Search NASA⌕ Search

SEARCH · Search NASA

Results for “random fields”

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

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Renormalization group computation of likelihood functions for cosmological data sets

I show how a renormalization group (RG) method can be used to incrementally integrate the information in cosmological large-scale structure data sets (including CMB, galaxy redshift surveys, etc.). I show numerical tests for Gaussian fields, where the method allows arbitrarily close to exact computation of the likelihood function in order N time, even for problems with no symmetry, compared to N 3 for brute force linear algebra (where N is the number of data points - to be fair, methods already exist to solve the Gaussian problem in at worst N log N time, and this method will not necessarily be faster in practice). The method requires no sampling or other Monte Carlo (random) element. Nonlinearity/non-Gaussianity can be accounted for to the extent that terms generated by integrating out small scale modes can be projected onto a sufficient basis, e.g., at least in the sufficiently perturbative regime. The formulas to evaluate are straightforward and require no understanding of quantum field theory, but this paper may also serve as a pedagogical introduction to Wilsonian RG for astronomers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Modeling and simulations of hydrodynamic shocks in a plasma flowing across randomized ICF scale laser beams

High-energy laser beams interacting with flowing plasmas can produce a plasma response that leads to deflection of the beam, beam bending. Such beams have usually a speckle structure generated by optical smoothing techniques that reduce the spatial and temporal coherence in the laser field pattern. The cumulative plasma response from laser speckles slows down the velocity of the incoming flow by momentum conservation. For slightly super-sonic flow the cumulative plasma response to the ponderomotive force exerted by the beam speckle ensemble is the strongest, such that slowing down the flow to subsonic velocities leads eventually to the generation of a shock around the cross section of the beam. This scenario has been predicted theoretically and is confirmed here by our hydrodynamic simulations in two dimensions with speckled beams and in one dimension with a reduced model. The conditions of shock generation are given in terms of the ponderomotive pressure, speckle size and the flow velocity. The nonlinear properties of the shocks are analyzed using Rankine–Hugoniot relations. According to linear theory, temporally smoothed laser beams exhibit a higher threshold for shock generation. Numerical simulations with beams that are smoothed by spectral dispersion compare well with the linear theory results, diverging from those produced by beams with only a random phase plates in the nonlinear regime. The conditions necessary for shock generation and their effects on the laser plasma coupling in inertial confinement fusion (ICF) experiments are also discussed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A crystal plasticity model with an atomistically informed description of grain boundary sliding for improved predictions of deformation fields

Crystal plasticity (CP) is a powerful meso-scale technique for deformation modeling in polycrystalline materials. Crystal plasticity models typically do not include an explicit description of grain boundary (GB) sliding, which could lead to inaccurate predictions of strain distributions, especially in the vicinity of GBs. In the present study, a CP model is developed that includes GB sliding as an additional deformation mechanism and models the interaction between slip and GB sliding. Atomistic simulations are used to formulate the constitutive model for GB sliding and its interaction with incident slip. The deformation fields and structure of the GBs are obtained directly from experimental characterization and are faithfully reproduced as bicrystal systems for molecular dynamics simulations. The GBs are modeled as random-type (non-coincidence, asymmetrical) boundaries as observed from experimental data. The underlying atomistic-scale mechanism for pure sliding of random GBs was found to be analogous to fluid-flow. The interaction between incident slip and a sliding GB caused local increases in stress concentration, which further led to a momentary increase in the local sliding rate. The displacement profiles at the sliding GBs computed from the CP model with sliding accommodation are 38% more accurate than the baseline CP model as quantified by the mean squared error between the simulations and experiment. Here these results help improve the sophistication and accuracy of deformation modeling by including physics-based descriptions for GB sliding and its interaction with slip, eventually leading to more reliable predictions of micromechanical quantities.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Relaxation dynamics of vortex lines in disordered type-II superconductors following magnetic field and temperature quenches

We study the effects of rapid temperature and magnetic field changes on the nonequilibrium relaxation dynamics of magnetic vortex lines in disordered type-II superconductors by employing an elastic line model and performing Langevin molecular dynamics simulations. In a previously equilibrated system, either the temperature is suddenly changed or the magnetic field is instantaneously altered which is reflected in adding or removing flux lines to or from the system. Here, the subsequent aging properties are investigated in samples with either randomly distributed pointlike or extended columnar defects, which allows us to distinguish the complex relaxation features that result from either type of pinning centers. One-time observables such as the radius of gyration and the fraction of pinned line elements are employed to characterize steady-state properties, and two-time correlation functions such as the vortex line height autocorrelations and their mean-square displacement are analyzed to study the nonlinear stochastic relaxation dynamics in the aging regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Making Quality HPGe Gamma Ray Spectrum Measurements for Uranium: The Role of FRAM for Analysis, Quality Control and Enrichment Measurements, and Opportunities for Improved Quantification Documentation

