Search NASA⌕ Search

SEARCH · Search NASA

Results for “Model fitting”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

3C 273 with NuSTAR: Unveiling the active galactic nucleus

We present results from a 244 ks NuSTAR observation of 3C 273 obtained during a cross-calibration campaign with the Chandra, INTEGRAL, Suzaku, Swift, and XMM-Newton observatories. We show that the spectrum, when fit with a power-law model using data from all observatories except INTEGRAL over the 1–78 keV band, leaves significant residuals in the NuSTAR data between 30 and 78 keV. The NuSTAR 3–78 keV spectrum is well described by an exponentially cutoff power law (Γ=1.646±0.006, E{sub cutoff}=202{sub −34}{sup +51} keV) with a weak reflection component from cold, dense material. There is also evidence for a weak (EW=23±11 eV) neutral iron line. We interpret these features as arising from coronal emission plus reflection off an accretion disk or distant material. Beyond 80 keV INTEGRAL data show clear excess flux relative to an extrapolation of the active galactic nucleus model fit to NuSTAR. This high-energy power law is consistent with the presence of a beamed jet, which begins to dominate over emission from the inner accretion flow at 30–40 keV. Modeling the jet locally (in the NuSTAR + INTEGRAL band) as a power law, we find that the coronal component is fit by Γ{sub AGN}=1.638±0.045, E{sub cutoff}=47±15 keV, and jet photon index by Γ{sub jet}=1.05±0.4. We also consider Fermi/LAT observations of 3C 273, and here the broadband spectrum of the jet can be described by a log-parabolic model, peaking at ∼2 MeV. Finally, we investigate the spectral variability in the NuSTAR band and find an inverse correlation between flux and Γ.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Study of GRB light-curve decay indices in the afterglow phase

In this work, we study the distribution of temporal power-law decay indices, α, in the gamma-ray burst (GRB) afterglow phase, fitted for 176 GRBs (139 long GRBs, 12 short GRBs with extended emission, and 25 X-ray flashes) with known redshifts. These indices are compared with the temporal decay index, α {sub W}, derived with the light-curve fitting using the Willingale et al. model. This model fitting yields similar distributions of α {sub W} to the fitted α, but for individual bursts a difference can be significant. Analysis of (α, L {sub a}) distribution, where L {sub a} is the characteristic luminosity at the end of the plateau, reveals only a weak correlation of these quantities. However, we discovered a significant regular trend when studying GRB α values along the Dainotti et al. correlation between L {sub a} and the end time of the plateau emission in the rest frame, T{sub a}{sup ∗}, hereafter LT correlation. We note a systematic variation of the α parameter distribution with luminosity for any selected T{sub a}{sup ∗}. We analyze this systematics with respect to the fitted LT correlation line, expecting that the presented trend may allow us to constrain the GRB physical models. We also attempted to use the derived correlation of α(T{sub a}) versus L{sub a}(T{sub a}) to diminish the luminosity scatter related to the variations of α along the LT distribution, a step forward in the effort of standardizing GRBs. A proposed toy model accounting for this systematics applied to the analyzed GRB distribution results in a slight increase of the LT correlation coefficient.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Suppressing simulation bias in multi-modal data using transfer learning

Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning↗
DOE OSTI2021

Radon Kinetics in a Basement Space Measured with Different Devices

Although indoor monitoring of radon and benchmarking of radon measurement devices remain important research topics, few intercomparisons of active radon measurement devices have been performed under realistic conditions, let alone dynamic ones enabling comparison of their transient behavior. Five different radon monitors were therefore placed in a poorly ventilated basement space under three different conditions: 24 h under a steady, elevated radon level, 24 h with fans turned on to produce a radon washout transient, and 9 d with fans turned off for a radon buildup transient. Resulting radon concentrations varied between ~200 and ~2,000 Bq m -3 . Accuracy of the devices were evaluated using root-mean-square error, and ventilation data were fit to first order linear compartmental models. To more accurately model behaviors such as cyclic diurnal variations, the source term corresponding to entry of radon from soil into the basement was considered to be non-constant, as it is likely to vary drastically with both the indoor-outdoor pressure differential and soil concentration variations. Here, the improved radon washout model fit very well with the measurements. Despite a wide variety in list prices, all devices performed similarly during transients and at different radon concentrations.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

