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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 307 records · Page 17

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NASA NTRS1981

Models of the earth's core

Combined inferences from seismology, high-pressure experiment and theory, geomagnetism, fluid dynamics, and current views of terrestrial planetary evolution lead to models of the earth's core with five basic properties. These are that core formation was contemporaneous with earth accretion; the core is not in chemical equilibrium with the mantle; the outer core is a fluid iron alloy containing significant quantities of lighter elements and is probably almost adiabatic and compositionally uniform; the more iron-rich inner solid core is a consequence of partial freezing of the outer core, and the energy release from this process sustains the earth's magnetic field; and the thermodynamic properties of the core are well constrained by the application of liquid-state theory to seismic and labroatory data.

Stevenson, D. J.↗

NASA NTRS1987

Voyager 2 at Uranus - A synopsis of atmospheric science results

Knowledge of the Uranian atmosphere took a quantum leap when the Voyager 2 spacecraft made a close approach in January 1986. Among the highlights of the early results are measurements of the atmospheric composition (He mole fraction = 0.15; Ch4 mole fraction = 0.02), rotation period of the deep interior (17.24 h), thermal structure and dynamics (the planet is coldest at midlatitudes; retrograde equatorial winds are inferred), and upper-atmosphere processes (a phenomenon called electroglow is only partly understood and is recognized as an important process n all the major-planet atmospheres examined by Voyager).

West, Robert A.↗

NASA NTRS1991

Analysis and modeling of summertime convective cloud and precipitation structure over the Southeastern United States

A summary of an investigation of deep convective cloud systems that typify the summertime subtropical environment of northern Alabama is presented. The major portion of the research effort included analysis of data acquired during the 1986 Cooperative Huntsville Meteorological Experiment (COHMEX), which consisted of the joint programs Satellite Precipitation and Cloud Experiment (SPACE) under NASA direction, the Microburst and Service Thunderstorm (MIST) Program under NSF sponsorship, and the FAA-Lincoln Laboratory Weather Study (FLOWS). This work relates closely to the SPACE component of COHMEX, one of the general goals of which was to further the understanding of kinematic and precipitation structure of convective cloud systems. The special observational plateforms that were available under the SPACE/COHMEX Program are shown. The original objectives included studies of both isolated deep convection and of (small) mesoscale convection systems that are observed in the Southeast environment. In addition, it was proposed to include both observational and comparative numerical modeling studies of these characteristic cloud systems. Changes in scope were made during the course of this investigation to better accommodate both the manpower available and the data that was acquired. A greater emphasis was placed on determination of the internal structure of small mesoscale convective systems, and the relationship of internal dynamical and microphysical processes to the observed cloud top behavior as inferred from GOES IR (30 min) data. The major accomplishments of this investigation are presented.

Knupp, Kevin R.↗

NASA NTRS1990

Gravitational lensing limits on the cosmological constant in a flat universe

Inflationary cosmological theories predict, and some more general aesthetic criteria suggest, that the large-scale spatial curvature of the universe k should be accurately zero (i.e., flat), a condition which is satisfied when the universe's present mean density and the value of the cosmological constant Lambda have certain pairs of values. Available data on the frequency of multiple image-lensing of high-redshift quasars by galaxies suggest that the cosmological constant cannot make a dominant contribution to producing a flat universe. In particular, if the mean density of the universe is as small as the baryon density inferred from standard cosmic nucleosynthesis calculations or as determined from typical dynamical studies of galaxies and galaxy clusters, then a value of Lambda large enough to produce a k = 0 universe would result in a substantially higher frequency of multiple-image lensing of quasars than has been observed so far. Shortcomings of the available lens data and uncertainties concerning galaxy properties allow some possibility of escaping this conclusion, but systematic searches for a gravitational lenses and continuing investigations of galaxy mass distributions should soon provide decisive information. It is also noted that nonzero-curvature cosmological models can account for the observed frequency of galaxy-quasar lens systems and for a variety of other constraints.

Turner, Edwin L.↗

NASA NTRS1991

Large-scale solar and heliospheric magnetic fields

The magnetic structure of the extended solar corona varies with the changing photospheric field during the solar cycle. A simple potential model of the corona using solar surface observations from 1976 to the present shows how the large-scale coronal field evolves over more than a solar activity cycle. These predictions match well with large stable structures inferred from measurements of coronal electron density and the IMF, though dynamic changes are poorly modeled. The sun's polar field was about 25 stronger at solar minimum in 1986 than in 1976; the heliospheric current sheet was also flatter. In Cycle 21 the coronal and photospheric large-scale long-lived field patterns rotated every 26.9 days in the northern hemisphere; the southern field rotated every 28 days. Similar periods have been present in the IMF and in the occurrence of solar flares during the last several solar cycles.

