Search NASA⌕ Search

SEARCH · Search NASA

Results for “Model fit”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Efficient lattice QCD computation of radiative-leptonic-decay form factors at multiple positive and negative photon virtualities

In previous work [D. Giusti, Methods for high-precision determinations of radiative-leptonic decay form factors using lattice QCD, Phys. Rev. D 107, 074507 (2023)], we showed that form factors for radiative leptonic decays of pseudoscalar mesons can be determined efficiently and with high precision from lattice QCD using the “three-dimensional (3D) method,” in which three-point functions are computed for all values of the current insertion time and the time integral is performed at the data-analysis stage. Here, we demonstrate another benefit of the 3D method: the form factors can be extracted for any number of nonzero photon virtualities from the same three-point functions at no extra cost. We present results for the $D_s → ℓνγ*$ vector form factor as a function of photon energy and photon virtuality, for both positive and negative virtuality, for a single ensemble with 340 MeV pion mass and 0.11 fm lattice spacing. In our analysis, we separately consider the two different time orderings and the different quark flavors in the electromagnetic current. We discuss in detail the behavior of the unwanted exponentials contributing to the three-point functions, as well as the choice of fit models and fit ranges used to remove them for various values of the virtuality. While positive photon virtuality is relevant for decays to multiple charged leptons, negative photon virtuality suppresses soft contributions and is of interest in QCD-factorization studies of the form factors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1994

Diffuse galactic continuum emission measured by COMPTEL and the cosmic-ray electron spectrum

Diffuse galactic continuum gamma-ray emission in the 0.75-30 MeV range from the inner Galaxy has been studied using data from COMPTEL on the Compton Gamma-Ray Observatory. Observations of the inner Galaxy from the Sky Survey have been used. The imaging properties of COMPTEL enable spatial analysis of the gamma-ray distribution using model fitting. A model based on atomic and molecular gas distributions in the Galaxy has been used to derive the emissivity spectrum of the gamma-ray emission and this spectrum is compared with theoretical estimates of bremsstrahlung emission from cosmic-ray electrons.

Strong, A. W.↗
NASA NTRS2014

Herschel Extreme Lensing Line Observations: Dynamics of Two Strongly Lensed Star-Forming Galaxies near Redshift z=2*

We report on two regularly rotating galaxies at redshift z approx. = 2, using high-resolution spectra of the bright [C microns] 158 micrometers emission line from the HIFI instrument on the Herschel Space Observatory. Both SDSS090122.37+181432.3 ("S0901") and SDSSJ120602.09+514229.5 ("the Clone") are strongly lensed and show the double-horned line profile that is typical of rotating gas disks. Using a parametric disk model to fit the emission line profiles, we find that S0901 has a rotation speed of v sin(i) approx. = 120 +/- 7 kms(sup −1) and a gas velocity dispersion of (standard deviation)g < 23 km s(sup −1) (1(standard deviation)). The best-fitting model for the Clone is a rotationally supported disk having v sin(i) approx. = 79 +/- 11 km s(sup −1) and (standard deviation)g 4 kms(sup −1) (1(standard deviation)). However, the Clone is also consistent with a family of dispersion-dominated models having (standard deviation)g = 92 +/- 20 km s(sup −1). Our results showcase the potential of the [C microns] line as a kinematic probe of high-redshift galaxy dynamics: [C microns] is bright, accessible to heterodyne receivers with exquisite velocity resolution, and traces dense star-forming interstellar gas. Future [C microns] line observations with ALMA would offer the further advantage of spatial resolution, allowing a clearer separation between rotation and velocity dispersion.

LENSING↗
DOE OSTI2022

Semi-analytic spectral fitting: simultaneously modelling the mass accumulation and chemical evolution in MaNGA spiral galaxies

We develop a novel semi-analytic spectral fitting approach to quantify the star formation histories (SFHs) and chemical enrichment histories (ChEHs) of individual galaxies. We construct simple yet general chemical evolution models that account for gas inflow and outflow processes as well as star formation, to investigate the evolution of merger-free star-forming systems. These models are fitted directly to galaxies’ absorption-line spectra, while their emission lines are used to constrain current gas phase metallicity and star formation rate. We apply this method to spiral galaxies selected from the SDSS-IV Mapping Nearby Galaxies at Apache Point Observatory survey. By fitting the co-added absorption-line spectra for each galaxy, and using the emission-line constraints on present-day metallicity and star formation, we reconstruct both the SFHs and the ChEHs for all objects in the sample. We can use these reconstructions to obtain archaeological measures of derived correlations such as the mass–metallicity relation at any redshift, which compare favourably with direct observations. We find that both the SFHs and ChEHs have strong mass dependence: massive galaxies accumulate their stellar masses and become enriched earlier. This mass dependence causes the observed flattening of the mass–metallicity relation at lower redshifts. The model also reproduces the observed gas-to-stellar mass ratio and its mass dependence. Moreover, we are able to determine that more massive galaxies have earlier gas infall times and shorter infall time-scales, and that the early chemical enrichment of low-mass galaxies is suppressed by strong outflows, while outflows are not very significant in massive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Some Peculiar Properties of Magnetic Clouds as Observed by the WIND Spacecraft

