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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Statistical Properties for Flows with Unbounded Roof Function, Including the Lorenz Attractor

For geometric Lorenz attractors (including the classical Lorenz attractor) we obtain a greatly simplified proof of the central limit theorem which applies also to the more general class of codimension two singular hyperbolic attractors. We also obtain the functional central limit theorem and moment estimates, as well as iterated versions of these results. A consequence is deterministic homogenisation (convergence to a stochastic differential equation) for fast-slow dynamical systems whenever the fast dynamics is singularly hyperbolic of codimension two.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation

Here, we present a supervised learning framework of training generative models for density estimation. Generative models, including generative adversarial networks (GANs), normalizing flows, and variational auto-encoders (VAEs), are usually considered as unsupervised learning models, because labeled data are usually unavailable for training. Despite the success of the generative models, there are several issues with the unsupervised training, e.g., requirement of reversible architectures, vanishing gradients, and training instability. To enable supervised learning in generative models, we utilize the score-based diffusion model to generate labeled data. Unlike existing diffusion models that train neural networks to learn the score function, we develop a training-free score estimation method. This approach uses mini-batch-based Monte Carlo estimators to directly approximate the score function at any spatial-temporal location in solving an ordinary differential equation (ODE), corresponding to the reverse-time stochastic differential equation (SDE). This approach can offer both high accuracy and substantial time savings in neural network training. Once the labeled data are generated, we can train a simple, fully connected neural network to learn the generative model in the supervised manner. Compared with existing normalizing flow models, our method does not require the use of reversible neural networks and avoids the computation of the Jacobian matrix. Compared with existing diffusion models, our method does not need to solve the reverse-time SDE to generate new samples. As a result, the sampling efficiency is significantly improved. We demonstrate the performance of our method by applying it to a set of 2D datasets as well as real data from the University of California Irvine (UCI) repository.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Nuclear kinetic density from ab initio theory

The nuclear kinetic density is one of many fundamental, nonobservable quantities in density functional theory (DFT) dependent on the nonlocal nuclear density. Often, approximations may be made when computing the density that may result in spurious contributions in other DFT quantities. With the ability to compute the nonlocal nuclear density from ab initio wave functions, it is now possible to estimate effects of such spurious contributions. Herein, we derive the kinetic density using ab initio nonlocal scalar one-body nuclear densities computed within the no-core shell model (NCSM) approach, utilizing two- and three-nucleon chiral interactions as the sole input. The ability to compute translationally invariant nonlocal densities allows us to gauge the impact of the spurious center-of-mass (c.m.) contributions in DFT quantities, such as the kinetic density, and provide ab initio insight into refining energy density functionals. The nonlocal nuclear densities are derived from the NCSM one-body densities calculated in second quantization. We present a review of c.m. contaminated and translationally invariant nuclear densities. We then derive an analytic expression for the kinetic density using these nonlocal densities, producing an ab initio kinetic density. The ground-state nonlocal densities of He 4 , 6 , 8 , C 12 , and O 16 are used to compute the kinetic densities of the aforementioned nuclei. The impact of c.m. removal techniques in the density are discussed and compared to a procedure applied in DFT. The results of this work can be extended to other fundamental quantities in DFT. The use of a general nonlocal density allows for the calculation of fundamental quantities taken as input in theories such as DFT. This allows benchmarking c.m. removal procedures and provides a bridge for comparison between ab initio and DFT many-body techniques.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Error Estimates for the Optimal Control of a Parabolic Fractional PDE

In this work, we consider the integral definition of the fractional Laplacian and analyze a linear-quadratic optimal control problem for the so-called fractional heat equation; control constraints are also considered. We derive existence and uniqueness results, first order optimality conditions, and regularity estimates for the optimal variables. To discretize the state equation we propose a fully discrete scheme that relies on an implicit finite difference discretization in time combined with a piecewise linear finite element discretization in space. We derive stability results and a novel $L^2(0,T;L^2(\Omega))$ a priori error estimate. On the basis of the aforementioned solution technique, we propose a fully discrete scheme for our optimal control problem that discretizes the control variable with piecewise constant functions, and we derive a priori error estimates for it. We illustrate the theory with one- and two-dimensional numerical experiments.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1977

Estimates of explosive yield

Explosive yield as a function of propellant type and accident conditions was discussed along with the characteristics of propellant explosions. Three types of fuel-hypergolic, liquid oxygen-hydrocarbon, and liquid oxygen-liquid-hydrogen were considered. Data are also given on three modes (failure modes) of mixing: confinement by missile, confinement by ground surface, and high velocity impact.