Hoeksema, J. Todd↗

NASA NTRS1994

Three-dimensional evolution of water vapor distributions in the Northern Hemisphere stratosphere as observed by the MLS

The three-dimensional evolution of stratospheric water vapor distributions observed by the Microwave Limb Sounder (MLS) during the period October 1991 - July 1992 is documented. The transport features inferred from the MLS water vapor distributions are corroborated using other dynamical fields, namely, nitrous oxide from the Cryogenic Limb Array Etalon Spectrometer instrument, analyzed winds from the U.K. Meteorological Office (UKMO), UKMO-derived potential vorticity, and the diabatic heating field. By taking a vortex-centered view and an along-track view, the authors observe in great detail the vertical and horizontal structure of the northern winter stratosphere. It is demonstrated that the water vapor distributions show clear signatures of the effects of diabatic descent through isentropic surfaces and quasi-horizontal transport along isentropic surfaces, and that the large-scale winter flow is organized by the interaction between the westerly polar vortex and the Aleutian high.

Lahoz, W. A.↗

NASA NTRS2005

Image of Fomalhaut Dust Ring at 350 Microns: The Relative Column Density Map Shows Pericenter-Apocenter Asymmetry

We have imaged the circumstellar disk of Fomalhaut at 350 mm wavelength, using SHARC II (Submillimeter High Angular Resolution Camera II) at the Caltech Submillimeter Observatory. The spatial resolution of the raw images (9") has been enhanced by a factor of 3 using the HiRes deconvolution procedure. We find that at this wavelength and signal-to-noise ratio (approx.12), the observed morphology is that of a simple inclined ring (i approx. 70 deg), with little or no other apparent structure--this is the first observation that shows clearly the ring morphology of the disk. We have combined our 350 mm data with Spitzer Space Telescope images at 24, 70, and 160 mm in order to estimate the two-dimensional spatial variation of relative column density ("tau map") using our DISKFIT procedure. The tau map is based on the following physical assumptions: (1) the wavelength variation of opacity is the same throughout the disk, (2) the radial variation of dust temperature is dictated by the energy balance of individual grains in the stellar radiation field, and (3) the vertical scale height of the disk follows a power-law radial variation. The results confirm the ringlike morphology but also show that the geometric center is displaced from the star by about 8 AU and that the ring has an apocentric enhancement of approximately 14% in integrated column density. If we interpret the displacement in terms of elliptical orbital motion due to gravitational perturbation by an unseen planet, then the implied forced eccentricity is ~0.06; dynamical modeling then predicts an apocentric density enhancement consistent with that inferred from the tau map.

Fomalhaut↗

DOE OSTI2021

Machine-learning-based inversion of nuclear responses

A microscopic description of the interaction of atomic nuclei with external electroweak probes is required for elucidating aspects of short-range nuclear dynamics and for the correct interpretation of neutrino oscillation experiments. Nuclear quantum Monte Carlo methods infer the nuclear electroweak response functions from their Laplace transforms. Inverting the Laplace transform is a notoriously ill-posed problem; and Bayesian techniques, such as maximum entropy, are typically used to reconstruct the original response functions in the quasielastic region. In this work, we present a physics-informed artificial neural network architecture suitable for approximating the inverse of the Laplace transform. Utilizing simulated, albeit realistic, electromagnetic response functions, we show that this physics-informed artificial neural network outperforms maximum entropy in both the low-energy transfer and the quasielastic regions, thereby allowing for robust calculations of electron scattering and neutrino scattering on nuclei and inclusive muon capture rates.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Non-intrusive reduced-order modeling for dynamical systems with spatially localized features

This work presents a non-intrusive reduced-order modeling framework for dynamical systems with spatially localized features characterized by slow singular value decay. The proposed approach builds upon two existing methodologies for reduced and full-order non-intrusive modeling, namely Operator Inference (OpInf) and sparse Full-Order Model (sFOM) inference. We decompose the domain into two complementary subdomains that exhibit fast and slow singular value decay. The dynamics of the subdomain exhibiting slow singular value decay are learned with sFOM while the dynamics with intrinsically low dimensionality on the complementary subdomain are learned with OpInf. The resulting, coupled OpInf-sFOM formulation leverages the computational efficiency of OpInf and the high resolution of sFOM, and thus enables fast non-intrusive predictions for conditions beyond those sampled in the training data set. A novel regularization technique with a closed-form solution based on the Gershgorin disk theorem is introduced to promote stable sFOM and OpInf models. We also provide a data-driven indicator for subdomain selection and ensure solution smoothness over the interface via a post-processing interpolation step. We evaluate the efficiency of the approach in terms of offline and online speedup through a quantitative, parametric computational cost analysis. We demonstrate the coupled OpInf-sFOM formulation for two test cases: a one-dimensional Burgers’ model for which accurate predictions beyond the span of the training snapshots are presented, and a two-dimensional parametric model for the Pine Island Glacier ice thickness dynamics, for which the OpInf-sFOM model achieves an average prediction error on the order of 1% with an online speedup factor of approximately 8$\times$ compared to the numerical simulation.

