Engineering Papers⌕ Search

SEARCH · Engineering Papers

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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

η Carinae's Dusty Homunculus Nebula from Near-infrared to Submillimeter Wavelengths: Mass, Composition, and Evidence for Fading Opacity

Infrared observations of the dusty, massive Homunculus Nebula around the luminous blue variable η Carinae are crucial to characterize the mass-loss history and help constrain the mechanisms leading to the great eruption. We present the 2.4–670 μm spectral energy distribution, constructed from legacy Infrared Space Observatory observations and new spectroscopy obtained with the Herschel Space Observatory. Using radiative transfer modeling, we find that the two best-fit dust models yield compositions that are consistent with CNO-processed material, with iron, pyroxene and other metal-rich silicates, corundum, and magnesium-iron sulfide in common. Spherical corundum grains are supported by the good match to a narrow 20.2 μm feature. Our preferred model contains nitrides AlN and Si{sub 3}N{sub 4} in low abundances. Dust masses range from 0.25 to 0.44 M{sub ⊙}, but M{sub tot}⩾45 M{sub ⊙} in both cases, due to an expected high Fe gas-to-dust ratio. The bulk of dust is within a 5{sup ′′}×7{sup ′′} central region. An additional compact feature is detected at 390 μm. We obtain L{sub IR} = 2.96 × 10{sup 6} L{sub ⊙}, a 25% decline from an average of mid-IR photometric levels observed in 1971–1977. This indicates a reduction in circumstellar extinction in conjunction with an increase in visual brightness, allowing 25%–40% of optical and UV radiation to escape from the central source. We also present an analysis of {sup 12}CO and {sup 13}CO J = 5–4 through 9–8 lines, showing that the abundances are consistent with expectations for CNO-processed material. The [{sup 12}C ii] line is detected in absorption, which we suspect originates in foreground material at very low excitation temperatures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

On-board state of health monitoring of batteries using incremental capacity analysis

A method is provided for determining capacity of a battery. The method includes: defining a model for a battery, where the model relates terminal voltage of the battery to charged capacity of the battery; taking a plurality of voltage measures of the battery, where the voltage measures are taken through a range of states of charge and the range excludes the battery being fully charged and fully discharged; determining the parameters of the model by fitting the plurality of voltage measures to the model; determining an incremental capacity curve for the battery by taking derivative of the model; and quantifying a peak of the incremental capacity curve to thereby determine a capacity of the battery.

Sun, Jing↗
DOE OSTI2015

UNSUPERVISED TRANSIENT LIGHT CURVE ANALYSIS VIA HIERARCHICAL BAYESIAN INFERENCE

Historically, light curve studies of supernovae (SNe) and other transient classes have focused on individual objects with copious and high signal-to-noise observations. In the nascent era of wide field transient searches, objects with detailed observations are decreasing as a fraction of the overall known SN population, and this strategy sacrifices the majority of the information contained in the data about the underlying population of transients. A population level modeling approach, simultaneously fitting all available observations of objects in a transient sub-class of interest, fully mines the data to infer the properties of the population and avoids certain systematic biases. We present a novel hierarchical Bayesian statistical model for population level modeling of transient light curves, and discuss its implementation using an efficient Hamiltonian Monte Carlo technique. As a test case, we apply this model to the Type IIP SN sample from the Pan-STARRS1 Medium Deep Survey, consisting of 18,837 photometric observations of 76 SNe, corresponding to a joint posterior distribution with 9176 parameters under our model. Our hierarchical model fits provide improved constraints on light curve parameters relevant to the physical properties of their progenitor stars relative to modeling individual light curves alone. Moreover, we directly evaluate the probability for occurrence rates of unseen light curve characteristics from the model hyperparameters, addressing observational biases in survey methodology. We view this modeling framework as an unsupervised machine learning technique with the ability to maximize scientific returns from data to be collected by future wide field transient searches like LSST.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Sci—Fri PM: Dosimetry—04: Radiation out-of-field dose in the treatment of pediatric central nervous system malignancies

