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NASA NTRS1987

Numerical simulations of collisions between rotating particles

Numerical simulations of Keplerian systems consisting of 200 mutually colliding rotating particles show that friction and surface irregularity reduce the equilibrium velocity dispersion and transfer some of the energy of random velocities to rotational velocities. The results confirm the theoretical predictions of Salo (1987). Simulations are performed for identical and different particle sizes, and for a power-law distribution of sizes. Taking rotation into account is not found to alter the previously observed Rayleigh distribution of eccentricities and inclinations, while the components of the rotational velocities are found to follow a Gaussian distribution. Application to the rarefied regions of Saturn's rings suggests that friction is able to reduce the equilibrium geometric thickness by about one-half.

Salo, H.↗

DOE OSTI2023

Single- and multi-photon-induced ultraviolet excitation and photodissociation of CH 3 I probed by coincident ion momentum imaging

The UV-induced photodissociation dynamics of iodomethane (CH 3 I) in its A-band are investigated by time-resolved coincident ion momentum imaging using strong-field ionization as a probe. The delay-dependent kinetic energy distribution of the photofragments resulting from double ionization of the molecule maps the cleavage of the carbon–iodine bond and shows how the existence of a potential well in the di-cationic potential energy surfaces shapes the observed distribution at small pump–probe delays. Furthermore, the competition between single- and multi-photon excitation and ionization of the molecule is studied as a function of the intensity of the UV-pump laser pulse. Two-photon excitation to Rydberg states is identified by tracking the transformation of the delay-dependent singly-charged iodomethane yield from a pure Gaussian distribution at low intensity to a Gaussian with an exponentially decaying tail at higher intensities. In conclusion, dissociative ionization induced by absorption of three UV photons is resolved as an additional delay-dependent feature in the kinetic energy of the fragment ions detected in coincidence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2005

Non-Gaussian Analysis of Turbulent Boundary Layer Fluctuating Pressure on Aircraft Skin Panels

The purpose of the study is to investigate the probability density function (PDF) of turbulent boundary layer fluctuating pressures measured on the outer sidewall of a supersonic transport aircraft and to approximate these PDFs by analytical models. Experimental flight results show that the fluctuating pressure PDFs differ from the Gaussian distribution even for standard smooth surface conditions. The PDF tails are wider and longer than those of the Gaussian model. For pressure fluctuations in front of forward-facing step discontinuities, deviations from the Gaussian model are more significant and the PDFs become asymmetrical. There is a certain spatial pattern of the skewness and kurtosis behavior depending on the distance upstream from the step. All characteristics related to non-Gaussian behavior are highly dependent upon the distance from the step and the step height, less dependent on aircraft speed, and not dependent on the fuselage location. A Hermite polynomial transform model and a piecewise-Gaussian model fit the flight data well both for the smooth and stepped conditions. The piecewise-Gaussian approximation can be additionally regarded for convenience in usage after the model is constructed.

Rizzi, Stephen A.↗

NASA NTRS1979

The correlation function for density perturbations in an expanding universe. IV - The evolution of the correlation function

The evolution of the two-point correlation function for the large-scale distribution of galaxies in an expanding universe is studied on the assumption that the perturbation densities lie in a Gaussian distribution centered on any given mass scale. The perturbations are evolved according to the Friedmann equation, and the correlation function for the resulting distribution of perturbations at the present epoch is calculated. It is found that: (1) the computed correlation function gives a satisfactory fit to the observed function in cosmological models with a density parameter (Omega) of approximately unity, provided that a certain free parameter is suitably adjusted; (2) the power-law slope in the nonlinear regime reflects the initial fluctuation spectrum, provided that the density profile of individual perturbations declines more rapidly than the -2.4 power of distance; and (3) both positive and negative contributions to the correlation function are predicted for cosmological models with Omega less than unity.

Mcclelland, J.↗

NASA NTRS1978

Response of defects to illumination in silicon solar cells

The enhancement of diffusion length with intensity was examined using spectral response measurements in solar cells based on Silso silicon and EFG silicon ribbon. Local diffusion length variations at defect sites were investigated as a function of illumination level using a scanning electron microscope operated in the electron beam induced current mode. An increase of diffusion length was observed at defect sites as the intensity level was increased. The diffusion length improvements are explained on the basis of saturation of minority carrier traps in these materials. The trap distribution in Silso silicon is shown to be peaked near (Ec - 0.7)eV. EFG silicon ribbon shows a broad, Gaussian distribution of traps located near (Ec - 0.5)eV.