Enrichment measurements are used in uranium safeguards verification and accountancy as both an attribute signature and in the interpretation of other nondestructive assay information, such as active interrogation for mass. Accurate and reliable assessments require quality information. The practices used to collect the raw data are therefore the crucial first step in managing the overall quality and uncertainty of the enrichment determination. This report discusses several topics associated with gamma-ray spectrum measurements of uranium using HPGe detectors. First a discussion of good data acquisition practices including physical setup, detector types and configurations, detector shielding and filtering, spectrum stabilization, and data acquisition protocols. Next is a discussion of analysis options to obtain isotopic composition and/or enrichment centered on the FRAM gamma ray isotopic analysis software. The report discusses the results of the development of a FRAM parameter file to perform classical Enrichment Meter Principle (EMP) analysis. Possible analysis and data acquisition issues (random summing, x-ray fluorescence peaks, peak interferences, shielding) that can affect FRAM analyses are also discussed. There is also a brief discussion of FRAM measurements in the field. Under the topic of uncertainty propagation and quantification in FRAM, uncertainty propagation verification methods and gaps in available uncertainty quantification data for uranium is covered. Suggestions are made for areas where ORNL can contribute to closing the identified uncertainty quantification gaps, and also to contributing nuclear data quality spectra to the research community.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS1971

Communication theory of quantum systems

Communication theory problems incorporating quantum effects for optical-frequency applications are discussed. Under suitable conditions, a unique quantum channel model corresponding to a given classical space-time varying linear random channel is established. A procedure is described by which a proper density-operator representation applicable to any receiver configuration can be constructed directly from the channel output field. Some examples illustrating the application of our methods to the development of optical quantum channel representations are given. Optimizations of communication system performance under different criteria are considered. In particular, certain necessary and sufficient conditions on the optimal detector in M-ary quantum signal detection are derived. Some examples are presented. Parameter estimation and channel capacity are discussed briefly.

Yuen, H. P. H.↗
NASA NTRS1973

Videomagnetograph studies of solar magnetic fields. II - Field changes in an active region

Using the Caltech videomagnetograph, we obtained a 6.5-hr movie of the magnetic fields in a young active region. The major contribution to the short term magnetic evolution of the region was provided by many discrete magnetic points which move in apparently random directions with typical velocities of 0.4 - 1.0 km/sec. The majority of these features appear to be footpoints of new EFR's, which emerge at an observed rate of one to two per hour. The pattern of the motions suggests that the magnetic evolution of a growing region cannot be principally due to photospheric convective cells.

Schoolman, S. A.↗
NASA NTRS1974

U.S. National Congress of Applied Mechanics, 7th, University of Colorado, Boulder, Colo., June 3-7, 1974, Proceedings

A series of experimental, theoretical, and review papers dealing with various aspects of applied mechanics, including structural analysis, mathematical methods, and fluid dynamics. Some of the topics covered are: the direct formulation of two-dimensional mechanics problems, the mechanical aspects of athletics, Laplace's tidal equations, cochlear mechanics, dynamic constitutive equations, optical techniques for the determination of displacement and strain fields, chemical and biochemical problems involving nonlinear diffusion processes, thermal stresses, the rotating rod viscometer, finite-element methods in plasticity, ships of minimum resistance, and wide-band random vibration of structures. Individual items are announced in this issue.

Source record↗
NASA NTRS1980

Radiative transfer theory for passive microwave remote sensing of a two-layer random medium with cylindrical structures

A model of the vegetation layer as a two-layer random medium with a small correlation length l sub rho in the horizontal direction, and a large correlation length l sub z in the vertical direction, is presented for fields with cylindrical structures. As l sub z approaches infinity, closed form solutions are derived for the brightness temperatures; the kernels in the scattering terms of the radiative transfer equations result in delta functions showing that forward scattering is dominant over all other directions. The results are compared with the Gaussian quadrature method data for numerical solution of the radiative transfer equations.

Chuang, S. L.↗
NASA NTRS1993

Relationship of attenuation in a vegetation canopy to physical parameters of the canopy

A discrete scatter model is employed to compute the radiometric response (i.e. emissivity) of a layer of vegetation over a homogeneous ground. This was done to gain insight into empirical formulas for the emissivity which have recently appeared in the literature and which indicate that the attenuation through the canopy is proportional to the water content of the vegetation and inversely proportional to wavelength raised to a power around unity. The analytical result assumes that the vegetation can be modeled by a sparse layer of discrete, randomly oriented particles (leaves, stalks, etc.). The attenuation is given by the effective wave number of the layer obtained from the solution for the mean wave using the effective field approximation. By using the Ulaby-El Rayes formula to relate the dielectric constant of the vegetation to its water content, it can be shown that the attenuation is proportional to water content. The analytical form offers insight into the dependence of the empirical parameters on other variables of the canopy, including plant geometry (i.e. shape and orientation of the leaves and stalks of which the vegetation is comprised), frequency of the measurement and even the physical temperature of the vegetation. Solutions are presented for some special cases including layers consisting of cylinders (stalks) and disks (leaves).

