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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Complexity Induced Anisotropic Bimodal Intermittent Turbulence in Space Plasmas

The "physics of complexity" in space plasmas is the central theme of this exposition. It is demonstrated that the sporadic and localized interactions of magnetic coherent structures arising from the plasma resonances can be the source for the coexistence of nonpropagating spatiotemporal fluctuations and propagating modes. Non-Gaussian probability distribution functions of the intermittent fluctuations from direct numerical simulations are obtained and discussed. Power spectra and local intermittency measures using the wavelet analyses are presented to display the spottiness of the small-scale turbulent fluctuations and the non-uniformity of coarse-grained dissipation that can lead to magnetic topological reconfigurations. The technique of the dynamic renormalization group is applied to the study of the scaling properties of such type of multiscale fluctuations. Charged particle interactions with both the propagating and nonpropagating portions of the intermittent turbulence are also described.

Chang, Tom↗
NASA NTRS1996

Statistical Tolerance and Clearance Analysis for Assembly

Tolerance is inevitable because manufacturing exactly equal parts is known to be impossible. Furthermore, the specification of tolerances is an integral part of product design since tolerances directly affect the assemblability, functionality, manufacturability, and cost effectiveness of a product. In this paper, we present statistical tolerance and clearance analysis for the assembly. Our proposed work is expected to make the following contributions: (i) to help the designers to evaluate products for assemblability, (ii) to provide a new perspective to tolerance problems, and (iii) to provide a tolerance analysis tool which can be incorporated into a CAD or solid modeling system.

statistical tolerance clearance analysis Monte-Car↗
NASA NTRS2006

Development of a Nonlinear Probability of Collision Tool for the Earth Observing System

The Earth Observing System (EOS) spacecraft Terra, Aqua, and Aura fly in constellation with several other spacecraft in 705-kilometer mean altitude sun-synchronous orbits. All three spacecraft are operated by the Earth Science Mission Operations (ESMO) Project at Goddard Space Flight Center (GSFC). In 2004, the ESMO project began assessing the probability of collision of the EOS spacecraft with other space objects. In addition to conjunctions with high relative velocities, the collision assessment method for the EOS spacecraft must address conjunctions with low relative velocities during potential collisions between constellation members. Probability of Collision algorithms that are based on assumptions of high relative velocities and linear relative trajectories are not suitable for these situations; therefore an algorithm for handling the nonlinear relative trajectories was developed. This paper describes this algorithm and presents results from its validation for operational use. The probability of collision is typically calculated by integrating a Gaussian probability distribution over the volume swept out by a sphere representing the size of the space objects involved in the conjunction. This sphere is defined as the Hard Body Radius. With the assumption of linear relative trajectories, this volume is a cylinder, which translates into simple limits of integration for the probability calculation. For the case of nonlinear relative trajectories, the volume becomes a complex geometry. However, with an appropriate choice of coordinate systems, the new algorithm breaks down the complex geometry into a series of simple cylinders that have simple limits of integration. This nonlinear algorithm will be discussed in detail in the paper. The nonlinear Probability of Collision algorithm was first verified by showing that, when used in high relative velocity cases, it yields similar answers to existing high relative velocity linear relative trajectory algorithms. The comparison with the existing high velocity/linear theory will also be used to determine at what relative velocity the analysis should use the new nonlinear theory in place of the existing linear theory. The nonlinear algorithm was also compared to a known exact solution for the probability of collision between two objects when the relative motion is strictly circular and the error covariance is spherically symmetric. Figure I shows preliminary results from this comparison by plotting the probabilities calculated from the new algorithm and those from the exact solution versus the Hard Body Radius to Covariance ratio. These results show about 5% error when the Hard Body Radius is equal to one half the spherical covariance magnitude. The algorithm was then combined with a high fidelity orbit state and error covariance propagator into a useful tool for analyzing low relative velocity nonlinear relative trajectories. The high fidelity propagator is capable of using atmospheric drag, central body gravitational, solar radiation, and third body forces to provide accurate prediction of the relative trajectories and covariance evolution. The covariance propagator also includes a process noise model to ensure realistic evolutions of the error covariance. This paper will describe the integration of the nonlinear probability algorithm and the propagators into a useful collision assessment tool. Finally, a hypothetical case study involving a low relative velocity conjunction between members of the Earth Observation System constellation will be presented.

