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

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At least 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Fitting strategies of accretion column models and application to the broadband spectrum of Cen X-3

Due to the complexity of modeling the radiative transfer inside the accretion columns of neutron star binaries, their X-ray spectra are still commonly described with phenomenological models, e.g., a cut off power law. While the behavior of these models is well understood and they allow for a comparison of different sources and studying source behavior, the extent to which the underlying physics can be derived from the model parameters is very limited. During recent years, several physically motivated spectral models have been developed to overcome these limitations. Their application, however, is generally computationally much more expensive and they require a high number of parameters which are difficult to constrain. In particular, Becker & Wolff(2007) presented an analytical solution to the radiative transfer equation inside the accretion column assuming a velocity profile that is linear in the optical depth. An implementation of this model that is both fast and accurate enough to be fitted to observed spectra is available in XSPEC. The main difficulty of this implementation is that some solutions violate energy conservation and therefore have to be rejected by the user. We propose a novel fitting strategy that ensures energy conservation during theχ2-minimization which simplifies the application of the model considerably. We demonstrate this approach as well as a study of possible parameter degeneracies with a comprehensive Markov-Chain Monte Carlo analysis of the complete parameter space for a combined NuSTAR and Swift/XRT dataset of Cen X-3.The derived accretion-flow structure features a small column radius of∼63 m and a spectrum dominated by bulk-Comptonization of bremsstrahlung seed photons, in agreement with previous studies.

X-rays: binaries↗
NASA NTRS2021

Fitting Strategies of Accretion Column Models and Application to the Broadband Spectrum of Cen X-3

Due to the complexity of modeling the radiative transfer inside the accretion columns of neutron star binaries, their X-ray spectra are still commonly described with phenomenological models, e.g., a cut off power law. While the behavior of these models is well understood and they allow for a comparison of different sources and studying source behavior, the extent to which the underlying physics can be derived from the model parameters is very limited. During recent years, several physically motivated spectral models have been developed to overcome these limitations. Their application, however, is generally computationally much more expensive and they require a high number of parameters which are difficult to constrain. In particular, Becker & Wolff(2007) presented an analytical solution to the radiative transfer equation inside the accretion column assuming a velocity profile that is linear in the optical depth. An implementation of this model that is both fast and accurate enough to be fitted to observed spectra is available in XSPEC. The main difficulty of this implementation is that some solutions violate energy conservation and therefore have to be rejected by the user. We propose a novel fitting strategy that ensures energy conservation during theχ2-minimization which simplifies the application of the model considerably. We demonstrate this approach as well as a study of possible parameter degeneracies with a comprehensive Markov-Chain Monte Carlo analysis of the complete parameter space for a combined NuSTAR and Swift/XRT data-set of Cen X-3.The derived accretion-flow structure features a small column radius of∼63 m and a spectrum dominated by bulk-Comptonization of bremsstrahlung seed photons, in agreement with previous studies

Philipp Thalhammer↗
NASA NTRS2022

An Isolated Mass-gap Black Hole or Neutron Star Detected with Astrometric Microlensing

We present the analysis of five black hole candidates identified from gravitational microlensing surveys. Hubble Space Telescope astrometric data and densely sampled light curves from ground-based microlensing surveys are fit with a single-source, single-lens microlensing model in order to measure the mass and luminosity of each lens and determine if it is a black hole. One of the five targets (OGLE-2011-BLG-0462/MOA-2011-BLG-191 or OB110462 for short) shows a significant >1 mas coherent astrometric shift, little to no lens flux, and has an inferred lens mass of 1.6–4.4 M ⨀ . This makes OB110462 the first definitive discovery of a compact object through astrometric microlensing and it is most likely either a neutron star or a low-mass black hole. This compact-object lens is relatively nearby (0.70–1.92 kpc) and has a slow transverse motion of <30 kms -1 . OB110462 shows significant tension between models well fit to photometry versus astrometry, making it currently difficult to distinguish between a neutron star and a black hole. Additional observations and modeling with more complex system geometries, such as binary sources, are needed to resolve the puzzling nature of this object. For the remaining four candidates, the lens masses are <2M ⨀ , and they are unlikely to be black holes; two of the four are likely white dwarfs or neutron stars. We compare the full sample of five candidates to theoretical expectations on the number of black holes in the Milky Way (∼10 8 ) and find reasonable agreement given the small sample size.

Astrophysical black holes↗
DOE OSTI2017

An exponential–gamma mixture model for extreme Santa Ana winds

We analyze the behavior of extreme winds occurring in Southern California during the Santa Ana wind season using a latent mixture model. This mixture representation is formulated as a hierarchical Bayesian model and fit using Markov chain Monte Carlo. The two‐stage model results in generalized Pareto margins for exceedances and generates temporal dependence through a latent Markov process. This construction induces asymptotic independence in the response, while allowing for dependence at extreme, but subasymptotic, levels. We compare this model with a frequentist analogue where inference is performed via maximum pairwise likelihood. We use interval censoring to account for data quantization and estimate the extremal index and probabilities of multiday occurrences of extreme Santa Ana winds over a range of high thresholds.

