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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Observations of interstellar helium with a gas absorption cell - Implications for the structure of the local interstellar medium

A photometer sensitive at the 584 A line of He 1, incorporating a helium gas resonance absorption cell, was flown on the Apollo-Soyuz Test Project in July 1975. The instrument observed much of the night-time sky, and returned 42 min of usable data. The data were analyzed by fitting to a model of resonant scattering of solar 584 A flux from nearby interstellar helium. Good model fits were obtained for an interstellar gas bulk velocity vector pointing toward alpha = 72 deg, delta = +15 deg, with speed 20 km/s, with interstellar medium temperatures from 5000 to 20,000 K and with neutral interstellar helium density (8.9 plus or minus 10 to the -3rd/cu cm). In the context of theoretical studies of the interstellar medium by McKee and Ostriker (1977), the results may indicate that the sun lies in the warm, partially ionized periphery of a cold interstellar cloud, surrounded by a high-temperature gas heated by old supernova remnants.

Freeman, J.↗
NASA NTRS1991

Limits on the radius and a possible atmosphere of Charon from its 1980 stellar occultation

Walker's (1980) stellar occultation data for Charon are presently fit by a model which encompasses the possibility of differential refraction by an atmosphere, followed by a sudden occultation behind Charon's limb. The 601.5-km Charon radius lower limit thus obtained may serve as a constraint in models of the mutual event data; while the model fits considered support a Charonian atmosphere of indeterminate composition, time resolution is insufficient for certainty and the data may be interpretable as indications of either a slight extinction near Charon or an entirely unidentified and unassociated effect.

Elliot, J. L.↗
NASA NTRS1994

Producing the universal spectrum of cosmological gamma-ray bursts with the Klein-Nishina cross section

A power-law spectrum attenuated through Compton scattering by an optically thick medium produces spectra that have a characteristic energy of several hundred keV. Add a redshift, and one finds that this model can qualitatively reproduce the color-color diagrams found for individual gamma-ray bursts. This model is easily tested through model fits to burst spectra and through comparisons of the parameters derived from model fits to the limits on parameters derived from the burst log N - log P(sub max) curve. The heavy attenuation makes the amount of energy released in the burst approximately equal to 10(exp 3) times larger than is inferred from the observed flux. The requirements of high optical depth and no photon-photon pair creation place a lower limit on the size of the scattering region. This size suggests that the attenuation occurs in giant molecular clouds in the cores of galaxies. This indicates that gamma-ray bursts are probably from supermassive black holes. If the Lorentz factor of the radiation source is large, the optical depth, and therefore the hardness ratio of a burst, can change over the duration of the burst.

Brainerd, J. J.↗
NASA NTRS2001

A Powerful New Engine

Through Small Business Innovation Research (SBIR) funding from NASA's Glenn Research Center, Moller International created a new coating for rotary engines, which significantly improves the fuel consumption of a vehicle while reducing emissions. The new coatings are offered in the new Rotapower(R) engine, which is produced and distributed by Moller subsidiary, Freedom Motors, Inc. The coating allows the Rotapower engine to function smoother than other models, reducing wear and protecting the engine. The Rotapower engine has the ability to operate on a variety of fuels, including gasoline, natural gas, diesel, alcohol, and kerosene. A small and lightweight engine, it is projected to replace many of today's bulkier versions. The 10 horsepower model fits in the palm of one's hand, while the 160 horsepower model fits into a 5-gallon bucket. The clean running Rotapower engine is environmentally appealing, because it eliminates over 98 percent of the total emissions given off by traditional piston engines. Fewer pollutants are spewed into the air, making it especially attractive in areas where air pollution is a major problem. Due to the clean-burning nature of the engine, it meets the stringent standards set by the California Air Resources Board. The engine also has numerous commercial benefits in several types of recreational, industrial, and transportation applications, including personal watercraft, snowmobiles, portable generators. and pumps.

Source record↗
NASA NTRS2013

Transfer Function Identification Using Orthogonal Fourier Transform Modeling Functions

A method for transfer function identification, including both model structure determination and parameter estimation, was developed and demonstrated. The approach uses orthogonal modeling functions generated from frequency domain data obtained by Fourier transformation of time series data. The method was applied to simulation data to identify continuous-time transfer function models and unsteady aerodynamic models. Model fit error, estimated model parameters, and the associated uncertainties were used to show the effectiveness of the method for identifying accurate transfer function models from noisy data.