Children diagnosed with central nervous system (CNS) malignancies often receive radiotherapy, which can cause radiogenic late effects. In order to identify and reduce the risk of these late effects, we must understand the radiation doses that these children receive. Modern treatment planning systems accurately estimate the absorbed dose within the treatment fields but poorly estimate the dose outside them. The purpose of our study was to measure the out-of-field dose for children receiving localized radiotherapy for CNS cancer and apply an analytical model for estimating dose as a function of distance from the field edge. Radiation fields designed for a 12-year-old boy treated in our clinic were applied to an anthropomorphic phantom containing more than 200 thermoluminescent dosimeters. A double-Gaussian function of absorbed dose versus distance from the field edge (i.e., 50% isodose line) was applied, and parameters were allowed to vary and were fit to the model by minimizing the root mean square deviation, RMSD. The fitted model accurately predicted the dose from distances of 4 cm to 50 cm (RMSD = 0.54 cGy/Gy), but the model was not useful in estimating dose for distances less than 4 cm because of wide variation in measured dose, and the double-Gaussian model failed by systematically underestimating the dose beyond 50 cm. In conclusion, the double-Gaussian model may be applicable for points at distances from the field edge between 4 cm and 50 cm, where most children's radiosensitive tissues are located, but for points beyond 50 cm, an improvement should be investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

PHAT. XIX. The Ancient Star Formation History of the M31 Disk

We map the star formation history across M31 by fitting stellar evolution models to color–magnitude diagrams of each 83″ × 83″ (0.3 × 1.4 kpc, deprojected) region of the Panchromatic Hubble Andromeda Treasury (PHAT) survey outside of the innermost 6{sup ′}×12{sup ′} portion. We find that most of the star formation occurred prior to ∼8 Gyr ago, followed by a relatively quiescent period until ∼4 Gyr ago, a subsequent star formation episode about 2 Gyr ago, and a return to relative quiescence. There appears to be little, if any, structure visible for populations with ages older than 2 Gyr, suggesting significant mixing since that epoch. Finally, assuming a Kroupa initial mass function from 0.1 to 100 M {sub ⊙}, we find that the total amount of star formation over the past 14 Gyr in the area over which we have fit models is 5 × 10{sup 10} M {sub ⊙}. Fitting the radial distribution of this star formation and assuming azimuthal symmetry, (1.5 ± 0.2) × 10{sup 11} M {sub ⊙} of stars has formed in the M31 disk as a whole, (9 ± 2) × 10{sup 10} M {sub ⊙} of which has likely survived to the present after accounting for evolutionary effects. This mass is about one-fifth of the total dynamical mass of M31.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Inference on accretion flow dynamics using TCAF solution from the analysis of spectral evolution of H 1743-322 during the 2010 outburst

We study accretion flow dynamics of the Galactic transient black hole candidate (BHC) H 1743-322 during its 2010 outburst by analyzing spectral data using the two-component advective flow (TCAF; Keplerian and sub-Keplerian) solution after its inclusion in XSPEC as a local model. We compare our TCAF solution fitted results with combined disk blackbody (DBB) and power-law (PL) model fitted results and find a similar smooth variation of thermal (Keplerian or DBB) and non-thermal (PL or sub-Keplerian) fluxes/rates in two types of model fits. For a spectral analysis, 2.5-25 keV spectral data from the Rossi X-Ray Timing Explorer Proportional Counter Array instrument are used. From the TCAF solution fit, accretion flow parameters, such as Keplerian rate, sub-Keplerian rate, location of centrifugal pressure-supported shock, and strength of the shock, are extracted, providing a deeper understanding of the accretion process and properties of accretion disks around BHC H 1743-322 during its X-ray outburst. Based on the halo to disk accretion rate ratio, shock properties, accretion rates, and the nature of the quasi-periodic oscillations' (if observed) entire outburst is classified into four different spectral states: hard, hard-intermediate, soft-intermediate, and soft. From the time variation of intrinsic flow parameters, it appears that their evolutions in the declining phase do not retrace the path of the rising phase. Since our current model does not include magnetic fields, spectral turnover at energies beyond 500-600 keV cannot be explained.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Using Maximum Circular Velocity in Halo Occupation Distribution Models to Predict Galaxy Clustering

Abstract Standard halo occupation distribution (HOD) models predict how galaxies occupy halos based on a single property, the virial mass, M vir . To incorporate galaxy assembly bias, we consider alternative halo mass proxies to use in the HOD. A promising replacement is maximum circular velocity, V max , which measures the halo’s potential well, and successfully predicts galaxy clustering in subhalo abundance matching models. We fit galaxy clustering measurements from SDSS DR7 with two modified HODs besides the standard M vir -based model: one where V max is used as the halo property that determines galaxy occupation, and the other adopting an adjustable combination of M vir and V max . Except for the reduced volume M r < − 20 threshold sample fit with V max alone, neither change improves the model performance in predicting the projected two-point correlation function, w p . We conclude that switching the primary variable to V max does not significantly improve the HOD model’s ability to fit galaxy clustering.