Bopp, Gregory P.↗
DOE OSTI2018

On polymorphism for discrete evolutionary dynamics driven either by selection or segregation distortion

We revisit some problems arising in the context of multiallelic discrete-time and deterministic evolutionary dynamics driven first by fitness differences and then by segregation distortion. In the model with fitness, we describe classes of fitness matrices exhibiting polymorphism. In the segregation case, still in search for conditions of polymorphism, we focus on a class of skew-symmetric matrices with a unique strictly positive kernel vector. Our main results reduce the study of these cases to the analysis of stochastic matrices.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Automated vehicle microscopic energy consumption study (AV-Micro): Data collection and model development

While the Adaptive Cruise Control (ACC) system in automated vehicles (AVs) is expected to impact transportation energy significantly, existing AV energy consumption models only directly adopt those developed with Human-driven Vehicle (HV) data without even slight adaptation or calibration to accommodate unique AV energy consumption features. This study will investigate how accurately HV data-based models can predict the energy consumption of AVs. Empirical trajectory data and corresponding instantaneous energy consumption rates from both AVs and HVs were collected. We adopted two classical HV data-based models to fit these data. The calibration results indicated that these models yield around 20 30% prediction errors for AVs. To further improve the prediction accuracy, this study designed an AV-Micro model by incorporating components of multiple classic energy consumption models that better capture ACC energy consumption features, including piecewise driving behavior. With this, the AV-Micro model achieves lower than 10% prediction errors. The AV-Micro model’s high consistency across different test runs was verified with statistical significance tests, demonstrating its adaptability in different driving profiles. To confirm the discrepancies between the energy consumption features of AVs and HVs, more statistical significance tests were conducted to show that the AV-Micro model cannot be directly applied to HV data. The findings by calibrated AV-Micro models revealed that AVs consume approximately 80.5–146.4 J more energy than HVs for each meter traveled. Furthermore, the frequency analysis of energy consumption indicates that there is still some room for AVs to improve energy efficiency, particularly given their larger amplitude high-frequency fluctuations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

TIDAL STREAM MORPHOLOGY AS AN INDICATOR OF DARK MATTER HALO GEOMETRY: THE CASE OF PALOMAR 5

This paper presents an example where the morphology of a single stellar stream can be used to rule out a specific galactic potential form without the need for velocity information. We investigate the globular cluster Palomar 5 (Pal 5), which is tidally disrupting into a cold, thin stream mapped over 22 deg on the sky with a typical width of 0.7 deg. We generate models of this stream by fixing Pal 5's present-day position, distance, and radial velocity via observations, while allowing its proper motion to vary. In a spherical dark matter halo we easily find models that fit the observed morphology. However, no plausible Pal 5 model could be found in the triaxial potential of Law and Majewski, which has been proposed to explain the properties of the Sagittarius stream. In this case, the long, thin, and curved morphology of the Pal 5 stream alone can be used to rule out such a potential configuration. Pal 5-like streams in this potential are either too straight, missing the curvature of the observations, or show an unusual morphology which we dub stream-fanning: a signature sensitive to the triaxiality of a potential. We conclude that the mere existence of other thin tidal streams must provide broad constraints on the orientation and shape of the dark matter halo they inhabit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Accretion disc sizes from continuum reverberation mapping of AGN selected from the ZTF survey

ABSTRACT We present the accretion disc-size estimates for a sample of 19 active galactic nuclei (AGNs) using the optical g-, r-, and i-band light curves obtained from the Zwicky Transient Facility survey. All the AGNs have reliable supermassive black hole (SMBH) mass estimates based on previous reverberation mapping measurements. The multiband light curves are cross-correlated, and the reverberation lag is estimated using the Interpolated Cross-Correlation Function method and the Bayesian method using the javelin code. As expected from the disc-reprocessing arguments, the g − r band lags are shorter than the g − i band lags for this sample. The interband lags for all, but five sources, are larger than the sizes predicted from the standard Shakura Sunyaev (SS) analytical model. We fit the light curves directly using a thin disc model implemented through the javelin code to get the accretion disc sizes. The disc sizes obtained using this model are on an average 3.9 times larger than the prediction based on the SS disc model. We find a weak correlation between the disc sizes and the known physical parameters, namely the luminosity and the SMBH mass. In the near future, a large sample of AGNs covering broader ranges of luminosity and SMBH mass from large photometric surveys would be helpful in a better understanding of the structure and physics of the accretion disc.