Karam, M. A.↗
NASA NTRS1997

Retrieval of Soil Moisture and Roughness from the Polarimetric Radar Response

The main objective of this investigation was the characterization of soil moisture using imaging radars. In order to accomplish this task, a number of intermediate steps had to be undertaken. In this proposal, the theoretical, numerical, and experimental aspects of electromagnetic scattering from natural surfaces was considered with emphasis on remote sensing of soil moisture. In the general case, the microwave backscatter from natural surfaces is mainly influenced by three major factors: (1) the roughness statistics of the soil surface, (2) soil moisture content, and (3) soil surface cover. First the scattering problem from bare-soil surfaces was considered and a hybrid model that relates the radar backscattering coefficient to soil moisture and surface roughness was developed. This model is based on extensive experimental measurements of the radar polarimetric backscatter response of bare soil surfaces at microwave frequencies over a wide range of moisture conditions and roughness scales in conjunction with existing theoretical surface scattering models in limiting cases (small perturbation, physical optics, and geometrical optics models). Also a simple inversion algorithm capable of providing accurate estimates of soil moisture content and surface rms height from single-frequency multi-polarization radar observations was developed. The accuracy of the model and its inversion algorithm is demonstrated using independent data sets. Next the hybrid model for bare-soil surfaces is made fully polarimetric by incorporating the parameters of the co- and cross-polarized phase difference into the model. Experimental data in conjunction with numerical simulations are used to relate the soil moisture content and surface roughness to the phase difference statistics. For this purpose, a novel numerical scattering simulation for inhomogeneous dielectric random surfaces was developed. Finally the scattering problem of short vegetation cover above a rough soil surface was considered. A general scattering model for grass-blades of arbitrary cross section was developed and incorporated in a first order random media model. The vegetation model and the bare-soil model are combined and the accuracy of the combined model is evaluated against experimental observations from a wheat field over the entire growing season. A complete set of ground-truth data and polarimetric backscatter data were collected. Also an inversion algorithm for estimating soil moisture and surface roughness from multi-polarized multi-frequency observations of vegetation-covered ground is developed.

Sarabandi, Kamal↗
NASA NTRS1984

Pitch angle diffusion in the Jovian magnetodisc

Using a linear approximation to the field variation and a mathematical technique for distorting the orbit integration into the complex gyrophase plane, a formula is derived for the nonadiabatic change in magnetic moment. This change varies as the cosine of the particle gyrophase at the equator, so that if a particle traverses the equator several times with different values of this gyrophase, it suffers randomly correlated values for the nonadiabatic change in magnetic moment. The algebraic formula for this nonadiabatic change is found to be in excellent agreement with previous numerical computations. The phase space density, averaged over several bounce periods, is found to satisfy a diffusion equation in pitch angle. The diffusion coefficient is dependent on particle energy, pitch angle, and the field line along which the particles are moving.

Birmingham, T. J.↗
DOE OSTI2023

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗
NASA NTRS2021

First Measurements of Ambient PM2.5 in Kinshasa, Democratic Republic of Congo and Brazzaville, Republic of Congo Using Field-calibrated Low-cost Sensors

Estimates of air pollution mortality in sub-Saharan Africa are limited by a lack of surface observations of fine particulate matter (PM2.5). Despite being large metropolises, Kinshasa, Democratic Republic of the Congo (DRC), population 14.3 million, and Brazzaville, Republic of the Congo (ROC), population 2.4 million, have no reference air pollution monitors at the time of writing. Recently, a few reference monitors have been deployed in other parts of sub-Saharan Africa, including Kampala, Uganda. A low-cost PurpleAir PM2.5 monitor was collocated next to the Kampala US Embassy BAM-1020 (Met One Beta Attenuation Monitor) starting in August 2019. Raw PurpleAir data are strongly correlated with the BAM (r(exp 2) = 0.88), but have a mean absolute error of approximately 14 μg/cu.m. Two calibration models, multiple linear regression and a random forest approach, decrease mean absolute error (MAE) from 14.3 μg/cu.m to 3.4 µg/cu.m or less and improve the the r(exp 2) from 0.88 to 0.96. Given )the similarity in climate and emissions in Kampala, we apply the collocated field correction factors to four PurpleAir sensors in Kinshasa, DRC and one in neighboring Brazzaville, ROC deployed beginning April 2018. Annual average PM2.5 for 2019 in Kinshasa is estimated at 43.5 µg/cu.m, more than 4 times higher than WHO Interim Target 1 of 10 µg/cu.m. Surface PM2.5 and aerosol optical depth were each about 40% lower during the 2020 COVID19 lockdown period compared to the same time period in 2019, which cannot be explained by changes in meteorology or wildfire emissions alone. Our results highlight the need for clean air solutions implementation in the Congo.