Mezini, Lorena↗
DOE OSTI2023

Evaluating E. coli genome‐scale metabolic model accuracy with high‐throughput mutant fitness data

Abstract The Escherichia coli genome‐scale metabolic model (GEM) is an exemplar systems biology model for the simulation of cellular metabolism. Experimental validation of model predictions is essential to pinpoint uncertainty and ensure continued development of accurate models. Here, we quantified the accuracy of four subsequent E. coli GEMs using published mutant fitness data across thousands of genes and 25 different carbon sources. This evaluation demonstrated the utility of the area under a precision–recall curve relative to alternative accuracy metrics. An analysis of errors in the latest (iML1515) model identified several vitamins/cofactors that are likely available to mutants despite being absent from the experimental growth medium and highlighted isoenzyme gene‐protein‐reaction mapping as a key source of inaccurate predictions. A machine learning approach further identified metabolic fluxes through hydrogen ion exchange and specific central metabolism branch points as important determinants of model accuracy. This work outlines improved practices for the assessment of GEM accuracy with high‐throughput mutant fitness data and highlights promising areas for future model refinement in E. coli and beyond.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

A revised model of ex-vivo reduction of hexavalent chromium in human and rodent gastric juices

Chronic oral exposure to hexavalent chromium (Cr-VI) in drinking water has been shown to induce tumors in the mouse gastrointestinal (GI) tract and rat oral cavity. The same is not true for trivalent chromium (Cr-III). Thus reduction of Cr-VI to Cr-III in gastric juices is considered a protective mechanism, and it has been suggested that the difference between the rate of reduction among mice, rats, and humans could explain or predict differences in sensitivity to Cr-VI. We evaluated previously published models of gastric reduction and believe that they do not fully describe the data on reduction as a function of Cr-VI concentration, time, and (in humans) pH. The previous models are parsimonious in assuming only a single reducing agent in rodents and describing pH-dependence using a simple function. We present a revised model that assumes three pools of reducing agents in rats and mice with pH-dependence based on known speciation chemistry. While the revised model uses more fitted parameters than the original model, they are adequately identifiable given the available data, and the fit of the revised model to the full range of data is shown to be significantly improved. Hence the revised model should provide better predictions of Cr-VI reduction when integrated into a corresponding PBPK model. - Highlights: • Hexavalent chromium (Cr-VI) reduction in gastric juices is a key detoxifying step. • pH-dependent Cr-VI reduction rates are explained using known chemical speciation. • Reduction in rodents appears to involve multiple pools of electron donors. • Reduction appears to continue after 60 min, although more slowly than initial rates.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Dynamics of water confined in lyotropic liquid crystals: Molecular dynamics simulations of the dynamic structure factor

The properties of water under confinement are of practical and fundamental interest. Here in this work we study the properties of water in the self-assembled lyotropic phases of gemini surfactants with a focus on testing the standard analysis of quasi-elastic neutron scattering (QENS) experiments. In QENS experiments the dynamic structure factor is measured and fit to models to extract the translational diffusion constant, D T , and rotational relaxation time, τ R . We test this procedure by using simulation results for the dynamic structure factor, extracting the dynamic parameters from the fit as is typically done in experiments, and comparing the values to those directly measured in the simulations. We find that the decoupling approximation, where the intermediate scattering function is assumed to be a product of translational and rotational contributions, is quite accurate. The jump-diffusion and isotropic rotation models, however, are not accurate when the degree of confinement is high. In particular, the exponential approximations for the intermediate scattering function fail for highly confined water and the values of D T and τ R can differ from the measured value by as much as a factor of two. Other models have more fit parameters, however, and with the range of energies and wave-vectors accessible to QENS, the typical analysis appears to be the best choice. In the most confined lamellar phase, the dynamics are sufficiently slow that QENS does not access a large enough time scale and neutron spin echo measurements would be a valuable technique in addition to QENS.

36 MATERIALS SCIENCE↗
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↗