Jha, Vivek Kumar (ORCID:0000000232776335)↗
DOE OSTI2015

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit and model complexity according to AIC{sub c}. With parameters fixed, the model reasonably predicted detectability of human observers in blended FBP-IMR images. Semianalytic internal noise computation gave results equivalent to Monte Carlo, greatly speeding parameter estimation. Using Model-k4, the authors found an average detectability improvement of 2.7 ± 0.4 times that of FBP. IMR showed greater improvements in detectability with larger signals and relatively consistent improvements across signal contrast and x-ray dose. In the phantom tested, Model-k4 predicted an 82% dose reduction compared to FBP, verified with physical CT scans at 80% reduced dose. Conclusions: IMR improves detectability over FBP and may enable significant dose reductions. A channelized Hotelling observer with internal noise proportional to channel output standard deviation agreed well with human observers across a wide range of variables, even across reconstructions with drastically different image characteristics. Utility of the model observer was demonstrated by predicting the effect of image processing (blending), analyzing detectability improvements with IMR across dose, size, and contrast, and in guiding real CT scan dose reduction experiments. Such a model observer can be applied in optimizing parameters in advanced iterative reconstruction algorithms as well as guiding dose reduction protocols in physical CT experiments.

60 APPLIED LIFE SCIENCES↗
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↗
NASA NTRS2000

A Comprehensive Model of the Near-Earth Magnetic Field

The near-Earth magnetic field is due to sources in Earth's core, ionosphere, magnetosphere, lithosphere, and from coupling currents between ionosphere and magnetosphere and between hemispheres. Traditionally, the main field (low degree internal field) and magnetospheric field have been modeled simultaneously, and fields from other sources modeled separately. Such a scheme, however, can introduce spurious features. A new model, designated CMP3 (Comprehensive Model: Phase 3), has been derived from quiet-time Magsat and POGO satellite measurements and observatory hourly and annual means measurements as part of an effort to coestimate fields from all of these sources. This model represents a significant advancement in the treatment of the aforementioned field sources over previous attempts, and includes an accounting for main field influences on the magnetosphere, main field and solar activity influences on the ionosphere, seasonal influences on the coupling currents, a priori characterization of ionospheric and magnetospheric influence on Earth-induced fields, and an explicit parameterization and estimation of the lithospheric field. The result of this effort is a model whose fits to the data are generally superior to previous models and whose parameter states for the various constituent sources are very reasonable.

Sabaka, Terence J.↗
NASA NTRS2017

Column Number Density Expressions Through M = 0 and M = 1 Point Source Plumes Along Any Straight Path

Providers of payloads carried aboard the International Space Station must conduct analyses to demonstrate that any planned gaseous venting events generate no more than a certain level of material that may interfere with optical measurements from other experiments or payloads located nearby. This requirement is expressed in terms of a maximum column number density (CND). Depending on the level of rarefaction, such venting may be characterized by effusion for low flow rates, or by a sonic distribution at higher levels. Since the relative locations of other sensitive payloads are often unknown because they may refer to future projects, this requirement becomes a search for the maximum CND along any path.In another application, certain astronomical observations make use of CND to estimate light attenuation from a distant star through gaseous plumes, such as the Fermi Bubbles emanating from the vicinity of the black hole at the center of our Milky Way galaxy, in order to infer the amount of material being expelled via those plumes.This paper presents analytical CND expressions developed for general straight paths based upon a free molecule point source model for steady effusive flow and for a distribution fitted to model flows from a sonic orifice. Among other things, in this Mach number range it is demonstrated that the maximum CND from a distant location occurs along the path parallel to the source plane that intersects the plume axis. For effusive flows this value is exactly twice the CND found along the ray originating from that point of intersection and extending to infinity along the plumes axis. For sonic plumes this ratio is reduced to about 43.

Venting↗
NASA NTRSDate not supplied

Application of a Bayesian Framework for Plasticity Model Selection

Interpretable Machine Learning (IML) has performed well when tasked with deriving constitutive material models. However, IML has been shown to prefer models that overfit noise in data, which tends to lead to bloat and a decrease in interpretability. Due to these issues, the ability of IML to reliably derive models that fit the data and are both interpretable and generalizable is limited. A method developed recently has shown promise to improve upon traditional IML by using a Bayesian fitness definition for the evolution of free-form models with non-deterministic parameters. This framework was developed for genetic-programming-based symbolic regression(GPSR) and involves model parameter estimation using Sequential Monte Carlo sampling (SMC).The method has demonstrated a reduction in bloat when dealing with noisy data in comparison to conventional GPSR. The results of this framework applied to stress-strain data for copper show models that more effectively predict the experimental data better than was previously shown with GPSR.

plasticity↗