We aimed at understanding the common characteristics of magnetic clouds, relevant to solar-interplanetary connections, but exceptional ones were noted and are stressed here through a short compendium. The study is based on analyses of 28 good or better events (Out of 33 candidates) as identified in WIND magnetic field and plasma data. These cloud intervals are provided by WIND-MFI's Website under the URL (http://lepmfi.gsfc.nasa.gov/mfi/mag_cloud_publ.html#table). The period covered is from early 1995 to November 1998. A force free, cylindrically symmetric, magnetic field model has been applied to the field data in usually 1-hour averaged form for the cloud analyses. Some of the findings are: (1) one small duration event turned out to have an approximately normal size which was due to a distant almost "skimming" passage by the spacecraft; (2) One truly small event was observed, where 10 min averages had to be used in the model fitting; it had an excellent model fit and the usual properties of a magnetic cloud, except it possessed a small axial magnetic flux; (3) One cloud ha a dual axial-field-polarity, in the sense that the "core" had one polarity and the annular region around it had an opposite polarity. This event also satisfied the model and with a ve3ry good chi-squared value. Some others show a hint of this dual polarity; (4) The temporal distribution of occurrence clouds over the 4 years show a dip in 1996; (5) About 50 % of the clouds had upstream shocks; any others had upstream pressure pulses; (6) The overall average speed (390 km/s) of the best 28 events is less than the normally quoted for the average solar wind speed (420 km/s) The average of central cloud speed to the upstream solar wind speed was not much greater than one (1.08), even though many of these clouds were drivers of interplanetary shocks. Cloud expansion is partly the reason for the existence of upstream shocks; (7) The cloud axes often (about 50 % of the time) revealed reasonable attitudes with respect to the interpreted solar source, from simple geometry, but many bore no relationship, suggesting that their observations at 1 AU were probably those of the legs of the global cloud often having near-radial axes; (8) many clouds appear to have magnetic holes at or their their boundaries.

Berdichevsky, D.↗
DOE OSTI2021

Performance characterization of nanofiltration, reverse osmosis, and ion exchange technologies for acetic acid separation

A major obstacle to widespread implementation of bio-based fuels and chemicals is the lack of efficient and costeffective separation methods. To purify acetic acid produced by biochemical conversion of biomass via anaerobic digestion, this work employs two commonly used separation technologies: (1) ion-exchange (IX) resin and (2) pressure-driven membranes. This study tested five commercially available strong- and weak-base anion-exchange resins and five commercially available nanofiltration (NF) and reverse osmosis (RO) membranes. The pH of the feed solution significantly affected adsorption capacity. At pH 6.3, a strong-base IX resin (IRN-78) performed best (95.1% acetate removal). With strong-base IX resins, the Langmuir isotherm model fit well, whereas for weak-base IX resins, the Freundlich isotherm provided a better fit. A pseudo-second-order kinetic model fit well for both IRN-78 and IRA-67. Regarding membrane separation, RO (BW30XFR membrane) achieved the highest rejection (98.6% acetate rejection), whereas an NF membrane (NF*) achieved the best combination of permeate flux (105 L/(h∙m 2 )) and rejection (83.1% acetate rejection). For membrane performance, the experimental data were fit using the solution diffusion model. Increased pH in the feed solution lowered permeate flux but increased acetic acid rejection. Finally, then the acetic acid concentration in the feed solution increased, both permeate flux and acetic acid rejection decreased for membrane NF*.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Fourier domain dynamic correction method for complex optical fringes in laser spectrometers

A method is provided for Fourier domain dynamic correction of optical fringes in a laser spectrometer. The method includes Fourier transforming a background spectrum contaminated with the optical fringes to obtain baseline fringes in a frequency domain. The method includes partitioning the baseline fringes in the frequency domain to obtain partitioned baseline fringes. The method includes reconstructing the partitioned baseline fringes as separate spectra. The method includes constructing a fitting model to approximate the background spectrum by assigning a first and a second free parameter to each of partitioned baseline fringe components to respectively allow for drift and amplitude adjustments during a fitting of the fitting model. The method includes applying the fitting model to a newly acquired spectrum to provide an interpretation of the newly acquired spectrum having a reduced influence of spectral contamination on concentration retrieval.