Celeste McFarlane↗
DOE OSTI2016

A phase-field approach to model multi-axial and microstructure dependent fracture in nuclear grade graphite

The fracture behavior of nuclear grade graphites is strongly influenced by underlying microstructural features such as the character of filler particles, and the distribution of pores and voids. These microstructural features influence the crack nucleation and propagation behavior, resulting in quasi-brittle fracture with a tortuous crack path and significant scatter in measured bulk strength. This paper uses a phase-field method to model the microstructural and multi-axial fracture in H-451, a historic variant of nuclear graphite that provides the basis for an idealized study on a legacy grade. The representative volume elements are constructed from randomly located pores with random size obtained from experimentally determined log-normal distribution. The representative volume elements are then subjected to simulated multi-axial loading, and a reasonable agreement of the resulting fracture stress with experiments is obtained. Finally, quasi-brittle stress-strain evolution with a tortuous crack path is also observed from the simulations and is consistent with experimental results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Artificial neural network in cosmic landscape

In this study we propose that artificial neural network, the basis of machine learning, is useful to generate the inflationary landscape from a cosmological point of view. Traditional numerical simulations of a global cosmic landscape typically need an exponential complexity when the number of fields is large. However, a basic application of artificial neural network could solve the problem based on the universal approximation theorem of the multilayer perceptron. A toy model in inflation with multiple light fields is investigated numerically as an example of such an application.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Mapping tree height in complex terrain of northern China using ultra-high-resolution images

Tree height is a key parameter for estimating forest biomass and carbon sequestration. In recent years, notable progress has been made in mapping tree height using satellite imagery. However, existing tree height products show low accuracy in mountainous and complex terrains, and few studies typically addressed tree height estimations in mountain areas. This study examines the Mentougou district of Beijing, China, characterized by complex terrain and mountainous landscapes. We analyzed two methods for estimating tree height: one using only spectral features and another combining spectral features with topographic factors (elevation, slope, aspect). We used 3-m resolution PlanetScope 8-band multispectral imagery, with 710 field-measured individual tree heights averaged to obtain 471 pixel-level tree height values as ground-truth, to develop tree height prediction models using eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Gradient Boosting Machine (GBM) models. The results show that the XGBoost model consistently presented the highest accuracy for both methods evaluated. Specifically, the XGBoost model that combined spectral data with elevation and slope variables with an R² of 0.75 and an RMSE of 2.69 m. Using the XGBoost model, we generated the tree height map for the Mentougou area at 3 m resolution, showing tree heights ranging from 0.5 to 30.4 m, and the model’s prediction error standard deviations ranged from 2.50 to 4.71 m, indicating reliable performance across varied terrain. Additionally, we compared and evaluated the global tree height products, identifying limitations in the accuracy within complex terrains. This study demonstrates the potential for accurately predicting tree heights by combining high-resolution multispectral satellites with a terrain factor modeling approach.

Complex terrain↗
DOE OSTI2020

The effect of local chemical ordering on Frank-Read source activation in a refractory multi-principal element alloy

In this work, we investigate the operation of Frank-Read (FR) sources in a refractory multi-principal element alloy (MPEA). Simulations of discrete dislocation motion in MPEAs is enabled by the development of a phase field dislocation dynamics model that treats the atomic-scale fluctuations in lattice energies across the glide plane, present due to local ordering in the chemical composition within the nominally random MPEA atomic structure. We consider, through simulation, a range of length scales over which ordering occurs, varying from short-range lengths, a few times dislocation core width, to long-range lengths, an order of magnitude longer than the core. Characteristic of this body-centered cubic MPEA, the simulations also include screw/edge character dependence in glide resistance, as informed by atomic scale simulation. The critical stresses to activate the source for the same source size are found to be statistically distributed, as a direct consequence of the underlying variation in lattice energy. Furthermore, analysis of critical state for activating edge and screw FR sources in the MPEA reveals that FR source operation occurs via a two-step mechanism, involving athermal kink-pair formation, unlike the conventional FR source operation in a material with no composition fluctuations. This mechanism lowers the average critical stress required to activate the FR source and causes the statistical dispersion in critical stress to depend on the range of composition ordering. More importantly, it leads to a more severe dependence of source strength on FR source length than predicted by line tension alone.

36 MATERIALS SCIENCE↗