Hari Rao, C. V.↗

NASA NTRS1994

Molecular Dynamics of a Water-Lipid Bilayer Interface

We present results of molecular dynamics simulations of a glycerol 1-monooleate bilayer in water. The total length of analyzed trajectories is 5ns. The calculated width of the bilayer agrees well with the experimentally measured value. The interior of the membrane is in a highly disordered fluid state. Atomic density profile, orientational and conformational distribution functions, and order parameters indicate that disorder increases toward the center of the bilayer. Analysis of out-of-plane thermal fluctuations of the bilayer surfaces occurring at the time scale of the present calculations reveals that the distribution of modes agrees with predictions of the capillary wave model. Fluctuations of both bilayer surfaces are uncorrelated, yielding Gaussian distribution of instantaneous widths of the membrane. Fluctuations of the width produce transient thinning defects in the bilayer which occasionally span almost half of the membrane. The leading mechanism of these fluctuations is the orientational and conformational motion of head groups rather than vertical motion of the whole molecules. Water considerably penetrates the head group region of the bilayer but not its hydrocarbon core. The total net excess dipole moment of the interfacial water points toward the aqueous phase, but the water polarization profile is non-monotonic. Both water and head groups significantly contribute to the surface potential across the interface. The calculated sign of the surface potential is in agreement with that from experimental measurements, but the value is markedly overestimated. The structural and electrical properties of the water-bilayer system are discussed in relation to membrane functions, in particular transport of ions and nonelectrolytes across membranes.

Wilson, Michael A.↗

NASA NTRS2013

Understanding How Kurtosis Is Transferred from Input Acceleration to Stress Response and Its Influence on Fatigue Llife

High cycle fatigue of metals typically occurs through long term exposure to time varying loads which, although modest in amplitude, give rise to microscopic cracks that can ultimately propagate to failure. The fatigue life of a component is primarily dependent on the stress amplitude response at critical failure locations. For most vibration tests, it is common to assume a Gaussian distribution of both the input acceleration and stress response. In real life, however, it is common to experience non-Gaussian acceleration input, and this can cause the response to be non-Gaussian. Examples of non-Gaussian loads include road irregularities such as potholes in the automotive world or turbulent boundary layer pressure fluctuations for the aerospace sector or more generally wind, wave or high amplitude acoustic loads. The paper first reviews some of the methods used to generate non-Gaussian excitation signals with a given power spectral density and kurtosis. The kurtosis of the response is examined once the signal is passed through a linear time invariant system. Finally an algorithm is presented that determines the output kurtosis based upon the input kurtosis, the input power spectral density and the frequency response function of the system. The algorithm is validated using numerical simulations. Direct applications of these results include improved fatigue life estimations and a method to accelerate shaker tests by generating high kurtosis, non-Gaussian drive signals.

Kihm, Frederic↗

NASA NTRS1993

Distributions of the Interplanetary Magnetic Field Revisite

The adequacy of the power spectrum to characterize the variations of a parameter depends on whether or not the parameter has a Gaussian distribution. We here perform very simple tests of Gaussianit on the distributions of the magnitudes of the interplanetary magnetic field, and on the distributions of the componentsi.e. we find the first four cumulants of the distributions (mean, variance, skewness and kurtosis).

pwer↗

DOE OSTI2021

Gaussian Kernel Methods for Seismic Fragility and Risk Assessment of Mid-Rise Buildings

Seismic fragility functions can be evaluated using the cloud analysis method with linear regression which makes three fundamental assumptions about the relation between structural response and seismic intensity: log-linear median relationship, constant standard deviation, and Gaussian distributed errors. While cloud analysis with linear regression is a popular method, the degree to which these individual and compounded assumptions affect the fragility and the risk of mid-rise buildings needs to be systematically studied. This paper conducts such a study considering three building archetypes that make up a bulk of the building stock: RC moment frame, steel moment frame, and wood shear wall. Gaussian kernel methods are employed to capture the data-driven variations in the median structural response and standard deviation and the distributions of residuals with the intensity level. With reference to the Gaussian kernels approach, it is found that while the linear regression assumptions may not affect the fragility functions of lower damage states, this conclusion does not hold for the higher damage states (such as the Complete state). In addition, the effects of linear regression assumptions on the seismic risk are evaluated. For predicting the demand hazard, it is found that the linear regression assumptions can impact the computed risk for larger structural response values. However, for predicting the loss hazard with downtime as the decision variable, linear regression can be considered adequate for all practical purposes.

