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

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Structure and evolution of solar radio bursts at 26.4 MHz

Results are reported for multiple-baseline interferometric measurements of type II, III, IV, and V solar radio bursts at 26.4 MHz. Thirty-two burst events in a two-month period are analyzed by fitting a double-Gaussian two-dimensional source-brightness distribution model to the observed interferometer visibility function. The multibaseline time-sharing interferometer system employed is described in detail, the model-fitting technique is outlined, and values of the model-fit parameters are given for all 32 cases, which include two type II bursts, three type IV bursts, 17 type III bursts, seven type V bursts, and three bursts of type III, V pairs. The temporal evolution of source structure, size, and motion is examined for the different burst types. The core-halo source structure for the type III bursts is interpreted in comparison to two models, one of which assumes scattering and refraction of a point source while the other postulates primarily refraction from an ensemble of sources distributed over a wide sector in solar longitude.

Chen, H. S.-L.↗
NASA NTRS1994

Comparison of plate and asthenospheric flow models for the thermal evolution of oceanic lithosphere

Although seafloor depth and heat flow for young oceanic lithosphere can be descibed by modeling the lithosphere as the boundary layer of a cooling halfspace, a long standing question has been why data at older ages deviate from those expected for a halfspace. Two classes of models have been proposed for these deviations. In one, heat added from below 'flattens' depth and heat flow. In the other, asthenospheric flow beneath the lithosphere perturbs the depths. We compare recent versions of the model classes: the GDH1 thin-lithosphere plate model (Stein and Stein, 1992) and an asthenospehric flow model (Phipps Morgan and Smith, 1992). The plate model fits heat flow data better than the flow model for all cases considered, and topographic data in all but one case. The flow model significantly overpredicts depths for the North Atlantic, because the assumed asthenospheric flow in the plate motion direction would yield deepening for old ages rather than the observed flattening. Overall, the GDH1 global average model does better than this flow model, whose parameters were fit to specific plates. Moreover, the plate models fit to specific plates do better than the flow model. Plate models thus appear more useful than this flow model, suggesting that deviations from a cooling halfspace are largely thermal in origin.

Stein, Carol A.↗
DOE OSTI2020

Sampling Low-Dimensional Markovian Dynamics for Preasymptotically Recovering Reduced Models from Data with Operator Inference

This work introduces a method for learning low-dimensional models from data of high-dimensional black-box dynamical systems. The novelty is that the learned models are exactly the reduced models that are traditionally constructed with classical projection-based model reduction techniques. Thus, the proposed approach learns models that are guaranteed to have the well-studied properties of reduced models known from model reduction, without requiring full knowledge of the governing equations and without requiring the operators of the high-dimensional systems. The key ingredient is a new data sampling scheme to obtain re-projected trajectories of high-dimensional systems that correspond to Markovian dynamics in low-dimensional subspaces. The exact recovery of reduced models from these re-projected trajectories is guaranteed pre-asymptotically under certain conditions for finite amounts of data and for a large class of systems with polynomial nonlinear terms. Numerical results demonstrate that the low-dimensional models learned with the proposed approach match reduced models from traditional model reduction up to numerical errors in practice. In conclusion, the numerical results further indicate that low-dimensional models fitted to re-projected trajectories are predictive even in situations where models fitted to trajectories without re-projection are inaccurate and unstable.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Constraint-dependent CTOA determination for stable ductile crack growth

The crack tip opening angle (CTOA) has been used as a reliable fracture toughness to characterize stable crack growth for thin-wall structures in low-constraint conditions. Recently, it is found that CTOA can also be utilized as a robust fracture parameter to describe the arrest fracture toughness for gas transmission pipelines in ductile steels. For better understanding the concept of CTOA, this paper presents a brief review on the CTOA definitions and its test methods. And then, four CTOA models are developed for determining the CTOA toughness using conventional single edge notched bend (SENB) specimens, including the load–displacement linear fit model, the logarithmic load–displacement linear fit model, the stable tearing energy model, and the J-differentiation model. Here fracture test data from SENB specimens in A285 carbon steel are employed to evaluate the proposed CTOA models. The results show that these CTOA models can determine either identical or comparable critical CTOA values for stable ductile crack growth using the SENB specimens. A constraint-corrected CTOA resistance curve and a constraint-corrected critical CTOA equation are also obtained for A285 carbon steel.

42 ENGINEERING↗
DOE OSTI2021

Efficient flexible characterization of quantum processors with nested error models

We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its wildcard error (a metric of the amount of unmodeled error) at each step. Each best-fit model, along with a quantification of its unmodeled error, constitutes a characterization of the processor. We explain how quantum processor models can be compared with experimental data and to each other. We demonstrate the technique by using it to characterize a simulated noisy two-qubit processor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1982

Curve fitting and modeling with splines using statistical variable selection techniques

The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.

Smith, P. L.↗
DOE OSTI2023

Glass formulation and composition optimization with property models: A review

Abstract Glass is a versatile material with a remarkable history and many practical applications. It plays a critical role in our everyday lives, the advancement of science, and the development of many technologies. The Edisonian type trial‐and‐error method was commonly used for conventional design of glass compositions, which was time‐consuming and costly. With the urgent need to develop new glass compositions for technology applications rapidly, it has become necessary to develop precise property models with predictive powers using large databases and efficient formulation approaches. This paper reviews the design of glass compositions using these analytical and numerical models of composition–structure–property relations of glasses, some based on large databases and machine learning approaches. Aspects of data collection, model fitting, feature extraction, model evaluation, and uncertainty quantification will be covered. Furthermore, advances in the glass optimization framework and available tools are summarized with examples. The outlook and perspective for further glass property model development and formulation approaches are discussed.

Lu, Xiaonan↗
DOE OSTI2020

The effect of enrofloxacin on enteric Escherichia coli : Fitting a mathematical model to in vivo data

Antimicrobial drugs administered systemically may cause the emergence and dissemination of antimicrobial resistance among enteric bacteria. To develop logical, research-based recommendations for food animal veterinarians, we must understand how to maximize antimicrobial drug efficacy while minimizing risk of antimicrobial resistance. Our objective is to evaluate the effect of two approved dosing regimens of enrofloxacin (a single high dose or three low doses) on Escherichia coli in cattle. We look specifically at bacteria above and below the epidemiological cutoff (ECOFF), above which the bacteria are likely to have an acquired or mutational resistance to enrofloxacin. We developed a differential equation model for the antimicrobial drug concentrations in plasma and colon, and bacteria populations in the feces. The model was fit to animal data of drug concentrations in the plasma and colon obtained using ultrafiltration probes. Fecal E. coli counts and minimum inhibitory concentrations were measured for the week after receiving the antimicrobial drug. We predict that the antimicrobial susceptibility of the bacteria above the ECOFF pre-treatment strongly affects the composition of the bacteria following treatment. Faster removal of the antimicrobial drugs from the colon throughout the study leads to improved clearance of bacteria above the ECOFF in the low dose regimen. If we assume a fitness cost is associated with bacteria above the ECOFF, the increased fitness costs leads to reduction of bacteria above the ECOFF in the low dose study. These results suggest the initial E. coli susceptibility is a strong indicator of how steers respond to antimicrobial drug treatment.

59 BASIC BIOLOGICAL SCIENCES↗
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↗
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.↗