Source record↗
NASA NTRS2015

Estimation of an Optimal Stimulus Amplitude for Using Vestibular Stochastic Stimulation to Improve Balance Function

Sensorimotor changes such as postural and gait instabilities can affect the functional performance of astronauts when they transition across different gravity environments. We are developing a method, based on stochastic resonance (SR), to enhance information transfer by applying non-zero levels of external noise on the vestibular system (vestibular stochastic resonance, VSR). The goal of this project was to determine optimal levels of stimulation for SR applications by using a defined vestibular threshold of motion detection.

Goel, R.↗
DOE OSTI2019

Isopiestic Measurements of Water Adsorption on Uranium Bearing Solids - 1900w

The research focus was to investigate the stability of the multicomponent uranium-bearing precipitates mimicking those created in sediments as a result of alkaline ammonia gas treatment in the vadose zone. Gravimetric measurements of moisture uptake on uranium-bearing precipitates as a function of increasing relative humidity can provide reasonable estimates of the deliquescence point of solid phases or its components. Water moisture uptake by uranium-bearing precipitates as a function of increasing relative humidity was measured at 25 deg. C via the isopiestic method. The conditions for each isotherm were calculated by a division of the amount of adsorbed moisture by the amount of dry precipitate samples. This method can provide estimates of water quantity retained within precipitates conducted in the range of water activities. The desorption portion of the isotherm was obtained by progressively decreasing the water activity or relative pressure in the isopiestic chamber while monitoring the equilibrium amount of moisture sorbed at each relative pressure. The amount of water adsorbed by multicomponent precipitates at a{sub w} = 0.67 ranged between 0.63 and 0.77 g water/g precipitate. Higher water activities or relative humidity values eventually lead to the deliquescence of the solid or its components and the formation of a liquid phase. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Features of ZnO Nanocrystal Size Distribution in a Polymer Matrix

X-ray diffraction patterns of a photocurable epoxy acryl-based polymer composite with addition of ZnO nanocrystals are analyzed. We recover the size distribution function of the ZnO nanocrystals and estimate the median size of the nanocrystals (∼40–50 nm) from a detailed analysis of the most intensive peak in the X-ray diffraction pattern.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1979

Optimal estimation of large structure model errors

In-flight estimation of large structure model errors is usually required as a means of detecting inevitable deficiencies in large structure controller/estimator models. The present paper deals with a least-squares formulation which seeks to minimize a quadratic functional of the model errors. The properties of these error estimates are analyzed. It is shown that an arbitrary model error can be decomposed as the sum of two components that are orthogonal in a suitably defined function space. Relations between true and estimated errors are defined. The estimates are found to be approximations that retain many of the significant dynamics of the true model errors. Current efforts are directed toward application of the analytical results to a reference large structure model.

Rodriguez, G.↗
DOE OSTI2016

On the induced gravitational collapse scenario of gamma-ray bursts associated with supernovae

Following the induced gravitational collapse (IGC) paradigm of gamma-ray bursts (GRBs) associated with type Ib/c supernovae, we present numerical simulations of the explosion of a carbon–oxygen (CO) core in a binary system with a neutron-star (NS) companion. The supernova ejecta trigger a hypercritical accretion process onto the NS thanks to a copious neutrino emission and the trapping of photons within the accretion flow. We show that temperatures of 1–10 MeV develop near the NS surface, hence electron–positron annihilation into neutrinos becomes the main cooling channel leading to accretion rates of 10{sup −9}–10{sup −1} M{sub ⊙} s{sup −1} and neutrino luminosities of 10{sup 43}–10{sup 52} erg s{sup −1} (the shorter the orbital period the higher the accretion rate). We estimate the maximum orbital period, P{sub max}, as a function of the NS initial mass, up to which the NS companion can reach by hypercritical accretion the critical mass for gravitational collapse leading to black hole formation. We then estimate the effects of the accreting and orbiting NS companion onto a novel geometry of the supernova ejecta density profile. We present the results of a 1.4×10{sup 7} particle simulation which show that the NS induces accentuated asymmetries in the ejecta density around the orbital plane. We elaborate on the observables associated with the above features of the IGC process. We apply this framework to specific GRBs: we find that X-ray flashes (XRFs) and binary-driven hypernovae are produced in binaries with P>P{sub max} and P<P{sub max}, respectively. We analyze in detail the case of XRF 060218.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2012

Mass and Momentum Transport in Microcavities for Diffusion-Dominant Cell Culture Applications

For the informed design of microfluidic devices, it is important to understand transport phenomena at the microscale. This letter outlines an analytically-driven approach to the design of rectangular microcavities extending perpendicular to a perfusion microchannel for microfluidic cell culture devices. We present equations to estimate the spatial transition from advection- to diffusion-dominant transport inside cavities as a function of the geometry and flow conditions. We also estimate the time required for molecules, such as nutrients or drugs to travel from the microchannel to a given depth into the cavity. These analytical predictions can facilitate the rational design of microfluidic devices to optimize and maintain long-term, physiologically-based culture conditions with low fluid shear stress.