58 GEOSCIENCES↗

DOE OSTI2025

Photometry of Outer Solar System Objects from the Dark Energy Survey. II. A Joint Analysis of Trans-Neptunian Absolute Magnitudes, Colors, Light Curves and Dynamics

For the 696 trans-Neptunian objects (TNOs) with absolute magnitudes 5.5 < H r < 8.2 detected in the Dark Energy Survey, we characterize the relationships between their dynamical state and physical properties—namely H r , indicating size; colors, indicating surface composition; and flux variation semiamplitude A, indicating asphericity and surface inhomogeneity. We seek “birth” physical distributions that can recreate these parameters in every dynamical class. We show that the observed colors of these TNOs are consistent with two Gaussian distributions in griz space, “near-infrared bright” (NIRB) and “near-infrared faint” (NIRF), presumably an inner and outer birth population, respectively. We find a model in which both the NIRB and NIRF H r and A distributions are independent of current dynamical states, supporting their assignment as birth populations. All objects are consistent with a common rolling p(H r ), but NIRF objects are significantly more variable. Cold classicals (CCs) are purely NIRF, while hot classical (HC), scattered, and detached TNOs are consistent with ≈ 70% NIRB and the resonance NIRB fractions show significant variation. The NIRB components of the HCs and of some resonances have broader inclination distributions than the NIRFs, i.e. their current dynamics retains information about birth location. We find evidence for radial stratification within the birth NIRB population, in that HC NIRBs are on average redder than detached or scattered NIRBs; a similar effect distinguishes CCs from other NIRFs. We estimate total object counts and masses of each class within our H r range. These results will strongly constrain models of the outer solar system.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Reynolds stress tensor measurements using magnetic resonance velocimetry: expansion of the dynamic measurement range and analysis of systematic measurement errors

This study presents magnetic resonance velocimetry (MRV) Reynolds Stress measurements in a periodic hill channel with a hill Reynolds number of Re = 29,500. The velocity encoding scheme is based on the ICOSA6 method with six icosahedral encoding directions and multiple encoding values are measured to increase the dynamic range. The full Reynolds stress tensor is obtained from a voxel-wise three-dimensional Gaussian fit using the magnitude data of all acquisitions. The MRV results are compared to a wall-resolved large eddy simulation and laser Doppler velocimetry measurements conducted in the same channel. It is shown that the MRV Reynolds stress data have excellent precision and agree qualitatively with the reference data. However, there are apparent systematic deviations. One of the most prominent error contributions is the signal attenuation caused by higher orders of motion, which leads to an overestimation of the turbulence level. Another fundamental error is identified in the assumption that the turbulence is Gaussian distributed. With the presented reconstruction technique, the MRV data are fitted to a statistical model, and depending on the examined flow setup, the Gaussian model can lead to considerable errors. Possible ways of how to reduce all identified errors are presented. In summary, this technique enables Reynolds stress tensor measurements in complex internal flows with high dynamic range and excellent precision. However, several issues need to be resolved to make the turbulence quantification more accurate.

42 ENGINEERING↗

NASA NTRS2012

Vandenberg Air Force Base Upper Level Wind Launch Weather Constraints

The 30th Operational Support Squadron Weather Flight (30 OSSWF) provides comprehensive weather services to the space program at Vandenberg Air Force Base (VAFB) in California. One of their responsibilities is to monitor upper-level winds to ensure safe launch operations of the Minuteman III ballistic missile. The 30 OSSWF tasked the Applied Meteorology Unit (AMU) to analyze VAFB sounding data with the goal of determining the probability of violating (PoV) their upper-level thresholds for wind speed and shear constraints specific to this launch vehicle, and to develop a tool that will calculate the PoV of each constraint on the day of launch. In order to calculate the probability of exceeding each constraint, the AMU collected and analyzed historical data from VAFB. The historical sounding data were retrieved from the National Oceanic and Atmospheric Administration Earth System Research Laboratory archive for the years 1994-2011 and then stratified into four sub-seasons: January-March, April-June, July-September, and October-December. The maximum wind speed and 1000-ft shear values for each sounding in each subseason were determined. To accurately calculate the PoV, the AMU determined the theoretical distributions that best fit the maximum wind speed and maximum shear datasets. Ultimately it was discovered that the maximum wind speeds follow a Gaussian distribution while the maximum shear values follow a lognormal distribution. These results were applied when calculating the averages and standard deviations needed for the historical and real-time PoV calculations. In addition to the requirements outlined in the original task plan, the AMU also included forecast sounding data from the Rapid Refresh model. This information provides further insight for the launch weather officers (LWOs) when determining if a wind constraint violation will occur over the next few hours on day of launch. The interactive graphical user interface (GUI) for this project was developed in Microsoft Excel using Visual Basic for Applications. The GUI displays the critical sounding data easily and quickly for the LWOs on day of launch. This tool will replace the existing one used by the 30 OSSWF, assist the LWOs in determining the probability of exceeding specific wind threshold values, and help to improve the overall upper winds forecast for the launch customer.