3D CFD Model Validation Using Benchmark Data of 1/16th Scaled VHTR Upper Plenum and Development of Wall Heat-Transfer Correlation For Laminar Flow

With support from the U.S. Department of Energy-Office of Nuclear Energy’s (DOE-NE’s) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an effort has been pursued to support high-temperature gas-cooled reactor (HTGR) technology development and its modeling and simulation needs. There is a particular need for advanced modeling and simulation tools to predict thermal-fluid behavior in the nuclear reactor primary system, especially in the core and the lower and upper plena, during safety-related transients. In this report, two main such activities are presented relevant to the HTGRs: (1) three-dimensional (3D) computational fluid dynamics (CFD) validation using benchmark data from the upper plenum of Texas A&M University’s 1/16th scaled very-high-temperature gas-cooled reactor (VHTR), and (2) development of wall heat-transfer correlation for laminar flow in a wall-heated pipe. The CFD tool validation exercises can be helpful to choose the models and CFD tools to simulate and design specific components of the HTRGs such as upper plenum where jet mixing is a complex phenomenon. In a loss of forced circulation event, the laminar flow can be observed during the development of natural circulation flow. This work includes the development and validation of heat transfer correlations for laminar flow using the Nek5000 CFD code due to limited available experimental data for laminar flow conditions to guide low-order models (1D). In this report, the flow characteristics of a single isothermal jet discharging into the upper plenum was investigated using the Nek5000 Large-Eddy Simulation (LES) CFD tool. Several numerical simulations were performed for various jet-discharged Reynolds numbers ranging from 3,413 to 12,819. A grid-independent study was performed. The numerical results of mean velocity, root-mean-square fluctuating velocity, and Reynolds stress were compared against the benchmark data. Good agreement was obtained between simulated and measured data for axial mean velocities, except near the upper plenum hemisphere. The maximum predicted errors for axial mean velocities at various normalized coolant channel diameter heights of 1, 5, and 10 are 1.56%, 1.88%, and 3.82%, respectively. In addition, the predicted root-mean-square fluctuating velocity and Reynolds stress are qualitatively in agreement with the experimental data. The Nek5000 code was used to develop wall-heat transfer correlation for laminar flow in a cylindrical tube. Several simulations were performed for various Reynolds flow and wall-heat fluxes. A new heat transfer correlation was developed using data from Nek5000 simulation results and regression functions in Matlab. The developed heat transfer correlation is valid for various Reynolds flows from 200 to 2000. The predicted R² value for model fit was 0.875, which ensures that 87.5% of the model data lies on the Nek5000 data. Moreover, a machine learning (ML) tool was used to train and test the Nek5000 data. A good fit of the ML-based model was observed with the test data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Oxidation and Condensation of Zinc Fume From Zn-CO 2 -CO-H 2 O Streams Relevant to Steelmaking Off-Gas Systems