Yew, Alvin G.↗
DOE OSTI2018

A numerical approach for solving a class of variable-order fractional functional integral equations

This paper proposes new discretization techniques to estimate variable-order fractional integral operators based on the piecewise integro quadratic spline interpolation. The proposed methods are modified to solve a class of variable-order fractional functional integral equations. Moreover, we investigate the performance of the proposed methods by solving the variable-order fractional pantograph and Emden–Fowler functional integral equations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2012

Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscape Assessed with High Quality Reference Data

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern USforests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are available. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery usingthe CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50, 75, and 100 energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns ofMISR 672 nm band surface reflectance (mean RMSE 0.011, mean R2 0.82, N 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid.The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Chopping, Mark↗
NASA NTRS2014

Estimation of Crop Gross Primary Production (GPP): I. Impact of MODIS Observation Footprint and Impact of Vegetation BRDF Characteristics

Accurate estimation of gross primary production (GPP) is essential for carbon cycle and climate change studies. Three AmeriFlux crop sites of maize and soybean were selected for this study. Two of the sites were irrigated and the other one was rainfed. The normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the green band chlorophyll index (CIgreen), and the green band wide dynamic range vegetation index (WDRVIgreen) were computed from the moderate resolution imaging spectroradiometer (MODIS) surface reflectance data. We examined the impacts of the MODIS observation footprint and the vegetation bidirectional reflectance distribution function (BRDF) on crop daily GPP estimation with the four spectral vegetation indices (VIs - NDVI, EVI, WDRVIgreen and CIgreen) where GPP was predicted with two linear models, with and without offset: GPP = a × VI × PAR and GPP = a × VI × PAR + b. Model performance was evaluated with coefficient of determination (R2), root mean square error (RMSE), and coefficient of variation (CV). The MODIS data were filtered into four categories and four experiments were conducted to assess the impacts. The first experiment included all observations. The second experiment only included observations with view zenith angle (VZA) ≤ 35◦ to constrain growth of the footprint size,which achieved a better grid cell match with the agricultural fields. The third experiment included only forward scatter observations with VZA ≤ 35◦. The fourth experiment included only backscatter observations with VZA ≤ 35◦. Overall, the EVI yielded the most consistently strong relationships to daily GPP under all examined conditions. The model GPP = a × VI × PAR + b had better performance than the model GPP = a × VI × PAR, and the offset was significant for most cases. Better performance was obtained for the irrigated field than its counterpart rainfed field. Comparison of experiment 2 vs. experiment 1 was used to examine the observation footprint impact whereas comparison of experiment 4 vs. experiment 3 was used to examine the BRDF impact. Changes in R2, RMSE,CV and changes in model coefficients "a" and "b" (experiment 2 vs. experiment 1; and experiment 4 vs. experiment 3) were indicators of the impacts. The second experiment produced better performance than the first experiment, increasing R2 (↑0.13) and reducing RMSE (↓0.68 g C m−2 d−1) and CV (↓9%). For each VI, the slope of GPP = a × VI × PAR in the second experiment for each crop type changed little while the slope and intercept of GPP = a × VI × PAR + b varied field by field. The CIgreen was least affected by the MODIS observation footprint in estimating crop daily GPP (R2, ↑0.08; RMSE, ↓0.42 g C m−2 d−1; and CV, ↓7%). Footprint most affected the NDVI (R2, ↑0.15; CV, ↓10%) and the EVI (RMSE, ↓0.84 g C m−2 d−1). The vegetation BRDF impact also caused variation of model performance and change of model coefficients. Significantly different slopes were obtained for forward vs. backscatter observations, especially for the CIgreen and the NDVI. Both the footprint impact and the BRDF impact varied with crop types, irrigation options, model options and VI options.