Teng, Cheyenne↗
NASA NTRS2006

X-ray and Sunyaev-Zel'dovich Effect Measurements of the Gas Mass Fraction in Galaxy Clusters

We present gas mass fractions of 38 massive galaxy clusters spanning redshifts from 0.14 to 0.89, derived from Chandra X-ray data and OVRO/BIMA interferometric Sunyaev-Zel' dovich Effect (SZE) measurements. We use three models for the gas distribution: (1) an isothermal Beta-model fit jointly to the X-ray data at radii beyond 100 kpc and to all of the SZE data, (2) a nonisothermal double Beta-model fit jointly to all of the X-ray and SZE data, and (3) an isothermal Beta-model fit only to the SZE spatial data. We show that the simple isothermal model well characterizes the intracluster medium (ICM) outside of the cluster core, and provides consistently good fits to clusters spanning a wide range of morphological properties. The agreement in the results shows that the core can be satisfactorily accounted for by either excluding the core in fits to the X-ray data (the 100 kpc-cut model) or modeling the intracluster gas with a non-isothermal double Beta-model. We find that the SZE is largely insensitive to structure in the core.

LaRoque, Samuel J.↗
DOE OSTI2021

Quantitative analysis of Raman spectral parameters for carbon fibers: practical considerations and connection to mechanical properties

Although the literature on the Raman spectra of carbon fibers is vast, no consistent, robust predictive relationship between mechanical properties of carbon fibers and spectral parameters exists. This shortcoming is due to the use of numerous fitting functions to evaluate Raman spectra of carbon fibers and the inconsistencies in establishing the best fitting models in a statistically robust fashion. To address this gap, we present a comprehensive work on the Raman spectra of carbon fibers that combines a vast library of experimental data with a robust numerical analysis and a statistical evaluation of a wide range of suggested fitting models. This manuscript begins with a brief review of the commonly applied fitting models. Then, the Raman spectra of 32 commercially available polyacrylonitrile-based carbon fibers collected at excitation wavelengths 532, 633, and 785 nm are presented and the best fit for all fibers is evaluated based on several statistical criteria in conjunction with numerical calculations and physical arguments. The results suggest that high-performance fibers must be fit with at least five peaks, whereas high-tensile modulus fibers are best fit with at least six distinct peaks. Finally, we employ simultaneous fitting of the Raman spectra of specific fibers and wavelengths and demonstrate that strong correlations exist between mechanical properties and the D1 peak position and shape across the range of evaluated mechanical properties. Finally, we suggest straightforward improvements in fitting analysis procedures that can be implemented to increase coherency in the understanding of the underlying carbon fiber microstructure intuited from Raman spectroscopy.

36 MATERIALS SCIENCE↗
NASA NTRS2015

Validation of a Best-Fit Pharmacokinetic Model for Scopolamine Disposition after Intranasal Administration

An intranasal gel formulation of scopolamine (INSCOP) was developed for the treatment of Motion Sickness. Bioavailability and pharmacokinetics (PK) were determined per Investigative New Drug (IND) evaluation guidance by the Food and Drug Administration. Earlier, we reported the development of a PK model that can predict the relationship between plasma, saliva and urinary scopolamine (SCOP) concentrations using data collected from an IND clinical trial with INSCOP. This data analysis project is designed to validate the reported best fit PK model for SCOP by comparing observed and model predicted SCOP concentration‐time profiles after administration of INSCOP.

Wu, L.↗
DOE OSTI2025

Deriving Stable Peak Models to Fit Complex XPS Data From Cu Contaminated Pt Electrocatalysts

