Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Statistics”

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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Estimating uncertainties in statistics computed from direct numerical simulation

Rigorous assessment of uncertainty is crucial to the utility of direct numerical simulation (DNS) results. Uncertainties in the computed statistics arise from two sources: finite statistical sampling and the discretization of the Navier–Stokes equations. Due to the presence of non-trivial sampling error, standard techniques for estimating discretization error (such as Richardson extrapolation) fail or are unreliable. This work provides a systematic and unified approach for estimating these errors. First, a sampling error estimator that accounts for correlation in the input data is developed. Then, this sampling error estimate is used as part of a Bayesian extension of Richardson extrapolation in order to characterize the discretization error. These methods are tested using the Lorenz equations and are shown to perform well. These techniques are then used to investigate the sampling and discretization errors in the DNS of a wall-bounded turbulent flow at Reτ ≈ 180. Both small (Lx/δ × Lz/δ = 4π × 2π) and large (Lx/δ × Lz/δ = 12π × 4π) domain sizes are investigated. For each case, a sequence of meshes was generated by first designing a “nominal” mesh using standard heuristics for wall-bounded simulations. These nominal meshes were then coarsened to generate a sequence of grid resolutions appropriate for the Bayesian Richardson extrapolation method. In addition, the small box case is computationally inexpensive enough to allow simulation on a finer mesh, enabling the results of the extrapolation to be validated in a weak sense. For both cases, it is found that while the sampling uncertainty is large enough to make the order of accuracy difficult to determine, the estimated discretization errors are quite small. This indicates that the commonly used heuristics provide adequate resolution for this class of problems. However, it is also found that, for some quantities, the discretization error is not small relative to sampling error, indicating that the conventional wisdom that sampling error dominates discretization error for this class of simulations needs to be reevaluated.

Oliver, Todd A.↗
DOE OSTI2014

Boundary between the thermal and statistical polarization regimes in a nuclear spin ensemble

As the number of spins in an ensemble is reduced, the statistical fluctuations in its polarization eventually exceed the mean thermal polarization. This transition has now been surpassed in a number of recent nuclear magnetic resonance experiments, which achieve nanometer-scale detection volumes. Here, we measure nanometer-scale ensembles of nuclear spins in a KPF{sub 6} sample using magnetic resonance force microscopy. In particular, we investigate the transition between regimes dominated by thermal and statistical nuclear polarization. The ratio between the two types of polarization provides a measure of the number of spins in the detected ensemble.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Statistical approach to nuclear level density

We discuss the level density in a finite many-body system with strong interaction between the constituents. Our primary object of applications is the atomic nucleus but the same techniques can be applied to other mesoscopic systems. We calculate and compare nuclear level densities for given quantum numbers obtained by different methods, such as nuclear shell model (the most successful microscopic approach), our main instrument - moments method (statistical approach), and Fermi-gas model; the calculation with the moments method can use any shell-model Hamiltonian excluding the spurious states of the center-of-mass motion. Our goal is to investigate statistical properties of nuclear level density, define its phenomenological parameters, and offer an affordable and reliable way of calculation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2014

Statistical analysis and modeling of intermittent transport events in the tokamak scrape-off layer

The turbulence observed in the scrape-off-layer of a tokamak is often characterized by intermittent events of bursty nature, a feature which raises concerns about the prediction of heat loads on the physical boundaries of the device. It appears thus necessary to delve into the statistical properties of turbulent physical fields such as density, electrostatic potential, and temperature, focusing on the mathematical expression of tails of the probability distribution functions. The method followed here is to generate statistical information from time-traces of the plasma density stemming from Braginskii-type fluid simulations and check this against a first-principles theoretical model. The analysis of the numerical simulations indicates that the probability distribution function of the intermittent process contains strong exponential tails, as predicted by the analytical theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Connes distance function on fuzzy sphere and the connection between geometry and statistics

An algorithm to compute Connes spectral distance, adaptable to the Hilbert-Schmidt operatorial formulation of non-commutative quantum mechanics, was developed earlier by introducing the appropriate spectral triple and used to compute infinitesimal distances in the Moyal plane, revealing a deep connection between geometry and statistics. In this paper, using the same algorithm, the Connes spectral distance has been calculated in the Hilbert-Schmidt operatorial formulation for the fuzzy sphere whose spatial coordinates satisfy the su(2) algebra. This has been computed for both the discrete and the Perelemov’s SU(2) coherent state. Here also, we get a connection between geometry and statistics which is shown by computing the infinitesimal distance between mixed states on the quantum Hilbert space of a particular fuzzy sphere, indexed by n ∈ ℤ/2.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Statistical properties of solar flares and coronal mass ejections through the solar cycle

