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Results for “parameter correlations”

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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

The application of neural networks to the SSME startup transient

Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine startup transient. The three parameters were the main combustion chamber pressure, a controlled parameter, the high pressure oxidizer turbine discharge temperature, a redlined parameter, and the high pressure fuel pump discharge pressure, a failure-indicating performance parameter. Network inputs consisted of time windows of data from engine measurements that correlated highly to the modeled parameter. A standard backpropagation algorithm was used to train the feedforward networks on two nominal firings. Each trained network was validated with four additional nominal firings. For all three parameters, the neural networks were able to accurately predict the data in the validation sets as well as the training set.

Meyer, Claudia M.↗
DOE OSTI2020

Machine learning Frenkel Hamiltonian parameters to accelerate simulations of exciton dynamics

In this manuscript, we develop multiple machine learning (ML) models to accelerate a scheme for parameterizing site-based models of exciton dynamics from all-atom configurations of condensed phase sexithiophene systems. This scheme encodes the details of a system’s specific molecular morphology in the correlated distributions of model parameters through the analysis of many single-molecule excited-state electronic-structure calculations. These calculations yield excitation energies for each molecule in the system and the network of pair-wise intermolecular electronic couplings. In this work, we demonstrate that the excitation energies can be accurately predicted using a kernel ridge regression (KRR) model with Coulomb matrix featurization. We present two ML models for predicting intermolecular couplings. The first one utilizes a deep neural network and bi-molecular featurization to predict the coupling directly, which we find to perform poorly. The second one utilizes a KRR model to predict unimolecular transition densities, which can subsequently be analyzed to compute the coupling. We find that the latter approach performs excellently, indicating that an effective, generalizable strategy for predicting simple bimolecular properties is through the indirect application of ML to predict higher-order unimolecular properties. Such an approach necessitates a much smaller feature space and can incorporate the insight of well-established molecular physics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1973

A new correlation among high-velocity clouds in the galaxy

Search for correlations among the various parameters associated with the hydrogen gas in high-velocity clouds in the galaxy. The results obtained indicate that there may be some general trends, but in most cases it is difficult to assess the significance of the correlation because of the large amount of scatter. In one case, however, there appears to be a significant relationship that leads to an estimate of the distance to the high-velocity gas of about 600 pc.

Silk, J.↗
NASA NTRS2010

Saturation of the Electric Field Transmitted to the Magnetosphere

We reexamined the processes leading to saturation of the electric field, transmitted into the Earth's ionosphere from the solar wind, incorporating features of the coupled system previously ignored. We took into account that the electric field is transmitted into the ionosphere through a region of open field lines, and that the ionospheric conductivity in the polar cap and auroral zone may be different. Penetration of the electric field into the magnetosphere is linked with the generation of the Alfven wave, going out from the ionosphere into the solar wind and being coupled with the field-aligned currents at the boundary of the open field limes. The electric field of the outgoing Alfven wave reduces the original electric field and provides the saturation effect in the electric field and currents during strong geomagnetic disturbances, associated with increasing ionospheric conductivity. The electric field and field-aligned currents of this Alfven wave are dependent on the ionospheric and solar wind parameters and may significantly affect the electric field and field-aligned currents, generated in the polar ionosphere. Estimating the magnitude of the saturation effect in the electric field and field-aligned currents allows us to improve the correlation between solar wind parameters and resulting disturbances in the Earth's magnetosphere.

Lyatsky, Wladislaw↗
DOE OSTI2018

On estimating the curvature attributes and strain invariants of deformed surface through radial basis functions

Numerical methods in approximation of derivatives on regular or irregular gridded and scattered data points are of significance in the study of numerous problems in engineering and geoscience. A mathematically accurate and stable method is assessed to compute the differential quantities, while being flexible and easy to implement. Strain-invariant parameters in deformation analysis and curvature attributes in geometrical analysis of approximated surfaces are independent quantities which could be derived numerically through radial basis functions (RBFs) for scattered data points. Approximation of a function or its derivatives through RBFs is highly correlated to its shape parameter which depends on the number and distribution of the particles on the support domain. A procedure to find the optimal shape parameter for RBFs in the influence domain of each nodal point together with the presentation of a manner of calculating the curvature attributes and strain parameters through Gaussian RBFs is proposed here. Results indicate a significant improvement in the approximation accuracy of strain parameters and curvature attributes, while this approximation is more stable when RBFs with optimal shape parameter are implemented rather than the traditional moving least squares.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