Here the objective of this research was to study the condensation of zinc vapor to metallic zinc and zinc oxide solid under varying environments to investigate the feasibility of in-process separation of zinc from steelmaking off-gas dusts. Water vapor content, temperature, degree of cooling, gas composition, and initial zinc partial pressure were varied to simulate the possible conditions that can occur within steelmaking off-gas systems, limited to Zn-CO 2 -CO-H 2 O gas compositions. The temperature of deposition and the effect of rapidly quenching the gas were specifically studied. A homogeneous nucleation model for applicable experiments was applied to the analysis of the experimental data. It was determined that under the experimental conditions, oxidation of zinc vapor by H 2 O or CO 2 does not occur above 1108 K (835 °C) even for highly oxidizing streams (CO 2 /CO = 40/7). Rate expressions that correlate CO 2 and H 2 O oxidation rates to gas composition, partial pressure of water vapor, temperature, and zinc partial pressure were determined to be as follows: Rate $ \left(\frac{mol}{m^2s}\right) $ = 406 exp $ \left(\frac{-50.2 kJ/mol}{RT}\right) $ (pZnpCO 2 $-$ PCO/K eq CO 2 ) $\frac{mol}{m^2 x s}$ Rate $ \left(\frac{mol}{m^2s}\right) $ = 32.9 exp $ \left(\frac{-13.7 kJ/mol}{RT}\right) $ (pZnPH 2 O $-$ PH 2 /K eq H 2 O) $\frac{mol}{m^2 x s}$. It was proven that a rapid cooling rate (500 K/s) significantly increases the ratio of metallic zinc to zinc oxide as opposed to a slow cooling rate (250 K/s). SEM analysis found evidence of heterogeneous growth of ZnO as well as of homogeneous formation of metallic zinc. The homogeneous nucleation model fit well with experiments where only metallic zinc deposited. An expanded model with rates of oxidation by CO 2 and H 2 O as shown was combined with the homogenous nucleation model and then compared with experimental data. The calculated results based on the model gave a reasonable fit to the measured data. For the conditions used in this study, the rate equations for the oxidation of zinc by carbon dioxide and water vapor as well as the homogeneous nucleation model of metallic zinc were applicable for various temperatures, zinc partial pressures, CO 2 :CO ratios, and H 2 O partial pressures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Local models for scatter estimation and descattering in polyenergetic X-ray tomography

We propose a new modeling approach for scatter estimation and descattering in polyenergetic X-ray computed tomography (CT) based on fitting models to local neighborhoods of a training set. X-ray CT is widely used in medical and industrial applications. X-ray scatter, if not accounted for during reconstruction, creates a loss of contrast in CT reconstructions and introduces severe artifacts including cupping, shading, and streaks. Even when these qualitative artifacts are not apparent, scatter can pose a major obstacle in obtaining quantitatively accurate reconstructions. Our approach to estimating scatter is, first, to generate a training set of 2D radiographs with and without scatter using particle transport simulation software. To estimate scatter for a new radiograph, we adaptively fit a scatter model to a small subset of the training data containing the radiographs most similar to it. We compared local and global (fit on full data sets) versions of several X-ray scatter models, including two from the recent literature, as well as a recent deep learning-based scatter model, in the context of descattering and quantitative density reconstruction of simulated, spherically symmetrical, single-material objects comprising shells of various densities. Our results show that, when applied locally, even simple models provide state-of-the-art descattering, reducing the error in density reconstruction due to scatter by more than half.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Observations and modeling of the companions of short period binary millisecond pulsars: evidence for high-mass neutron stars

We present observations of fields containing eight recently discovered binary millisecond pulsars using the telescopes at MDM Observatory. Optical counterparts to four of these systems are detected, one of which, PSR J2214+3000, is a novel detection. Additionally, we present the fully phase-resolved B, V, and R light curves of the optical counterparts to two objects, PSR J1810+1744 and PSR J2215+5135 for which we employ model fitting using the eclipsing light curve (ELC) model of Orosz and Hauschildt to measure the unknown system parameters. For PSR J1810+1744, we find that the system parameters cannot be fit even assuming that 100% of the spin-down luminosity of the pulsar is irradiating the secondary, and so radial velocity measurements of this object will be required for the complete solution. However, PSR J2215+5135 exhibits light curves that are extremely well constrained using the ELC model and we find that the mass of the neutron star is constrained by these and the radio observations to be M {sub NS} > 1.75 M {sub ☉} at the 3σ level. We also find a discrepancy between the model temperature and the measured colors of this object, which we interpret as possible evidence for an additional high-temperature source such as a quiescent disk. Given this and the fact that PSR J2215+5135 contains a relatively high mass companion (M {sub c} > 0.1 M {sub ☉}), we propose that similar to the binary pulsar systems PSR J1023+0038 and IGR J18245–2452, the pulsar may transition between accretion- and rotation-powered modes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Reduction Kinetics of Perovskite Oxides for Selective Hydrogen Combustion in the Context of Olefin Production