Waiting Time Distributions (WTDs) of solar flares are investigated all through the solar cycle. The same approach applied to Coronal Mass Ejections (CMEs) in a previous work is considered here for flare occurrence. Our analysis reveals that flares and CMEs share some common statistical properties, which result dependent on the level of solar activity. Both flares and CMEs seem to independently occur during minimum solar activity phases, whilst their WTDs significantly deviate from a Poisson function at solar maximum, thus suggesting that these events are correlated. The characteristics of WTDs are constrained by the physical processes generating those eruptions associated with flares and CMEs. A scenario may be drawn in which different mechanisms are actively at work during different phases of the solar cycle. Stochastic processes, most likely related to random magnetic reconnections of the field lines, seem to play a key role during solar minimum periods. On the other hand, persistent processes, like sympathetic eruptions associated to the variability of the photospheric magnetism, are suggested to dominate during periods of high solar activity. Moreover, despite the similar statistical properties shown by flares and CMEs, as it was mentioned above, their WTDs appear different in some aspects. During solar minimum periods, the flare occurrence randomness seems to be more evident than for CMEs. Those persistent mechanisms generating interdependent events during maximum periods of solar activity can be suggested to play a more important role for CMEs than for flares, thus mitigating the competitive action of the random processes, which seem instead strong enough to weaken the correlations among flare event occurrence during solar minimum periods. However, it cannot be excluded that the physical processes at the basis of the origin of the temporal correlation between solar events are different for flares and CMEs, or that, more likely, more sophisticated effects are at work at the same time leading to an even more complex picture. This work represents a first step for further investigations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Application of image recognition algorithms for statistical description of nano- and microstructured surfaces

In this paper we propose a statistical approach for describing the self-assembling of sub-micronic polystyrene beads on silicon surfaces, as well as the evolution of surface topography due to plasma treatments. Algorithms for image recognition are used in conjunction with Scanning Electron Microscopy (SEM) imaging of surfaces. In a first step, greyscale images of the surface covered by the polystyrene beads are obtained. Further, an adaptive thresholding method was applied for obtaining binary images. The next step consisted in automatic identification of polystyrene beads dimensions, by using Hough transform algorithm, according to beads radius. In order to analyze the uniformity of the self–assembled polystyrene beads, the squared modulus of 2-dimensional Fast Fourier Transform (2- D FFT) was applied. By combining these algorithms we obtain a powerful and fast statistical tool for analysis of micro and nanomaterials with aspect features regularly distributed on surface upon SEM examination.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Path integral molecular dynamics for exact quantum statistics of multi-electronic-state systems

An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD), for quantum statistical mechanics when a single potential energy surface is involved. We first define an effective potential function that is numerically favorable for MES-PIMD and then derive corresponding estimators in MES-PIMD for evaluating various physical properties. Furthermore, its application to several representative one-dimensional and multi-dimensional models demonstrates that MES-PIMD in principle offers a practical tool in either of the diabatic and adiabatic representations for studying exact quantum statistics of complex/large MES systems when the Born-Oppenheimer approximation, Condon approximation, and harmonic bath approximation are broken.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Weak convergence to equilibrium of statistical ensembles in integrable Hamiltonian systems

This article explores the long-time behavior of the bounded orbits associated with an ensemble of initial conditions in a nondegenerate integrable Hamiltonian system. Such systems are inherently nonlinear and subject to highly regular phase space filamentation that can drive the ensemble of orbits toward a stationary state. Describing the statistical ensemble by a probability density on a neighborhood of a family of invariant tori, it is proved that the probability density describing the ensemble at time t converges weakly to an invariant density as t → ∞. More generally, we provide sufficient conditions for convergence to equilibrium of a multiphase system in action-angle form. These ideas are applied to an illustrative exactly soluble example. Finally, this work is relevant for understanding the statistical mechanics of integrable and near-integrable Hamiltonian systems

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Reconstruction of effective potential from statistical analysis of dynamic trajectories

The broad incorporation of microscopic methods is yielding a wealth of information on the atomic and mesoscale dynamics of individual atoms, molecules, and particles on surfaces and in open volumes. Analysis of such data necessitates statistical frameworks to convert observed dynamic behaviors to effective properties of materials. Here, we develop a method for the stochastic reconstruction of effective local potentials solely from observed structural data collected from molecular dynamics simulations (i.e., data analogous to those obtained via atomically resolved microscopies). Using the silicon vacancy defect in graphene as a model, we apply the statistical framework presented herein to reconstruct the free energy landscape from the calculated atomic displacements. Evidence of consistency between the reconstructed local potential and the trajectory data from which it was produced is presented, along with a quantitative assessment of the uncertainty in the inferred parameters.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Statistical data analysis of x-ray spectroscopy data enabled by neural network accelerated Bayesian inference