X-ray Photoelectron Spectroscopy spectra peak models, designed to partition photoemission signals emanating from different elements or chemical states within an atom, are fitted to data limited to an energy interval over which inelastically scattered photoemission signal can be estimated. While the choice of background approximation and line shapes of components to the peak model requires careful consideration, the energy interval used to define the data to which the peak model is optimized has a significant impact on the final peak model. The relationship between the background intensity and data intensity at the start and end of the energy interval dictates the line shapes used in the peak model. In this work, we devise a method to peak fit a complex overlapping Cu 3p and Pt 4f XPS peak structure to perform the elemental quantification. We first use an Al 2s peak to illustrate how background curves approach data at the limits of the energy interval over which the background is defined, influencing the analysis of XPS spectra. Next, we demonstrate the nature of interactions between specific line shapes (Voigt and pseudo-Voigt profiles) suitable for photoemission peaks and a specific background curve (Shirley) and a peak model is presented that includes components to the peak model that accommodates background intensity during fitting of the peak model to data. The peak model allowed for quantification of the contributions of Pt 4f peaks emanating from the substrate that exhibits strong asymmetry in the presence of the inhomogeneously distributed Cu species, mostly of Lorentzian character.

XPS↗
NASA NTRS2010

An Algorithm for the Fitting of Planet Models to Kepler Light Curves

We describe an algorithm which fits model planetary system parameters to light curves from Kepler Mission target stars. The algorithm begins by producing an initial model of the system which is used to seed the fit,with particular emphasis on obtaining good transit timing parameters. An attempt is then made to determine whether the observed transits are more likely due to a planet or an eclipsing binary. In the event that the transits are consistent with a transiting planet, an iterative fitting process is initiated: a wavelet-based whitening filter is used to eliminate stellar variations on timescales long compared to a transit; a robust nonlinear fitter operating on the whitened light curve produces a new model of the system; and the procedure iterates until convergence upon a self-consistent whitening filter and planet model. The fitted transits are removed from the light curve anda search for additional planet candidates is performed upon the residual light curve. The fitted models are used in additional tests which identify false positive planet detections: multiple planet candidates with near-identical fitted periods are far more likely to be an eclipsing binary, for example, while target stars in which the model lightcurve is correlated with the star centroid position may indicate a background eclipsing binary, and subtraction of all model planet candidates yields a light curve of pure noise and stellar variability, which can be used to study the probability that the planet candidates result from statistical fluctuations in the data.

Exoplanet↗
NASA NTRSDate not supplied

Quantifying radiation quality for space relevant radiation types: Fitting excess risk models to outbred mice data

Accurately quantifying the differences in radiation quality between space and terrestrial environments is important for predicting health risks for astronauts.Recently, Edmundson et al. 2020[1] provided valuable new results from out-bred mice linking tumor induction and genetic background aer exposure to low and high-LET radiation. The goal of the current study is to more rigorously estimate a relative biological effectiveness (RBE) factor by leveraging the solid tumor data from Edmundson et al. 2020. Excess relative risk (ERR) models and excess absolute risk (EAR) models were fit using Poisson regression similar to the models that the Radiation Effects Research Foundation uses to fit atomic bomb survivor data. Linear ERR and EAR slopes were simulated usingBayesian analyses, and RBE values were calculated from the ratio of the heavy ion linear slope to the gamma linear slope using the full posterior distribution.

Lori J. Chappell↗
NASA NTRS1979

An aperture synthesis study of Saturn and its rings at 3.71-cm wavelength

Aperture synthesis maps of Saturn and its ring system are presented. The maps are free from most of the assumptions about the brightness structure of Saturn that were used in a previous model-fitting analysis. Generally, the maps confirm the model-fitting results, with the exception that the brightness temperature of the planet determined by the models is greater than it needs to be in order to match the contours in the map. This discrepancy is attributed to random errors in the phase of the visibility function.

Schloerb, F. P.↗
DOE OSTI2021

Tensile Property and Lifetime Prediction for Low-Temperature Aged Uranium-Niobium Alloys

