanisms in thermal insulation materials and push the thermal conductivity's lower limits. However, most works focused singularly on specific types of materials, and the models used for thermal conductivity predictions are diverse - a model that fits one material might not fit others. Here, we improve and unify the gas and solid thermal conductivity models for porous materials. Through experimental characterization of several different materials as well as literature data for other materials, these models are validated. Further, we have also found that the pressure-dependent gas thermal conductivity of most materials can be well fitted by using one or two pore sizes without using a complex pore size distribution. With the refined models, we decompose the effective thermal conductivity of several thermal insulation materials into gas, solid, and radiation contributions. For cellular (polystyrene and polyurethane) foams, the relative contributions from air, solid, and radiation are 58–75%, 3–11%, 16–38%, respectively. For granular porous materials (polyurethane and silica in this work), the contributions from air, solid, and radiation are 45–66%, 34–46%, and 0–8%, respectively. This work is expected to provide guidance on the design and optimization of the next generation of thermal insulation materials, for example, through the effort of reducing gas conduction and radiation in foams and suppressing gas and solid conduction in aerogels.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Overcoming significant challenges in extracting off-stoichiometric thermodynamics using the compound energy formalism through complementary use of experimental and first principles data: A case study of Ba 1-x Sr x FeO 3-δ

The compound energy formalism (CEF) is a powerful framework to describe the thermodynamics of metal oxides as a function of off-stoichiometry, temperature, and composition. The thermodynamic properties are crucial materials design attributes in metal oxide-based oxygen-exchange chemical processes. Despite the richness of information an accurate CEF model provides, a method to determine a unique and accurate fit for oxygen exchange materials remains elusive. This contribution details a method for fitting the CEF model that overcomes the current fitting challenges through three innovations: 1) the combination of density functional theory calculations with experimental data decorrelates excess terms and delineates the enthalpic/entropic contributions to the Gibbs free energy; 2) a systematic determination of the important CEF model terms, removing thermodynamic predetermining human intervention; 3) a self-consistent solution of the starting oxygen offstoichiometry (δ 0 ) of thermogravimetric measurements. Thus, our method enables the reliable extraction of off-stoichiometric metal oxide thermodynamic properties and facilitates rapid materials compositional screening, and reliable process design of systems dependent on off-stoichiometric redox-active metal oxides. We apply this method to a Ba x Sr 1-x FeO 3-δ test case. We find by systematically examining the performance of the CEF model fit with and without each innovation that all three innovations are necessary for an accurate fit. We determined that reduction enthalpy is higher and more sensitive to off-stoichiometry when the Sr fraction is large (139.5 and 185.3 kJ/mol O 2 for SrFeO 3 at δ = 0 and δ = 0.5, respectively vs. nearly constant 83 kJ/mol O 2 for BaFeO 3 ). However, the reduction entropy is mostly insensitive to Sr fraction, but highly dependent on δ suggesting larger contributions in the non-configurational entropy parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Timing the r -process Enrichment of the Ultra-faint Dwarf Galaxy Reticulum II

The ultra-faint dwarf galaxy Reticulum II (Ret II) exhibits a unique chemical evolution history, with ${72}_{-12}^{+10}$% of its stars strongly enhanced in r-process elements. We present deep Hubble Space Telescope photometry of Ret II and analyze its star formation history. As in other ultra-faint dwarfs, the color–magnitude diagram is best fit by a model consisting of two bursts of star formation. If we assume that the bursts were instantaneous, then the older burst occurred around the epoch of reionization, forming ~80% of the stars in the galaxy, while the remainder of the stars formed ~3 Gyr later. When the bursts are allowed to have nonzero durations, we obtain slightly better fits. The best-fitting model in this case consists of two bursts beginning before reionization, with approximately half the stars formed in a short (100 Myr) burst and the other half in a more extended period lasting 2.6 Gyr. Considering the full set of viable star formation history models, we find that 28% of the stars formed within 500 ± 200 Myr of the onset of star formation. The combination of the star formation history and the prevalence of r-process-enhanced stars demonstrates that the r-process elements in Ret II must have been synthesized early in its initial star-forming phase. We therefore constrain the delay time between the formation of the first stars in Ret II and the r-process nucleosynthesis to be less than 500 Myr. This measurement rules out an r-process source with a delay time of several Gyr or more, such as GW170817.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Time-integrated activity coefficient estimation for radionuclide therapy using PET and a pharmacokinetic model: A simulation study on the effect of sampling schedule and noise

Purpose: The aim of this study was to investigate the accuracy of PET-based treatment planning for predicting the time-integrated activity coefficients (TIACs). Methods: The parameters of a physiologically based pharmacokinetic (PBPK) model were fitted to the biokinetic data of 15 patients to derive assumed true parameters and were used to construct true mathematical patient phantoms (MPPs). Biokinetics of 150 MBq {sup 68}Ga-DOTATATE-PET was simulated with different noise levels [fractional standard deviation (FSD) 10%, 1%, 0.1%, and 0.01%], and seven combinations of measurements at 30 min, 1 h, and 4 h p.i. PBPK model parameters were fitted to the simulated noisy PET data using population-based Bayesian parameters to construct predicted MPPs. Therapy simulations were performed as 30 min infusion of {sup 90}Y-DOTATATE of 3.3 GBq in both true and predicted MPPs. Prediction accuracy was then calculated as relative variability v{sub organ} between TIACs from both MPPs. Results: Large variability values of one time-point protocols [e.g., FSD = 1%, 240 min p.i., v{sub kidneys} = (9 ± 6)%, and v{sub tumor} = (27 ± 26)%] show inaccurate prediction. Accurate TIAC prediction of the kidneys was obtained for the case of two measurements (1 and 4 h p.i.), e.g., FSD = 1%, v{sub kidneys} = (7 ± 3)%, and v{sub tumor} = (22 ± 10)%, or three measurements, e.g., FSD = 1%, v{sub kidneys} = (7 ± 3)%, and v{sub tumor} = (22 ± 9)%. Conclusions: {sup 68}Ga-DOTATATE-PET measurements could possibly be used to predict the TIACs of {sup 90}Y-DOTATATE when using a PBPK model and population-based Bayesian parameters. The two time-point measurement at 1 and 4 h p.i. with a noise up to FSD = 1% allows an accurate prediction of the TIACs in kidneys.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Uncertain characterization of reservoir fluids due to brittleness of equation of state regression