Bayesian inference applied to x-ray spectroscopy data analysis enables uncertainty quantification necessary to rigorously test theoretical models. However, when comparing to data, detailed atomic physics and radiation transfer calculations of x-ray emission from non-uniform plasma conditions are typically too slow to be performed in line with statistical sampling methods, such as Markov Chain Monte Carlo sampling. Furthermore, differences in transition energies and x-ray opacities often make direct comparisons between simulated and measured spectra unreliable. Here, we present a spectral decomposition method that allows for corrections to line positions and bound–bound opacities to best fit experimental data, with the goal of providing quantitative feedback to improve the underlying theoretical models and guide future experiments. In this work, we use a neural network (NN) surrogate model to replace spectral calculations of isobaric hot-spots created in Kr-doped implosions at the National Ignition Facility. The NN was trained on calculations of x-ray spectra using an isobaric hot-spot model post-processed with Cretin, a multi-species atomic kinetics and radiation code. The speedup provided by the NN model to generate x-ray emission spectra enables statistical analysis of parameterized models with sufficient detail to accurately represent the physical system and extract the plasma parameters of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Statistical characteristics of laser interference and its effect on IR optoelectronic observation systems

We consider statistical characteristics of laser interference recorded in the focal region of an IR optoelectronic observation system under field and out-of-field illumination by laser radiation. The applicability of the analytical description of experimental histograms of the laser interference signal distribution at the photodetector array output using the probability density approximations in the form of gamma distribution and the Gaussian function is substantiated. It is shown that the specific form of these functions is determined both by the mean value (mathematical expectation) of the interference signal and by the characteristic parameter M, which depends on the statistical properties of the laser interference. (laser applications and other issues in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Statistical mentoring at early training and career stages

At Los Alamos National Laboratory (LANL), statistical scientists develop solutions for a variety of national security challenges through scientific excellence, typically as members of interdisciplinary teams. At LANL, mentoring is actively encouraged and practiced to develop statistical skills and positive career-building behaviors. Mentoring activities targeted at different career phases from student to junior staff are an important catalyst for both short and long term career development. This article discusses mentoring strategies for undergraduate and graduate students through internships as well as for postdoctoral research associates and junior staff. Topics addressed include project selection, progress, and outcome; intellectual and social activities that complement the student internship experience; key skills/knowledge not typically obtained in academic training; and the impact of such internships on students’ careers. Experiences and strategies from a number of successful mentorships are presented. Feedback from former mentees obtained via a questionnaire is incorporated. As a result, these responses address some of the benefits the respondents received from mentoring, helpful contributions and advice from their mentors, key skills learned, and how mentoring impacted their later careers.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Information and Statistics in Nuclear Experiment and Theory (ISNET)

As with all empirical sciences, nuclear physics operates in the virtuous cycle of the scientific method: observations inspire theoretical models; models lead to new predictions; predictions are tested in experiments; experiments lead to new observations; and so on. Evaluating what we are inferring, and how certain we are of it, is key to this process. These requirements, and a general interest in applying novel statistical, mathematical, and computational techniques, led to the formation of a dedicated research community entitled “Information and Statistics in Nuclear Experiment and Theory (ISNET)” (https://isnet-series.github.io/), which now includes more than 300 members. While the community’s interests lean toward nuclear theory, the unifying theme for this group is the inference of knowledge from data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

MAPPING THE LOCAL HALO: STATISTICAL PARALLAX ANALYSIS OF SDSS LOW-MASS SUBDWARFS

We present a statistical parallax study of nearly 2000 M subdwarfs with photometry and spectroscopy from the Sloan Digital Sky Survey (SDSS). Statistical parallax analysis yields the mean absolute magnitudes, mean velocities, and velocity ellipsoids for homogenous samples of stars. We selected homogeneous groups of subdwarfs based on their photometric colors and spectral appearance. We examined the color-magnitude relations of low-mass subdwarfs and quantified their dependence on the newly refined metallicity parameter, {zeta}. We also developed a photometric metallicity parameter, {delta}{sub (g-r)}, based on the g - r and r - z colors of low-mass stars and used it to select stars with similar metallicities. The kinematics of low-mass subdwarfs as a function of color and metallicity were also examined and compared to main-sequence M dwarfs. We find that the SDSS subdwarfs share similar kinematics to the inner halo and thick disk. The color-magnitude relations derived in this analysis will be a powerful tool for identifying and characterizing low-mass metal-poor subdwarfs in future surveys such as Gaia and LSST, making them important and plentiful tracers of the stellar halo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