42 ENGINEERING↗

DOE OSTI2020

Kinetic modeling of microbial growth, enzyme activity, and gene deletions: An integrated model of β-glucosidase function in Cellvibrio japonicus

Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene-deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium Cellvibrio japonicus grown using either cellobiose or glucose media. The model parameters were inferred from an experimental data set using an evolutionary computation method. The resulting model was able to explain the growth dynamics of C. japonicus using either cellobiose or glucose media and was also able to accurately predict the metabolite concentrations in the wild-type strain as well as in β-glucosidase gene deletion mutant strains. We validated the model by correctly predicting the non-diauxic growth and metabolite consumptions of the wild-type strain in a mixed medium containing both cellobiose and glucose, made further predictions of mutant strains growth phenotypes when using cellobiose and glucose media, and demonstrated the utility of the model for designing industrially-useful strains. Importantly, the model is able to explain the role of the different β-glucosidases and their behavior under genetic perturbations. Here, this integrated approach can be extended to other metabolic pathways to produce mechanistic models for the comprehensive understanding of enzymatic functions in multiple substrates.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Deep-Learning-Based Koopman Modeling for Online Control Synthesis of Nonlinear Power System Transient Dynamics

Power system stability and control have become more challenging due to the increasing uncertainty associated with renewable generation. Here, the performance of conventional control is highly driven by the physics-based offline-developed dynamic models that can deviate from the actual system characteristics under different operating conditions and/or configurations. Data-driven approaches based on online measurements can be a better solution to addressing these issues by capturing real-time operation conditions. This article describes a novel fully data-driven probabilistic framework to derive a linear representation of postcontingency grid dynamics and online prescribe control based on the derived model to enhance transient stability. The complex nonlinear power system dynamics is approximated by a linear model by using multiple neural network modules that infer distributions of the observations and introducing a Koopman layer to sample possible Koopman linear models from the inferred distributions. The trained model features linearity that can be easily incorporated into the existing linear control design paradigm and ease the controller design process. The effectiveness of Koopman-based control designs is validated through comparative case studies, which demonstrate increased prediction accuracy and control performance when applied to a power system with heterogeneous generator dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Ion transport in non-aqueous electrolyte mixtures of zinc chloride deep eutectic solvent (DES) and molecular solvents

For this work, the ion dynamics of null solvents 1ZnCl 2 :4EtG and 1ChCl:1ZnCl 2 :6EtG incorporating 1M water, propylene carbonate (PC) or acetonitrile (AcN) were investigated using 1 H NMR spectra and spin-lattice relaxation time (T 1 ) measurements combined with ionic conductivity, density, and viscosity, all as a function of temperature. Results show that the inclusion of all co-solvents increased the available free volume of the mixtures and followed the trend H 2 O ≤ PC < AcN. 1 H NMR spectra and T 1 inferred the presence of multiple ionic species with varying rates of mobilities. These dynamic heterogeneities were displayed by the broad T 1 minima – especially for the 1ZnCl 2 :4EtG mixtures – and asymmetrically broadened linewidths. T 1 results also revealed selective interaction sites between the hydrogen bond donors and acceptors, as well as with the co-solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1987

Kinetic aspects of magnetotail dynamics - Observations

The observed kinetic (as opposed to fluid) aspects of particle behavior in the geomagnetic tail are discussed. Such behavior has been observed from thermal plasma energies to energies a few MeV or more. The importance of recognizing and analyzing the kinetic behavior of tail particles is that it provides a powerful diagnostic tool for inferring the state of the local and remote environment and the mechanisms responsible for observed tail dynamics, and a way of determining when fluid analyses (relying upon moments such as bulk velocity and temperature) may be misleading. Thus kinetic analyses provide a valuable complement to fluid-dynamics-based studies of the collective behavior of geomagnetic tail particles. Observed kinetic effects can be analyzed to examine spatial gradients; convection electric fields, distances to source regions, source-region characteristics, magnetic-field topology, heating/acceleration mechanism, boundary characteristics, and remote mechanisms affecting local particle distributions.