McKinley, David P.↗
NASA NTRS2014

AG Channel Measurement and Modeling Results for Over-Sea Conditions

This report describes results from flight tests conducted in an over-sea environment, for the purpose of characterizing the air-to-ground (AG) channel, for future unmanned aircraft system (UAS) communication system analysis and design. These results are for the first of a set of several flight tests conducted in different ground site (GS) environments. An ultimate aim of all these tests is the development of models for the AG channel that can be used in communication system evaluation. In this report we provide measured results for propagation path loss, root-mean square delay spread (RMS-DS), and the correlation coefficient of the primary received signal components on the four antennas (two antennas for C-band, two for L-band). For path loss, the curved-earth two-ray model provides a reasonable fit to the measured data, altered by several dB at the shortest link distances by aircraft antenna pattern effects. This two-ray model also accounts for the majority of measured RMS-DS results of a few tens of nanoseconds, except for the occasional intermittent reflections from surface objects. These intermittent reflections yield RMS-DS values up to several hundred nanoseconds. For portions of the flight path that were over a harbor area highly populated with boats, the channel was found to be more "continuously dispersive," with RMS-DS reaching approximately 250 ns. A separate model will be developed for this over-harbor setting. The correlation coefficient results are still undergoing analysis; preliminary observations are that correlation between signals on the same-band antennas is generally large (>0.6) for the C-band straight flight paths, whereas for the L-band signals and for the oval-shaped flight paths the correlation is generally small (below 0.4). Inter-band correlations are typically very small, and are well modeled as zero-mean Gaussian in distribution, with a standard deviation less than 0.2. Hence the over-sea channel effects in the two bands can be considered uncorrelated, which will allow for good diversity gains in dual-band systems. We describe initial modeling approaches for the over-sea channel; complete models for this and the over-harbor setting will appear in a subsequent report.

Aircraft Communications↗
NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan‐1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017, https://doi.org/10.1126/sciadv.1701471). The model reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U(sub 0) = 0.5 eV, U(sub W) = 0.078–0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

Tucker, O. J.↗
NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan-1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017). Themodel reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U(o) = 0.5eV, U(w) = 0.078 – 0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

O. J. Tucker↗
NASA NTRS2018

Solar Wind Implantation Into the Lunar Regolith: Monte Carlo Simulations of H Retention in a Surface With Defects and the H2 Exosphere

The solar wind implants protons into the top 20–30 nm of lunar regolith grains, and the implanted hydrogen will diffuse out of the regolith but also interact with oxygen in the regolith oxides. We apply a statistical approach to estimate the diffusion of hydrogen in the regolith hindered by forming temporary bonds with regolith oxygen atoms. A Monte Carlo simulation was used to track the temporal evolution of bound OH surface content and the H2 exosphere. The model results are consistent with the interpretation of the Chandrayaan‐1 M3 observations of infrared absorption spectra by surface hydroxyls as discussed in Li and Milliken (2017, https://doi.org/10.1126/sciadv.1701471). The model reproduced the latitudinal concentration of OH by using a Gaussian energy distribution of f(U0 = 0.5 eV, UW = 0.078–0.1 eV) to characterize the activation energy barrier to the diffusion of hydrogen in space weathered regolith. In addition, the model results of the exospheric content of H2 are consistent with observations by the Lyman Alpha Mapping Project on the Lunar Reconnaissance Orbiter. Therefore, we provide support for hydroxyl formation by chemically trapped solar wind protons.