Correlation of bow shock plasma wave turbulence with solar wind parameters

The rms field strengths of electrostatic and electromagnetic turbulence in the earth's bow shock, measured in the frequency range 20 Hz to 200 kHz with the Imp 6 satellite, are examined. The largest strengths of electrostatic turbulence occur when the upstream electron-to-proton temperature ratio is large and the proton temperature is small. No substantial correlation is found among the rms field strengths of electrostatic turbulence, the Alfven Mach number, the ratio of particle to magnetic-field pressure, and the shock normal angle. These results indicate that the strength of electrostatic turbulence in the bow shock is determined by the kinetic properties of the solar-wind plasma. The largest strengths for electromagnetic turbulence occur when the upstream particle density is large and when the shock normal angle is closer to 90 deg, supporting a previous conclusion that whistler waves comprise the electromagnetic turbulence in the bow shock.

Rodriguez, P.↗
DOE OSTI2018

Predicting Future Soiling Losses Using Environmental Data: Preprint

Soiling consists of the accumulation of dust and dirt on the surfaces of photovoltaic (PV) modules and causes a reduction in the energy conversion. Investors generally consider an average yearly soiling loss to estimate the energy yield and the economic revenue of a site for a new PV installation. If soiling could be estimated from wide available parameters, describing the pollution and the rainfall pattern at a site, more accurate losses could be predicted, reducing the uncertainty in the estimation of the energy yield and therefore the finance rates offered for new PV systems. The present work investigates the correlations between present environmental parameters and future soiling losses.

14 SOLAR ENERGY↗
NASA NTRS1996

Nonlinear Dynamics and Nucleation Kinetics in Near-Critical Liquids

The objective of our study is to model the nonlinear behavior of a near-critical liquid following a rapid change of the temperature and/or other thermodynamic parameters (pressure, external electric or gravitational field). The thermodynamic critical point is manifested by large, strongly correlated fluctuations of the order parameter (particle density in liquid-gas systems, concentration in binary solutions) in the critical range of scales. The largest critical length scale is the correlation radius r(sub c). According to the scaling theory, r(sub c) increases as r(sub c) = r(sub 0)epsilon(exp -alpha) when the nondimensional distance epsilon = (T - T(sub c))/T(sub c) to the critical point decreases. The normal gravity alters the nature of correlated long-range fluctuations when one reaches epsilon approximately equal to 10(exp -5), and correspondingly the relaxation time, tau(r(sub c)), is approximately equal to 10(exp -3) seconds; this time is short when compared to the typical experimental time. Close to the critical point, a rapid, relatively small temperature change may perturb the thermodynamic equilibrium on many scales. The critical fluctuations have a hierarchical structure, and the relaxation involves many length and time scales. Above the critical point, in the one-phase region, we consider the relaxation of the liquid following a sudden temperature change that simultaneously violates the equilibrium on many scales. Below T(sub c), a non-equilibrium state may include a distribution of small scale phase droplets; we consider the relaxation of such a droplet following a temperature change that has made the phase of the matrix stable.

Patashinski, Alexander Z.↗
DOE OSTI2024

Second harmonic generation for estimating state of charge of lithium-ion batteries

This study applied the nonlinear ultrasonic method, second harmonic generation, to precisely estimate the state of charge (SoC) in lithium-ion batteries. The second harmonic of the longitudinal wave is generated on a pouch cell battery at 5 MHz with a through-transmission setup. The relative nonlinear parameter β' is determined by analyzing the amplitudes at the fundamental and second harmonic frequencies. To enhance the nonlinear parameter's measurement accuracy, multiple excitation amplitudes are employed. Two separate charge/discharge tests (four-cycle and eight-cycle) are conducted on the battery at a rate of C/10. The nonlinear parameter is measured periodically during the charge/discharge process, and temperature compensation is applied to the measurement. The correlation curves between the nonlinear parameter and the actual SoC align well for the four-cycle and eight-cycle tests, and a robust linear relationship is observed for both correlation curves. A linear model and a second-order polynomial model are applied to fit the correlation using all data points from both tests. The two models are employed to validate the SoC prediction on a second battery by using a four-cycle test. Furthermore, the results indicate that both models can predict the SoC with an accuracy of approximately 3%, whereas the polynomial model demonstrates smaller errors in the regions near 0% and 100% SoC. Therefore, the nonlinear parameter β', measured through the second harmonic generation, can effectively predict lithium-ion battery SoC with an accuracy of less than 3%.