Chemical looping represents a novel approach for generating light olefins in which thermal cracking or catalytic dehydrogenation is coupled with selective hydrogen combustion (SHC) by a metal oxide redox catalyst, which enables autothermal operation, increased per-pass conversion, and greater-than-equilibrium yields. Recent studies indicate that Na 2 WO 4 -promoted perovskite oxides are effective redox catalysts with high olefin selectivity. Herein, kinetic parameters, rates, and reaction models for the reduction of unpromoted and Na 2 WO 4 -promoted CaMnO 3 redox catalysts by H 2 , C 2 H 4 , and C 2 H 6 , is reported. Reduction rates of CaMnO 3 under ethylene and ethane are significantly lower than under H 2 . Additionally, model fitting of reduction kinetics show good agreement with reaction order–controlled models for CaMnO 3 reduction and predict greater oxygen site dependence and higher activation energy for CaMnO 3 reduction by C 2 H 4 as compared with H 2 . Avrami–Erofe'ev nucleation and growth models provide the best fit to the reduction of Na 2 WO 4 /CaMnO 3 in H 2 and in C 2 H 4 . After Na 2 WO 4 promotion, the reduction rate of CaMnO 3 is three orders of magnitude lower in ethylene in comparison to hydrogen, consistent with its superior selectivity to hydrogen combustion. The models developed can be applied toward reactor design and optimization in the context of enhanced olefin production via SHC under a cyclic redox scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Models of the Hydrodynamic Histories of Post-AGB Stars. I. Multiflow Shaping of OH 231.8+04.2

We present a detailed hydrodynamic model that matches the present structure of the well-observed preplanetary nebula (“pPN”) OH 231.8+04.2 (“OH231”). The purpose of the model is to present a physically justified and coherent picture of its evolutionary history from about 100 years from the start of the formation of its complex outer structures to the present. We have adopted a set of initial conditions that are heavily constrained by high-quality observations of its present structure and kinematics. The shaping of the nebula occurs while the densities of the flows are “light,” i.e., less than the surrounding AGB-wind environment. The simulations show that pairs of essentially coeval clumps and sprays of the same extent and density, but different outflow speeds, sculpted both the pair of thin axial flow “or spine” and the bulbs. The total ejected mass and momentum in the best-fit model are surprisingly large—3 M {sub ⊙} and 2.2 × 10{sup 41} gm cm s{sup −1}, respectively—however, these values are reduced by up to a factor of 10 in other models that fit the data almost as well. Our ultimate goal is to combine the present model results of masses, momenta, flow speeds, and flow geometries for OH231 with those of other models to be published in the future in order to find common attributes of their ejection histories.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Response of CR-39 nuclear track detectors to protons with non-normal incidence

This paper presents data from experiments with protons at non-normal incidence to CR-39 nuclear track detectors, analyzing the properties of detection efficiency, proton track diameter, track contrast, and track eccentricity. Understanding the CR-39 response to protons incident at an angle is important for designing charged particle detectors for inertial confinement fusion (ICF) applications. This study considers protons with incident energies less than 3 MeV. In this regime, an incident angle of 10° has no effect on CR-39 detection efficiency, and >85% detection efficiency is preserved up through 25° in the range of 1.0 MeV–2.1 MeV. For ICF applications, incident angles above 30° are deemed impractical for detector design due to significant drops in proton detection at all energies. We observe significant reductions in detection efficiency compared to theoretical predictions, particularly at low energies where proton tracks are etched away. The proton track diameter measured by the scan system is observed to decrease with higher incident angles. The track diameters are analyzed with two fitting models, and it is shown that the diameter–energy relation can be fit with the existing models at angles up to 30° . The optical contrast of the tracks tends to increase with the angle, meaning that the tracks are fainter, and a larger increase is observed for higher energies. Eccentricity, a measure of how elongated proton tracks are, increases with the incident angle and drops after the critical angle. The lowest energy tracks remain nearly circular even at higher angles.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Response of CR-39 nuclear track detectors to protons with non-normal incidence