Morelli, Eugene A.↗
NASA NTRS2013

Application and Evaluation of a Snowmelt Runoff Model in the Tamor River Basin, Eastern Himalaya Using a Markov Chain Monte Carlo (MCMC) Data Assimilation Approach

Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree-day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash-Sutcliffe metric approx. 0.84, annual volume bias <3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002-2006 period is estimated to be 29.7+/-2.9% (which includes 4.2+/-0.9% from snowfall that promptly melts), whereas 70.3+/-2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000-5500m range contributes the most to basin runoff, averaging 56.9+/-3.6% of all snowmelt input and 28.9+/-1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree-day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds.

runoff↗
NASA NTRS2015

Understanding the Atmosphere of 51 Eri b: Do Photochemical Hazes Cloud the Planets Spectrum?

The first young giant planet to be discovered by the Gemini Planet Imager was the (is) approximately 2MJ planet 51 Eri b. This approximately 20 Myr old young Jupiter is the first directly imaged planet to show unmistakable methane in H band. To constrain the planet's mass, atmospheric temperature, and composition, the GPI J and H band spectra as well as some limited photometric points were compared to the predictions of substellar atmosphere models. The best fitting models reported in the discovery paper (Macintosh et al. 2015) relied upon a combination of clear and cloudy atmospheric columns to reproduce the data. However for an object as cool as 700 K, the origin of the cloud coverage is somewhat puzzling, as the global silicate and iron clouds would be expected to have sunk well below the photosphere by this effective temperature. While strong vertical mixing in these low gravity atmospheres remains a plausible explanation, we have explored whether atmospheric photochemistry, driven by the UV flux from the primary star, may yield hazes that also influence the observed spectrum of the planet. To explore this possibility we have modeled the atmospheric photochemistry of 51 Eri b using two state-of-the-art photochemical models, both capable of predicting yields of complex hydrocarbons under various atmospheric conditions. In our presentation we will summarize the modeling approach employed to characterize 51 Eri b, explaining constraints on the planet's effective temperature, gravity, and atmospheric composition and also present results of our studies of atmospheric photochemistry. We will discuss whether photochemical hazes could indeed be responsible for the particulate opacity that apparently sculpts the spectrum of the planet.

GPI - Gemini Planet Imager↗
DOE OSTI2020

Linear point and sound horizon as purely geometric standard rulers

The baryon acoustic oscillations feature (BAO) imprinted in the clustering correlation function is known to furnish us cosmic distance determinations that are independent of the cosmological-background model and the primordial perturbation parameters. These measurements can be accomplished rigorously by means of the purely geometric BAO methods. To date two different purely geometric BAO approaches have been proposed. The first exploits the linear-point standard ruler. The second, called correlation-function model-fitting, exploits the sound-horizon standard ruler. A key difference between them is that, when estimated from clustering data, the linear point makes use of a cosmological-model-independent procedure to extract the ratio of the ruler to the cosmic distance, while the correlation-function model-fitting relies on a phenomenological cosmological model for the correlation function. Nevertheless the two rulers need to be precisely defined independently of any specific observable (e.g., the BAO). We define the linear point and sound horizon and we fully characterize and compare the two rulers’ cosmological-parameter dependence. We find that they are both geometrical (i.e., independent of the primordial cosmological parameters) within the required accuracy, and that they have the same parameter dependence for a wide range of parameter values. We estimate the rulers’ best-fit values and errors, given the cosmological constraints obtained by the Planck Satellite team from their measurements of the cosmic microwave background temperature and polarization anisotropies. We do this for three different cosmological models encompassed by the purely geometric BAO methods. In each case we find that the relative errors of the two rulers coincide and they are insensitive to the assumed cosmological model. Interestingly both the linear point and the sound horizon shift by 0.5σ when we do not fix the spatial geometry to be flat in Λ CDM. Finally, this points toward a sensitivity of the rulers to different cosmological models when they are estimated from the cosmic microwave background.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The inside-out growth of the most massive galaxies at 0.3 < z < 0.9

We study the surface brightness profiles of a sample of brightest cluster galaxies (BCGs) with 0.3 < z < 0.9. The BCGs are selected from the first Red-sequence Cluster Survey and an X-ray cluster survey. The surface brightness profiles of the BCGs are measured using HST ACS images, and the majority of them can be well modeled by a single Sérsic profile with a typical Sérsic index n ∼ 6 and a half-light radius ∼30 kpc. Although the single Sérsic model fits the profiles well, we argue that the systematics in the sky background measurement and the coupling between the model parameters make the comparison of the best-fit model parameters ambiguous. Direct comparison of the BCG profiles, on the other hand, has revealed an inside-out growth for these most massive galaxies: as the mass of a BCG increases, the central mass density of the galaxy increases slowly (ρ{sub 1kpc}∝M{sub ∗}{sup 0.39}), while the slope of the outer profile grows continuously shallower (α{sub r{sup 1}{sup /}{sup 4}}∝M{sub ∗}{sup −2.5}). Such a fashion of growth continues down to the less massive early-type galaxies (ETGs) as a smooth function of galaxy mass, without apparent distinction between BCGs and non-BCGs. For the very massive ETGs and BCGs, the slope of the Kormendy relation starts to trace the slope of the surface brightness profiles and becomes insensitive to subtle profile evolution. These results are generally consistent with dry mergers being the major driver of the mass growth for BCGs and massive ETGs. We also find strong correlations between the richness of clusters and the properties of BCGs: the more massive the clusters are, the more massive the BCGs (M{sub bcg}{sup ∗}∝M{sub clusters}{sup 0.6}) and the shallower their surface brightness profiles. After taking into account the bias in the cluster samples, we find the masses of the BCGs have grown by at least a factor of 1.5 from z = 0.5 to z = 0, in contrast to the previous findings of no evolution. Such an evolution validates the expectation from the ΛCDM model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