Thermal aging models and lifetime predictions for uranium-niobium (U-Nb) alloys were created using an approach similar to those previously employed. Lifetime estimates for generic U-6Nb components were thus updated; the reported value being 800 years. This update represents a small change in lifetime vs. that of the 2012 assessment (540 years). This lifetime estimate emerged from consideration of several model fits specific to the aging datasets and properties chosen. Aging was quantified using quasi-static tensile properties measured on specimens artificially aged for up to 10 years. The major change relative to the most recent 2012 LANL assessment was that a more comprehensive body of U-Nb literature data was mined, in addition to being augmented by the latest LANL and UK AWE data. The tensile data compilation was published separately (LANL report LA-14493, December 2016). Recognizing the chemical banding of industrially produced U-6Nb, models were developed for the mid-range (6 wt.%) and extrema (4 and 8 wt.%) compositions. Lifetime estimates were calculated for all three alloy classes (4, 6, 8 wt.% nominal) and two measures of total tensile elongation (TE) to failure, namely TE-ext. — extensometer method, and TE-NCD — normalized crosshead displacement method. The conservative assumption was made that whichever composition (4, 6, or 8 wt.% Nb) and property (TE-ext or TE-NCD) was the first to cross the ductility failure threshold would limit the lifetime of the entire component. Tensile strength properties did not figure into the lifetime predictions, but could be useful as age-sensitive diagnostics and were also modeled. Of these, only first yield strength is expected to show a change at 40°C aging vs. time = 0 over the ~100-year timespan of engineering interest. Second yield strength evolves more slowly, and ultimate tensile strength slower still. Among all the models, the apparent activation energies for aging were mostly in the narrow 29– 37 kcal/mol range, which is close to that for diffusion of Nb in gamma-uranium. This agreement may be coincidental. The data from recent long-term aging studies substantially improved the model fit quality and robustness of the lifetimes. Appendices document sensitivity studies of the model fits and lifetimes with respect to using more limited datasets. These results highlight the limitations of relying solely on data from scattered literature studies and smaller datasets more generally.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effects of random forest modeling decisions on biogeochemical time series predictions

Abstract Random forests (RF) are an increasingly popular machine learning approach used to model biogeochemical processes in the Earth system. While RF models are robust to many assumptions that complicate deterministic models, there are several important parameterization decisions for appropriate use and optimal model fit. We explored the role that parameter decisions, including training/testing data splitting strategies, variable selection, and hyperparameters play on RF goodness‐of‐fit by constructing models using 1296 unique parameter combinations to predict concentrations of nitrate, a key nutrient for biogeochemical cycling in aquatic ecosystems. Models were built on long‐term, publicly available water quality and meteorology time series collected by the National Estuarine Research Reserve monitoring network for two contrasting ecosystems representing freshwater and brackish estuaries. We found that accounting for temporal dependence when splitting data into training and testing subsets was key for avoiding over‐estimation of model predictive power. In addition, variable selection, the ratio of training to testing data, and to a lesser degree, variables per split and number of trees, were significant parameters for optimizing RF goodness‐of‐fit. We also explored how model parameter decisions influenced interpretation of the relative importance of predictors to the model, and model predictor‐dependent variable relationships, with results suggesting that both data structure and model parameterization influence these factors. Because much of the current RF literature is written for the computational and statistical science communities, the primary goal of this study is to provide guidelines for aquatic scientists new to machine learning to apply RF techniques appropriately to aquatic biogeochemical datasets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

AT2017gfo: Bayesian inference and model selection of multicomponent kilonovae and constraints on the neutron star equation of state

The joint detection of the gravitational wave GW170817, of the short γ-ray burst GRB170817A and of the kilonova AT2017gfo, generated by the the binary neutron star (NS) merger observed on 2017 August 17, is a milestone in multimessenger astronomy and provides new constraints on the NS equation of state. We perform Bayesian inference and model selection on AT2017gfo using semi-analytical, multicomponents models that also account for non-spherical ejecta. Observational data favour anisotropic geometries to spherically symmetric profiles, with a log-Bayes’ factor of ~104, and favour multicomponent models against single-component ones. The best-fitting model is an anisotropic three-component composed of dynamical ejecta plus neutrino and viscous winds. Using the dynamical ejecta parameters inferred from the best-fitting model and numerical–relativity relations connecting the ejecta properties to the binary properties, we constrain the binary mass ratio to q < 1.54 and the reduced tidal parameter to $120\lt \tilde{\Lambda }\lt 1110$. Finally, we combine the predictions from AT2017gfo with those from GW170817, constraining the radius of a NS of 1.4 M ⊙ to 12.2 ± 0.5 km (1σ level). This prediction could be further strengthened by improving kilonova models with numerical-relativity information.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

Fitting dynamic models to the Geosat sea level observations in the tropical Pacific Ocean. I - A free wave model

Free, equatorially trapped sinusoidal wave solutions to a linear model on an equatorial beta plane are used to fit the Geosat altimetric sea level observations in the tropical Pacific Ocean. The Kalman filter technique is used to estimate the wave amplitude and phase from the data. The estimation is performed at each time step by combining the model forecast with the observation in an optimal fashion utilizing the respective error covariances. The model error covariance is determined such that the performance of the model forecast is optimized. It is found that the dominant observed features can be described qualitatively by basin-scale Kelvin waves and the first meridional-mode Rossby waves. Quantitatively, however, only 23 percent of the signal variance can be accounted for by this simple model.

Fu, Lee-Lueng↗