Chlorophyll↗
NASA NTRS2005

Proposed Project Selection Method for Human Support Research and Technology Development (HSR&TD)

The purpose of HSR&TD is to deliver human support technologies to the Exploration Systems Mission Directorate (ESMD) that will be selected for future missions. This requires identifying promising candidate technologies and advancing them in technology readiness until they are acceptable. HSR&TD must select an may of technology development projects, guide them, and either terminate or continue them, so as to maximize the resulting number of usable advanced human support technologies. This paper proposes an effective project scoring methodology to support managing the HSR&TD project portfolio. Researchers strongly disagree as to what are the best technology project selection methods, or even if there are any proven ones. Technology development is risky and outstanding achievements are rare and unpredictable. There is no simple formula for success. Organizations that are satisfied with their project selection approach typically use a mix of financial, strategic, and scoring methods in an open, established, explicit, formal process. This approach helps to build consensus and develop management insight. It encourages better project proposals by clarifying the desired project attributes. We propose a project scoring technique based on a method previously used in a federal laboratory and supported by recent research. Projects are ranked by their perceived relevance, risk, and return - a new 3 R's. Relevance is the degree to which the project objective supports the HSR&TD goal of developing usable advanced human support technologies. Risk is the estimated probability that the project will achieve its specific objective. Return is the reduction in mission life cycle cost obtained if the project is successful. If the project objective technology performs a new function with no current cost, its return is the estimated cash value of performing the new function. The proposed project selection scoring method includes definitions of the criteria, a project evaluation questionnaire, and a scoring formula.

Jones, Harry↗
DOE OSTI2018

Fundamental Properties of Co-moving Stars Observed by Gaia

We have estimated fundamental parameters for a sample of co-moving stars observed by Gaia and identified by Oh et al. We matched the Gaia observations to the 2MASS and Wide-Field Infrared Survey Explorer catalogs and fit MIST isochrones to the data, deriving estimates of the mass, radius, [Fe/H], age, distance, and extinction to 9754 stars in the original sample of 10606 stars. We verify these estimates by comparing our new results to previous analyses of nearby stars, examining fiducial cluster properties, and estimating the power-law slope of the local present-day mass function. A comparison to previous studies suggests that our mass estimates are robust, while metallicity and age estimates are increasingly uncertain. We use our calculated masses to examine the properties of binaries in the sample and show that separation of the pairs dominates the observed binding energies and expected lifetimes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

On the geometric dependence of the molecular dipole polarizability in water: A benchmark study of higher-order electron correlation, basis set incompleteness error, core electron effects, and zero-point vibrational contributions

In this work, we investigate how geometric changes influence the static dipole polarizability ($α$) of a water molecule by explicitly computing the corresponding dipole polarizability surface (DPS) across 3125 total (1625 symmetry-unique) geometries using linear response coupled cluster theory including single, double, and triple excitations (LR-CCSDT) and the doubly augmented triple-$ζ$ basis set (d-aug-cc-pVTZ). Analytical formulae based on power series expansions of this $ab initio$ surface are generated using linear least-squares analysis and provide highly accurate estimates of this quantity as a function of molecular geometry (i.e., bond and angle variations) in a computationally tractable manner. An additional database, which consists of 25 representative molecular geometries and incorporates a more thorough treatment of both basis sets and core electron effects, is provided as a current benchmark for this quantity and the corresponding leading-order $C_6$ dispersion coefficient. This database has been utilized to assess the importance of these effects as well as the relative accuracy that can be obtained using several quantum chemical methods and a library of density functional approximations. In addition to high-level electron correlation methods (like CCSD) and our analytical least-squares formulae, we find that the SCAN0, PBE0, MN15, and B97-2 hybrid functionals yield the most accurate descriptions of the molecular polarizability tensor in H 2 O. Using first-order perturbation theory, we compute the zero-point vibrational correction to $α$ at the CCSDT/d-aug-cc-pVTZ level and find that this correction contributes approximately 3% to the isotropic ($α$ iso ) and nearly 50% to the anisotropic ($α$ aniso ) polarizability values. In doing so, we find that $α$ iso = 9.8307 bohr 3 , which is in excellent agreement with the experimental value of 9.83 ± 0.02 bohr 3 provided by Russell and Spackman. The DPS reported herein provides a benchmark-quality quantum mechanical estimate of this fundamental quantity of interest and should find extensive use in the development (and assessment) of next-generation force fields and machine-learning based approaches for modeling water in complex condensed-phase environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Likelihood Methods for CMB Experiments

A great deal of experimental effort is currently being devoted to the precise measurements of the cosmic microwave background (CMB) sky in temperature and polarization. Satellites, balloon-borne, and ground-based experiments scrutinize the CMB sky at multiple scales, and therefore enable to investigate not only the evolution of the early Universe, but also its late-time physics with unprecedented accuracy. The pipeline leading from time ordered data as collected by the instrument to the final product is highly structured. Moreover, it has also to provide accurate estimates of statistical and systematic uncertainties connected to the specific experiment. In this paper, we review likelihood approaches targeted to the analysis of the CMB signal at different scales, and to the estimation of key cosmological parameters. We consider methods that analyze the data in the spatial (i.e., pixel-based) or harmonic domain. We highlight the most relevant aspects of each approach and compare their performance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