A no-scale inflationary model to fit them all

The magnitude of B-mode polarization in the cosmic microwave background as measured by BICEP2 favours models of chaotic inflation with a quadratic m{sup 2} φ{sup 2}/2 potential, whereas data from the Planck satellite favour a small value of the tensor-to-scalar perturbation ratio r that is highly consistent with the Starobinsky R +R{sup 2} model. Reality may lie somewhere between these two scenarios. In this paper we propose a minimal two-field no-scale supergravity model that interpolates between quadratic and Starobinsky-like inflation as limiting cases, while retaining the successful prediction n{sub s} ≅ 0.96.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1999

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Non-NASA Center↗
NASA NTRS1993

M dwarf spectra from 0.6 to 1.5 micron - A spectral sequence, model atmosphere fitting, and the temperature scale

Red/infrared (0.6-1.5 micron) spectra are presented for a sequence of well-studied M dwarfs ranging from M2 through M9. A variety of temperature-sensitive features useful for spectral classification are identified. Using these features, the spectral data are compared to recent theoretical models, from which a temperature scale is assigned. The red portion of the model spectra provide reasonably good fits for dwarfs earlier than M6. For layer types, the infrared region provides a more reliable fit to the observations. In each case, the wavelength region used includes the broad peak of the energy distribution. For a given spectral type, the derived temperature sequence assigns higher temperatures than have earlier studies - the difference becoming more pronounced at lower luminosities. The positions of M dwarfs on the H-R diagram are, as a result, in closer agreement with theoretical tracks of the lower main sequence.

Kirkpatrick, J. D.↗
DOE OSTI2025

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1995

Dust in the Small Magellanic Cloud

We discuss simultaneous dust model fits to our extinction and polarization data for the Small Magellanic Cloud (SMC) using existing dust models. Dust model fits to the wavelength dependent polarization are possible for stars with small lambda(sub max). They generally imply size distributions which are narrower and have smaller average sizes compared to those in the Galaxy. The best fits for the extinction curves are obtained with a power law size distribution. The typical, monotonic SMC extinction curve can be well fit with graphite and silicate grains if a small fraction of the SMC carbon is locked up in the grains. Amorphous carbon and silicate grains also fit the data well.

Rodrigues, C. V.↗
DOE OSTI2016

glmnetLRC f/k/a lrc package: Logistic Regression Classification

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.

Source record↗
DOE OSTI2016

glmnetLRC f/k/a lrc package: Logistic Regression Classification

Methods for fitting and predicting logistic regression classifiers (LRC) with an arbitrary loss function using elastic net or best subsets. This package adds additional model fitting features to the existing glmnet and bestglm R packages. This package was created to perform the analyses described in Amidan BG, Orton DJ, LaMarche BL, et al. 2014. Signatures for Mass Spectrometry Data Quality. Journal of Proteome Research. 13(4), 2215-2222. It makes the model fitting available in the glmnet and bestglm packages more general by identifying optimal model parameters via cross validation with an customizable loss function. It also identifies the optimal threshold for binary classification.

Source record↗
DOE OSTI2015

Dynamics of neutrals and ions in an ultrafast laser produced Zn plasma

Optical time of flight dynamics of neutrals and ions in an ultrafast laser produced zinc plasma generated by irradiating a solid zinc target using 100 fs laser pulses is investigated. An acceleration of ions is observed which arises from internal Coulomb forces acting between charged species in the plasma. Some of the fast ions recombine with electrons in the plasma and generate fast neutrals. Plasma plume imaging performed at various ambient pressures indicates adiabatic expansion at lower pressures and plume front deceleration at higher pressures: at lower pressures the plume front-time (R-t) plot displays a linear expansion, shock wave model fits to the data at 5 Torr and at higher pressures the data fits better to the drag model. Furthermore, around an intermediate pressure of 10 Torr, the R-t plot fits to the shock wave model at earlier stages of plasma expansion, while it fits to the drag model at the later stages. These investigations provide relevant information on the acceleration of ions and neutrals in an expanding zinc plasma plume produced by ultrafast laser pulses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