Equations of state (EoS) play a central role in modeling the phase equilibrium of fluid mixtures. Their parameterization involves fitting a model to experimental data, i.e., solving a nonlinear, non-convex, multivariate optimization problem. The latter requires one to select design variables, domains of definition for each variable, and weights assigned to individual measurements. We demonstrate that subjective choices of an optimization algorithm and an initial guess also impact the regression process. Consequently, EoS predictions are fundamentally uncertain even after the EoS tuning to a limited set of experimental data points. We demonstrate this observation for two hydrocarbon reservoir fluids, in which five properties of the heaviest carbon fraction are treated as design variables. While all the optimization algorithms and initial guesses match experimental data for the gas and liquid properties, the resulting EoS parameterizations lead to dramatically different predictions of the fluid’s thermophysical behavior in the unsampled pressure and temperature regions. In conclusion, we propose the probabilistic treatment of design variables to quantify the predictive uncertainty of the resulting fluid models.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Surrogate modelling the Baryonic Universe II: On forward modelling the colours of individual and populations of galaxies

ABSTRACT Among the properties shaping the light of a galaxy, the star formation history (SFH) is one of the most challenging to model due to the variety of correlated physical processes regulating star formation. In this work, we leverage the stellar population synthesis model fsps, together with SFHs predicted by the hydrodynamical simulation IllustrisTNG and the empirical model universemachine, to study the impact of star formation variability on galaxy colours. We start by introducing a model-independent metric to quantify the burstiness of a galaxy formation model, and we use this metric to demonstrate that universemachine predicts SFHs with more burstiness relative to IllustrisTNG. Using this metric and principal component analysis, we construct families of SFH models with adjustable variability, and we show that the precision of broad-band optical and near-infrared colours degrades as the level of unresolved short-term variability increases. We use the same technique to demonstrate that variability in metallicity and dust attenuation presents a practically negligible impact on colours relative to star formation variability. We additionally provide a model-independent fitting function capturing how the level of unresolved star formation variability translates into imprecision in predictions for galaxy colours; our fitting function can be used to determine the minimal SFH model that reproduces colours with some target precision. Finally, we show that modelling the colours of individual galaxies with per cent-level precision demands resorting to complex SFH models, while producing precise colours for galaxy populations can be achieved using models with just a few degrees of freedom.

Chaves-Montero, Jonás (ORCID:0000000295534261)↗
DOE OSTI2017

A nondestructive method to estimate the chlorophyll content of Arabidopsis seedlings

Chlorophyll content decreases in plants under stress conditions, therefore it is used commonly as an indicator of plant health. Arabidopsis thaliana offers a convenient and fast way to test physiological phenotypes of mutations and treatments. But, chlorophyll measurements with conventional solvent extraction are not applicable to Arabidopsis leaves due to their small size, especially when grown on culture dishes. We provide a nondestructive method for chlorophyll measurement whereby the red, green and blue (RGB) values of a color leaf image is used to estimate the chlorophyll content from Arabidopsis leaves. The method accommodates different profiles of digital cameras by incorporating the ColorChecker chart to make the digital negative profiles, to adjust the white balance, and to calibrate the exposure rate differences caused by the environment so that this method is applicable in any environment. We chose an exponential function model to estimate chlorophyll content from the RGB values, and fitted the model parameters with physical measurements of chlorophyll contents. As further proof of utility, this method was used to estimate chlorophyll content of G protein mutants grown on different sugar to nitrogen ratios. Our method is a simple, fast, inexpensive, and nondestructive estimation of chlorophyll content of Arabidopsis seedlings. This method lead to the discovery that G proteins are important in sensing the C/N balance to control chlorophyll content in Arabidopsis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

West Flank Coso FORGE: Magnetotelluric Inversion

The Coso Magnetotelluric (MT) dataset of which the West Flank FORGE MT data is a subset, was collected by Schlumberger / WesternGeco and initially processed by the WesternGeco GeoSolutions Integrated EM Center of Excellence in Milan, Italy. The 2011 data was based on 99 soundings that were centered on the West Flank geothermal prospect. The new soundings along with previous data from 2003 and 2006 were incorporated into a 3D inversion. Full impedance tensor data were inverted in the 1-3000 Hz range. The modelling report notes several noise sources, specifically the DC powerline that is 20,000 feet west of the survey area, and may have affected data in the 0.02 to 10 Hz range. Model cell dimensions of 450 x 450 x 65 feet were used to avoid computational instability in the 3D model. The fit between calculated and observed MT values for the final model run had an RMS value of 1.807. The included figure from the WesternGeco report shows the sounding locations from the 2011, 2006 and 2003 surveys.

15 GEOTHERMAL ENERGY↗