This paper presents data from experiments with protons at non-normal incidence to CR-39 nuclear track detectors, analyzing the properties of detection efficiency, proton track diameter, track contrast, and track eccentricity. Understanding the CR-39 response to protons incident at an angle is important for designing charged particle detectors for inertial confinement fusion (ICF) applications. This study considers protons with incident energies less than 3 MeV. In this regime, an incident angle of 10° has no effect on CR-39 detection efficiency, and >85% detection efficiency is preserved up through 25° in the range of 1.0 MeV–2.1 MeV. For ICF applications, incident angles above 30° are deemed impractical for detector design due to significant drops in proton detection at all energies. We observe significant reductions in detection efficiency compared to theoretical predictions, particularly at low energies where proton tracks are etched away. The proton track diameter measured by the scan system is observed to decrease with higher incident angles. The track diameters are analyzed with two fitting models, and it is shown that the diameter–energy relation can be fit with the existing models at angles up to 30°. The optical contrast of the tracks tends to increase with the angle, meaning that the tracks are fainter, and a larger increase is observed for higher energies. Eccentricity, a measure of how elongated proton tracks are, increases with the incident angle and drops after the critical angle. The lowest energy tracks remain nearly circular even at higher angles.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Missing components in ΛCDM from DESI Y1 baryonic acoustic oscillation measurements: Insights from redshift remapping

We explore transformations of the Friedman-Lemaître-Robertson-Walker (FLRW) metric and cosmological parameters that align with observational data while aiming to gain insights into potential extensions of standard cosmological models. We modified the FLRW metric by introducing a scaling factor, e 2Θ(a) –the cosmological scaling function (CSF), which alters the standard relationship between cosmological redshift and the cosmic scale factor without affecting angular measurements or cosmic microwave background (CMB) anisotropies. Using data from DESI Year 1, Pantheon+ supernovae, and the Planck CMB temperature power spectrum, we constrained both the CSF and cosmological parameters through a Markov chain Monte Carlo approach. Our results indicate that the CSF model fits observational data with a lower Hubble constant (although it is compatible with the value given by Planck 2018 within 1σ) and is predominantly dark matter dominated. Additionally, the CSF model produces temperature and lensing power spectra similar to those predicted by the standard model, though with lower values in the CSF model at large scales. We also checked that when fitting a CSF model without dark energy to the data, we obtain a more negative conformal function. This suggests that the CSF model may offer hints about missing elements and opens up a new avenue for exploring physical interpretations of cosmic acceleration.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Validation of sea ice models using an uncertainty-based distance metric for multiple model variables: NEW METRIC FOR SEA ICE MODEL VALIDATION

Here, we implement a variance-based distance metric (D n ) to objectively assess skill of sea ice models when multiple output variables or uncertainties in both model predictions and observations need to be considered. The metric compares observations and model data pairs on common spatial and temporal grids improving upon highly aggregated metrics (e.g., total sea ice extent or volume) by capturing the spatial character of model skill. The D n metric is a gamma-distributed statistic that is more general than the χ 2 statistic commonly used to assess model fit, which requires the assumption that the model is unbiased and can only incorporate observational error in the analysis. The D n statistic does not assume that the model is unbiased, and allows the incorporation of multiple observational data sets for the same variable and simultaneously for different variables, along with different types of variances that can characterize uncertainties in both observations and the model. This approach represents a step to establish a systematic framework for probabilistic validation of sea ice models. The methodology is also useful for model tuning by using the D n metric as a cost function and incorporating model parametric uncertainty as part of a scheme to optimize model functionality. We apply this approach to evaluate different configurations of the standalone Los Alamos sea ice model (CICE) encompassing the parametric uncertainty in the model, and to find new sets of model configurations that produce better agreement than previous configurations between model and observational estimates of sea ice concentration and thickness.

58 GEOSCIENCES↗
DOE OSTI2019

High Removal Capacity of Arsenic from Drinking Water Using Modified Magnetic Polyurethane Foam Nanocomposites

In this study, a novel polyurethane foam (PU) nanocomposite adsorbent based on silane-modified magnetic iron-oxide nanoparticles (Fe{sub 3}O{sub 4}@APTES) is synthesized via a low cost and simple in situ polymerization method for the removal of arsenic ions from aqueous solutions. The chemical structure and surface morphology of the prepared nanoparticles and adsorbent were characterized using Fourier transform infrared spectroscopy, attenuated total reflection, scanning electron microscopy, transmission electron microscopy, and energy-dispersive X-ray spectroscopy. Inductively coupled plasma mass spectrometry was used to measure the arsenic concentration of the treated solutions. Sorption isotherms models were applied to determine the adsorption mechanism and modeling parameters. The removal capacity of the modified PU foam was at its highest during a contact time of four hours which resulted in a removal capacity of 95%. Kinetic studies were conducted to determine the adsorption capacity and the uptake rate of arsenic. A Pseudo-order model was found to be the best fit model for adsorption. The prepared adsorbent can be separated from the solution by using an external magnet field.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Similarity Metric for Data Optimization and Efficient Training of Reactive Machine Learning Force Fields for Hydrocarbon Radiolysis