THE ABSOLUTE MAGNITUDE OF RRc VARIABLES FROM STATISTICAL PARALLAX

We present the first definitive measurement of the absolute magnitude of RR Lyrae c-type variable stars (RRc) determined purely from statistical parallax. We use a sample of 242 RRc variables selected from the All Sky Automated Survey for which high-quality light curves, photometry, and proper motions are available. We obtain high-resolution echelle spectra for these objects to determine radial velocities and abundances as part of the Carnegie RR Lyrae Survey. We find that M{sub V,RRc} = 0.59 ± 0.10 at a mean metallicity of [Fe/H] = –1.59. This is to be compared with previous estimates for RRab stars (M{sub V,RRab} = 0.76 ± 0.12) and the only direct measurement of an RRc absolute magnitude (RZ Cephei, M{sub V,RRc} = 0.27 ± 0.17). We find the bulk velocity of the halo relative to the Sun to be (W{sub π}, W{sub θ}, W{sub z} ) = (12.0, –209.9, 3.0) km s{sup –1} in the radial, rotational, and vertical directions with dispersions (σ{sub W{sub π}},σ{sub W{sub θ}},σ{sub W{sub z}}) = (150.4, 106.1, 96.0) km s{sup -1}. For the disk, we find (W{sub π}, W{sub θ}, W{sub z} ) = (13.0, –42.0, –27.3) km s{sup –1} relative to the Sun with dispersions (σ{sub W{sub π}},σ{sub W{sub θ}},σ{sub W{sub z}}) = (67.7,59.2,54.9) km s{sup -1}. Finally, as a byproduct of our statistical framework, we are able to demonstrate that UCAC2 proper-motion errors are significantly overestimated as verified by UCAC4.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The matryoshka run: A Eulerian refinement strategy to study the statistics of turbulence in virialized cosmic structures

We study the statistical properties of turbulence driven by structure formation in a massive merging galaxy cluster at redshift z = 0. The development of turbulence is ensured as the largest eddy turnover time is much shorter than the Hubble time independent of mass and redshift. We achieve a large dynamic range of spatial scales through a novel Eulerian refinement strategy where the cluster volume is refined with progressively finer uniform nested grids during gravitational collapse. This provides an unprecedented resolution of 7.3 h {sup –1} kpc across the virial volume. The probability density functions of various velocity-derived quantities exhibit the features characteristic of fully developed compressible turbulence observed in dedicated periodic-box simulations. Shocks generate only 60% of the total vorticity within the R {sub vir}/3 region and 40% beyond that. We compute second- and third-order longitudinal and transverse structure functions for both solenoidal and compressional components in the cluster core, virial region, and beyond. The structure functions exhibit a well-defined inertial range of turbulent cascade. The injection scale is comparable to the virial radius but increases toward the outskirts. Within R {sub vir}/3, the spectral slope of the solenoidal component is close to Kolmogorov's, but for the compressional component is substantially steeper and close to Burgers's; the flow is mostly solenoidal and statistically rigorously, which is consistent with fully developed homogeneous and isotropic turbulence. Small-scale anisotropy appears due to numerical artifact. Toward the virial region, the flow becomes increasingly compressional, the structure functions become flatter, and modest genuine anisotropy appear particularly close to the injection scale. In comparison, mesh adaptivity based on Lagrangian refinement and the same finest resolution leads to a lack of turbulent power on a small scales, an excess thereof on large scales, and unreliable density-weighted structure functions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

The statistical nature of the brightest group galaxies

We examine the statistical properties of the brightest group galaxies (BGGs) by using a complete spectroscopic sample of groups/clusters of galaxies selected from the Data Release 7 of the Sloan Digital Sky Survey. We test whether BGGs and other bright members of groups are consistent with an ordered population among the total population of group galaxies. We find that the luminosity distributions of BGGs do not follow the predictions from the order statistics (OS). The average luminosities of BGGs are systematically brighter than OS predictions. On the other hand, by properly taking into account the brightening effect of the BGGs, the luminosity distributions of the second brightest galaxies are in excellent agreement with the expectations of OS. The brightening of BGGs relative to the OS expectation is consistent with a scenario that the BGGs on average have overgrown about 20% masses relative to the other member galaxies. The growth (ΔM) is not stochastic but correlated with the magnitude gap (G {sub 1,} {sub 2}) between the brightest and the second brightest galaxy. The growth (ΔM) is larger for the groups having more prominent BGGs (larger G {sub 1,} {sub 2}) and averagely contributes about 30% of the final G {sub 1,} {sub 2} of the groups of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