25 ENERGY STORAGE↗
DOE OSTI2016

Transparent flexible nanogenerator as self-powered sensor for transportation monitoring

A traffic sensor includes a flexible substrate having a top surface. A piezoelectric structure extends from the first electrode layer. The piezoelectric structure has a top end. An insulating layer is infused into the piezoelectric structure. A first electrode layer is disposed on top of the insulating layer. A second electrode layer is disposed below the flexible substrate. A packaging layer is disposed around the substrate, the first electrode layer, the piezoelectric structure, the insulating layer and the second electrode layer. In a method of sensing a traffic parameter, a piezoelectric nanostructure-based traffic sensor is applied to a roadway. An electrical event generated by the piezoelectric nanostructure-based traffic sensor in response to a vehicle interacting with the piezoelectric nanostructure-based traffic sensor is detected. The electrical event is correlated with the traffic parameter.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Prediction of countercurrent flow limitation and its uncertainty in a PWR hot leg

In previous studies, we did small-scale air-water experiments for the hot leg and pressurizer surge line in a PWR and three-dimensional (3D) numerical simulations for PWR conditions to evaluate countercurrent flow limitation (CCFL) there, and we developed a one-dimensional (1D) prediction method to generalize prediction of CCFL in a piping system such as the hot leg and pressurizer surge line. In this study, we evaluated computation errors of the 1D prediction method in comparison with CCFL data in the PWR hot leg models with the diameter D and length L of D = 50-650 mm and L/D = 4.5-9.5, and then evaluated uncertainties of the 1D prediction method in comparison with 3D numerical simulations for PWR conditions with D = 750 mm and L/D = 8.6. We found the computation errors were within the difference of dC = ±0.05 for the CCFL constant of C = 0.63 in the correlation with the Wallis parameters, but the computation errors include experimental errors and they are not uncertainties for the PWR conditions. The total uncertainty of the 1D computations for the actual PWR hot leg (including effects of the diameter and fluid properties) was estimated to be dC = ±0.035. The CCFL correlation and its uncertainty of dC = ±0.035 derived from the 1D prediction method were very close to those previously obtained from CCFL data and 3D simulations (dC = ±0.03). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1991

Solar control of the earth's emission of energetic O(+)

Energetic (0.1-16 keV/e) O(+) data obtained in the earth's plasma sheet (between 10 and 23 RE) by an ion mass spectrometer on the ISEE-1 spacecraft are compared statistically with published data on the concurrent solar wind and IMF. The most strongly variable parameter of the plasma sheet O(+) is its density, which is found to be well correlated with certain solar wind parameters, especially with the solar wind flow speed and the IMF component perpendicular to the flow vector. When those two solar wind parameters are combined to form an electric field (-v x B), both the number density and the energy density of the O(+) are found to vary in proportion to the square of that electric field, on average, suggesting that the emission of energetic O(+) ions from the earth may be powered by that same field. Based on this and on the previously published correlation with solar activity, it is argued that the emission of O(+) is controlled by a combination of HF (ionizing) and quasi-static (accelerating) solar electromagnetic fields.

Lennartsson, W.↗
NASA NTRS2024

Azimuthal Size Scales of Solar Wind Periodic Density Structures

Periodic Density Structures (PDSs) are quasi-periodic variations of solar wind density ranging from a few minutes to a few hours. PDSs advect with the solar wind and have radial length scales (Lx) of tens to several thousand Mm, thus belonging to the class of “mesoscale structures”. Current interplanetary multi-spacecraft observations are not at spatial separations capable of directly measuring the 3D size scale of PDSs or other mesoscale structures. Instead, previous investigations estimated characteristic spatial scales in solar wind parameters using cross-correlation and/or coherence analysis applied to multi-spacecraft observations. For solar wind density and interplanetary magnetic field (IMF) intensity, the reported size scales perpendicular to the Sun-Earth line (Ly) ranged between ≈30 and ≈200 Earth Radii (RE). Here, we implemented a similar approach on the same parameters but focused on high density slow solar wind intervals with PDSs observed by the Wind and ARTEMIS-P1 spacecraft. Additionally, this is the first statistical study of the IMF intensity periodicities in relation to PDSs. We identified intervals in which the two spacecraft observed the same periodicity obtaining two PDS groups based on their radial length scale: Lx1 ≈86RE and Lx2 ≈35RE. Then, we classified the events based on the periodic variations’ coherence level. Reproducing the results with simulations of the PDSs’ transit, we inferred the Ly order of magnitudes for the two PDS groups: Ly1 ≈340RE and Ly2 ≈187RE. Knowing the PDSs’ size scales is fundamental to constrain models aimed at reproducing these structures and is critical to better understand the PDS-magnetosphere coupling.