Radiolysis is a common approach to sterilize polymers, chemically modify them for upcycling, and accelerate their decomposition for recycling purposes. Reactive molecular dynamics (MD) simulations provide a powerful tool to generate atomic-level trajectories of the reactive processes and quantify radiolytic chemical degradation pathways. For this, machine learning (ML) surrogate models for reactive force fields with quantum mechanical accuracy are now widely used, which require ML training data sets that can provide information on atomic environments for target chemical systems. However, radiolysis chemistry can be highly complex and diverse, which poses significant challenges for generating training data to parametrize ML models. In this regard, we developed a method for optimizing the training data set using a cosine similarity metric to help guide training set selection for radiolysis of polyethylene, a model hydrocarbon polymer, as well as to enhance the transferability of our reactive ML force field (MLFF) to a variety of molecular and polymeric systems. Our approach performs atom-by-atom comparisons between local atomic environments to pinpoint important data points associated with rare and localized events, such as radiolysis damage within structures. We apply this approach to train the Chebyshev Interaction Model for Efficient Simulation (ChIMES) MLFF model, which expresses the atomic interaction potentials in terms of linear combinations of many-body Chebyshev polynomials. We first show that our method can reduce our training set size by ∼70% while improving overall accuracy compared to more standard MD model fitting approaches. We then validate our optimum model against diverse hydrocarbon simulation data, including simple alkanes and systems with unsaturated carbon bonds, over a wide range of thermodynamic conditions. Finally, we use our ChIMES model to perform MD simulations of radiolytic damage with large-scale systems that help avoid system size effects. Overall, our approach yields an MD force field that retains most of the accuracy of the underlying quantum method while yielding many orders of improvement in computational efficiency. In conclusion, our efforts will have impact on future hydrocarbon polymer radiolysis studies, where the chemical details of the polymer–radiation interactions can have a strong effect on the resulting products observed in experiments.

Hydrocarbons↗
DOE OSTI2014

A broadband X-ray study of the Geminga pulsar with NuSTAR And XMM-Newton

We report on the first hard X-ray detection of the Geminga pulsar above 10 keV using a 150 ks observation with the Nuclear Spectroscopic Telescope Array (NuSTAR) observatory. The double-peaked pulse profile of non-thermal emission seen in the soft X-ray band persists at higher energies. Broadband phase-integrated spectra over the 0.2-20 keV band with NuSTAR and archival XMM-Newton data do not fit to a conventional two-component model of a blackbody plus power law, but instead exhibit spectral hardening above ∼5 keV. We find that two spectral models fit the data well: (1) a blackbody (kT {sub 1} ∼ 42 eV) with a broken power law (Γ{sub 1} ∼ 2.0, Γ{sub 2} ∼ 1.4 and E {sub break} ∼ 3.4 keV) and (2) two blackbody components (kT {sub 1} ∼ 44 eV and kT {sub 2} ∼ 195 eV) with a power-law component (Γ ∼ 1.7). In both cases, the extrapolation of the Rayleigh-Jeans tail of the thermal component is consistent with the UV data, while the non-thermal component overpredicts the near-infrared data, requiring a spectral flattening at E ∼ 0.05-0.5 keV. While strong phase variation of the power-law index is present below ∼5 keV, our phase-resolved spectroscopy with NuSTAR indicates that another hard non-thermal component with Γ ∼ 1.3 emerges above ∼5 keV. The spectral hardening in non-thermal X-ray emission as well as spectral flattening between the optical and X-ray bands argue against the conjecture that a single power law may account for multi-wavelength non-thermal spectra of middle-aged pulsars.

79 ASTRONOMY AND ASTROPHYSICS↗