Mitchell, D. G.↗

DOE OSTI2020

Dealing with Measurement Uncertainties as Nuisance Parameters in Bayesian Model Calibration

In the presence of model discrepancy, the calibration of physics-based models for physical parameter inference is a challenging problem. Lack of identifiability between calibration parameters and model discrepancy requires additional identifiability constraints to be placed on the model discrepancy to obtain unique physical parameter estimates. If these assumptions are violated, the inference for the calibration parameters can be systematically biased. In many applications, such as in dynamic material property experiments, many of the calibration inputs refer to measurement uncertainties. Here, we develop a metric for identifying overfitting of these measurement uncertainties, propose a prior capable of reducing this overfitting, and show how this leads to a diagnostic tool for validation of physical parameter inference. The approach is demonstrated for a benchmark example and applied for a material property application to perform inference on the equation of state parameters of tantalum.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1991

Modelled and measured strain in mascon basins on the moon

The close association of wrinkle ridges and grabens with mascon basins on the Moon has suggested that the responsible compression and extension resulted from basin subsidence and peripheral flexing of the lithosphere. The distribution of grabens and wrinkle ridges associated with mascon basins has been further used along with elastic plate bending models to constrain the thickness of the lithosphere at the time of their formation. Kinematic models for basin subsidence have also been developed and compared with strains inferred from grabens and wrinkle ridges. Note that kinematic models may be preferable to dynamic models because the strain associated with tectonic features can be compared directly with model predictions and because fewer assumptions are required for their calculations, such as perfect elasticity and specific values of the elastic moduli. Also, if the results from kinematic models compare favorably with the strain estimated across the tectonic features on the Moon, then a global strain field may not be necessary. Herein, the strain inferred for wrinkle ridges and grabens was compared to that calculated from a simple kinematic subsidence model for mascon basins on the Moon.

Golombek, M. P.↗

DOE OSTI2025

Computing Nonlinear Power Spectra Across Dynamical Dark Energy Model Space with Neural ODEs

I show how to compute the nonlinear power spectrum across the entire $w(z)$ dynamical dark energy model space. Using synthetic ΛCDM data, I train a neural ordinary differential equation (ODE) to infer the evolution of the nonlinear matter power spectrum as a function of the background expansion and mean matter density across ∼9 Gyr of cosmic evolution. After training, the model generalises to any dynamical dark energy model parameterised by $w(z)$. With little optimisation, the neural ODE is accurate to within 4% up to $k = 5\, h\, {\mathrm Mpc}^{−1}$. Unlike simulation rescaling methods, neural ODEs naturally extend to summary statistics beyond the power spectrum that are sensitive to the growth history.

cosmology↗

DOE OSTI2021

Non-intrusive data-driven model reduction for differential–algebraic equations derived from lifting transformations

In this paper we present a non-intrusive data-driven approach for model reduction of nonlinear systems. The approach considers the particular case of nonlinear partial differential equations (PDEs) that form systems of partial differential–algebraic equations (PDAEs) when lifted to polynomial form. Such systems arise, for example, when the governing equations include Arrhenius reaction terms (e.g., in reacting flow models) and thermodynamic terms (e.g., the Helmholtz free energy terms in a phase-field solidification model). Using the known structured form of the lifted algebraic equations, the approach computes the reduced operators for the algebraic equations explicitly, using straightforward linear algebra operations on the basis matrices. The reduced operators for the differential equations are inferred from lifted snapshot data using operator inference, which solves a linear least squares regression problem. The approach is illustrated for the nonlinear model of solidification of a pure material. The lifting transformations reformulate the solidification PDEs as a system of PDAEs that have cubic structure. The operators of the lifted system for this solidification example have affine dependence on key process parameters, permitting us to learn a parametric reduced model with operator inference. Numerical experiments show the effectiveness of the resulting reduced models in capturing key aspects of the solidification dynamics.

42 ENGINEERING↗

NASA NTRS1976

The dynamical interaction between galaxies and intracluster gas in clusters of galaxies

The interaction between the hot gas inferred to exist in clusters of galaxies and the interstellar medium of a spherical galaxy has been studied by means of time-dependent numerical hydrodynamics. Galaxies moving at transonic speeds with respect to the ambient medium lose 80% to 90% of their interstellar gas before a crossing time has elapsed. The amount of gas remaining is consistent with current observational limits to the gas content of elliptical galaxies. Negligible heating of the intracluster gas results from this process. Implications of these results for spiral galaxies with halos, radio sources in clusters of galaxies, and globular clusters in galactic halos are discussed.

Lea, S. M.↗