Shafer, Jaclyn A.↗

DOE OSTI2025

Solving high-dimensional inverse problems using amortized likelihood-free inference with noisy and incomplete data

Here, we present a likelihood-free probabilistic inversion method based on normalizing flows for high-dimensional inverse problems. The proposed method is composed of two complementary networks: a summary network for data compression and an inference network for parameter estimation. The summary network encodes raw observations into a fixed-size vector of summary features, while the inference network generates samples of the approximate posterior distribution of the model parameters based on these summary features. The posterior samples are produced in a deep generative fashion by sampling from a latent Gaussian distribution and passing these samples through an invertible transformation. We construct this invertible transformation by sequentially alternating conditional invertible neural network and conditional neural spline flow layers. The summary and inference networks are trained simultaneously. We apply the proposed method to an inversion problem in groundwater hydrology to estimate the posterior distribution of the log-conductivity field conditioned on spatially sparse time-series observations of the system’s hydraulic head responses. The conductivity field is represented with 706 degrees of freedom in the considered problem. Comparison with the likelihood-based iterative ensemble smoother PEST-IES method demonstrates that the proposed method accurately estimates the parameter posterior distribution and the observations’ predictive posterior distribution at a fraction of the inference time of PEST-IES.

conditional invertible neural network↗

NASA NTRS1994

Resolution requirements for velocity gradients in turbulence

Since high resolution numerical simulations of turbulent flows, or experiments at high Reynolds numbers, represent a substantial investment in resources, the estimation of the minimum resolution required for the study of a given property has been the subject of continued interest. Different properties require, in general, different resolutions, and the present paper is dedicated to the requirements for the measurement of the probability distribution functions of the velocity gradients and, in particular, of their low order moments. The deviation of these quantities from the values corresponding to a Gaussian distribution was one of the first indications of the presence of Reynolds number-dependent intermittency and has been the object of recent interest as numerical simulations have become able to explore the distribution of gradients in the low Reynolds number range, while new experiments have extended the range to increasingly high Reynolds numbers. We will use progressive filtering of the results of numerical simulations of isotropic turbulence as a model for the effect of a sensor of finite size. The numerical issues will be addressed first to ensure that the simulations are fully resolved from the point of view of the velocity gradients. This will also give us an estimate for the numerical resolution required for the different quantities.

Jimenez, Javier↗

DOE OSTI2021

Xenon implantation of nanodiamond films for targeted color center emission at sub-nanosecond time scales

In this work, the lifetime of nitrogen-vacancy color centers within nanodiamonds is reduced from 550±13 ps to 297±10 ps through the implantation of xenon. Coupled-mode analysis is employed to characterize the mechanism responsible for the reduction in emission lifetime. The observed spectral lineshape is found to be consistent with a Voigt profile consisting of two Lorentzian resonant peaks at 637 nm and 811 nm that are inhomogeneously broadened by a Gaussian distribution. A convolution of the frequency-domain Lorentzian output, with linewidths less than 1 nm, from the coupled-mode system of equations with a Gaussian with standard deviation of 85 nm is performed to generate the Voigt profile. The shortened emission lifetime is found to be consistent with a coupled mode theory model incorporating coupling between nitrogen-vacancy and xenon-vacancy color centers.

36 MATERIALS SCIENCE↗

NASA NTRS1972

Input noise approximation in tracker modeling

The validity of approximating random Gaussian distributed inputs used in human response modeling by sums of discrete sine waves is studied. An ideal rectangular power density spectrum is simulated using both filtered Gaussian white noise and sums-of-discrete sine waves with three different input cutoff frequencies in the same compensatory tracking task. Resulting normalized tracking error and quality operator observations are used to investigate apparent discrepancies in human operator characteristics. Results show that discrete and continuous input tracking data compare favorable when the power in the crossover region is taken into account.

Torrey, P. F.↗

NASA NTRS1986

Simulated laser fluorosensor signals from subsurface chlorophyll distributions

A semianalytic Monte Carlo model has been used to simulate laser fluorosensor signals returned from subsurface distributions of chlorophyll. This study assumes the only constituent of the ocean medium is the common coastal zone dinoflagellate Prorocentrum minimum. The concentration is represented by Gaussian distributions in which the location of the distribution maximum and the standard deviation are variable. Most of the qualitative features observed in the fluorescence signal for total chlorophyll concentrations up to 1.0 microg/liter can be accounted for with a simple analytic solution assuming a rectangular chlorophyll distribution function.

Venable, D. D.↗