Interplanetary physics↗
DOE OSTI2024

Surface-mediated spontaneous emulsification of the acylated peptide, semaglutide

Acylated peptides composed of glucagon-like peptide-1 receptor agonists modified with a fatty acid side chain are an important class of therapeutics for type 2 diabetes and obesity but are susceptible to an unusual physical instability in the presence of hydrophobic surfaces, i.e., spontaneous emulsification, also known as ouzo formation in practice. In this work, light scattering, small-angle X-ray scattering, and circular dichroism measurements are used to characterize the physical properties of the semaglutide colloidal phase, including size distribution, shape, secondary structure, internal structure, and internal composition, as a function of solution physico-chemical conditions. The existence and size of the colloids formed are successfully predicted by a classical Rayleigh model, which identifies the parameters controlling their size and formation. Colloid formation is found to be catalyzed by hydrophobic surfaces, and formation rates are modeled as an autocatalytic reaction, enabling the formation of a master curve for various surfaces that elucidates the mechanism. Surfaces differ due to differences in surface wettability, which can be correlated with Hansen solubility parameters. This work provides insights into this unusual colloidal phenomenon and guides the peptide synthesis process and drug product formulation in the pharmaceutical industry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

3D correlations in the Lyman-α forest from early DESI data

We present the first measurements of Lyman-α (Lyα) forest correlations using early data from the Dark Energy Spectroscopic Instrument (DESI). We measure the auto-correlation of Lyα absorption using 88 509 quasars at z > 2, and its cross-correlation with quasars using a further 147 899 tracer quasars at z ≳ 1.77. Then, we fit these correlations using a 13-parameter model based on linear perturbation theory and find that it provides a good description of the data across a broad range of scales. We detect the BAO peak with a signal-to-noise ratio of 3.8σ, and show that our measurements of the auto- and cross-correlations are fully-consistent with previous measurements by the Extended Baryon Oscillation Spectroscopic Survey (eBOSS). Even though we only use here a small fraction of the final DESI dataset, our uncertainties are only a factor of 1.7 larger than those from the final eBOSS measurement. As a result, we validate the existing analysis methods of Lyα correlations in preparation for making a robust measurement of the BAO scale with the first year of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Thermal response to ozone fluctuations of the stratosphere

Correlations between stratospheric meteorological parameters and ozone amount are examined in terms of radiation absorption by ozone. Fluctuations of ozone concentration at subtropic latitudes in summer are analyzed on the assumption that local temperature is governed entirely by radiative equilibrium. The analysis suggests that the fluctuations of mean monthly temperature and ozone are not only correlated, but also follow the order-of-magnitude values expected if ozone heating dominates the temperatures. Most direct control of ozone on temperature exists in the lowest parts of the stratosphere.

Stanulonis, S. F.↗
DOE OSTI2023

Assessing pore network heterogeneity across multiple scales to inform CO2 injection models

Geologic heterogeneity is a key feature that must be considered when translations of scaled data are performed. This paper presents the assessment of geologic heterogeneity using a multiscale workflow that includes image analysis-based methods coupled with well log analysis to provide data in which fractals and machine learning methods estimate the carbon dioxide (CO 2 ) storage resource potential of a reservoir. The heterogeneity of rock properties of the complex Bell Creek reservoir in Montana, USA, was explored at the pore scale (~nm to mm), core scale (~mm to m), and well scale (~cm to m). The data used in this study included advanced image analysis of micro-CT (computed tomography) images (pore scale), thin sections (pore scale), plugs and core images (core scale) and well logs (well scale). The micro-CT images were segmented using a U-net segmentation approach into objects of pores and grains. Further, the segmented images were reconstructed into subvolumes of different sizes. Physical properties (porosity and permeability) and fractal dimensions were calculated for the various subvolumes, and Lorenz coefficient (Lc) values, a single parameter to describe the degree of heterogeneity within a pay zone section, were calculated from thin-section images and well logs. Porosity and fractal dimension values were used to estimate the 188-µm threshold of representative elementary volume (REV) in this study. Both the Lc and fractal dimension values were found to be negatively correlated. When these two parameters are combined, it is possible to discern differences in the complex porous networks of the samples analyzed in this study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