O J Tucker↗
NASA NTRS2025

Time-Dependent Satellite Explosion Probabilities for Long-Term Orbital Debris Environment Modeling

On-orbit accidental explosions are a significant contributor to the growth of the orbital debris population. Certain types of satellites have been seen to exhibit different behaviors and timelines of explosions. Recent assessments of on-orbit explosions for three categories of satellites – Russian Sistema Obespecheniya Zapuska (SOZ, Proton 4th stage attitude and ullage motors) units, spacecraft, and rocket bodies – suggest that on-orbit explosions can be modeled using a continuous, time-dependent probability of explosion. This paper discusses the methodology for developing a time-dependent probability of explosion as a function of the satellite’s orbital lifetime based on historical explosions. The SOZ units are found to be best modeled by a modified Gaussian probability distribution, with the peak probability of explosion occurring around 10.4 years on-orbit. Spacecraft and rocket bodies both exhibit exponentially decaying explosion probabilities, with rocket bodies showing fast-, medium-, and slow-time modes of decay. Total cumulative probabilities of explosion are approximately 57% for SOZ units, 4% for spacecraft, and 2% for rocket bodies. Examples of implementation in a simulation of the orbital debris environment using NASA's long-term evolutionary model are given, showing the overall explosion behavior over two centuries is significantly different from that using a previously implemented constant-probability type-dependent explosion rate model and provides a better representation of the historical explosion record.

Alyssa P Manis↗
NASA NTRS2011

Transition from the Sector Zone to the Unipolar Zone in the Heliosheath: Voyager 2 Magnetic Field Observations

The magnetic polarity pattern observed by Voyager 2 (V2) evolved with time from a nearly equal mixture of positive and negative polarity sectors in the sector zone from 2007.00 to 2007.67 to nearly uniform positive polarity (magnetic fields directed away from the Sun) in the unipolar zone from 2009.6 to 2010.3. This change was caused by the decreasing latitudinal extent of the sector zone, when the minimum extent of the heliospheric current sheet moved northward toward the solar equator as the solar activity associated with solar cycle 23 decreased a minimum in 2010. In the heliosheath, the distribution of daily averages of the magnetic field strength B was lognormal in the sector zone from 2008.83 to 2009.57 and Gaussian in the unipolar zone from 2009.57 to 2010.27. The distribution of daily increments of B was a Tsallis distribution (q-Gaussian distribution) with q = 1.66 +/- 0.010 in the sector zone and . Gaussian (q = 1.01+/-0.29) in the unipolar zone. The unipolar region appears to be in a relatively undisturbed equilibrium state.

Burlaga, L. F.↗
DOE OSTI2020

Kepler Data Analysis: Non-Gaussian Noise and Fourier Gaussian Process Analysis of Stellar Variability

We develop a statistical analysis model of Kepler stellar flux data in the presence of planet transits, non-Gaussian noise, and stellar variability. We first develop a model for the Kepler noise probability distribution in the presence of outliers, which make the noise probability distribution non-Gaussian. We develop a signal likelihood analysis based on this probability distribution, in which we model the signal as a sum of the star variability and planetary transits. We argue that these components need to be modeled together if optimal signal is to be extracted from the data. For the stellar variability model we develop an optimal Gaussian process analysis using a Fourier-based Wiener filter approach, where the power spectrum is non-parametric and learned from the data. We develop high dimensional optimization of the objective function, where we jointly optimize all the model parameters, including thousands of star variability modes, and planet transit parameters. We apply the method to Kepler-90 data and show that it gives a better match to the stellar variability than the existing methods, and robustly handles noise outliers. As a consequence, the planet radii have a higher value than what the existing methods give, including splines and celerite.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Learning the temporal evolution of multivariate densities via normalizing flows

In this work, we propose a method to learn multivariate probability distributions using sample path data from stochastic differential equations. Specifically, we consider temporally evolving probability distributions (e.g., those produced by integrating local or nonlocal Fokker–Planck equations). Here, we analyze this evolution through machine learning assisted construction of a time-dependent mapping that takes a reference distribution (say, a Gaussian) to each and every instance of our evolving distribution. If the reference distribution is the initial condition of a Fokker–Planck equation, what we learn is the time-T map of the corresponding solution. Specifically, the learned map is a multivariate normalizing flow that deforms the support of the reference density to the support of each and every density snapshot in time. We demonstrate that this approach can approximate probability density function evolutions in time from observed sampled data for systems driven by both Brownian and Lévy noise. We present examples with two- and three-dimensional, uni- and multimodal distributions to validate the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

ORBITAL ANGULAR MOMENTUM BEAMS RESEARCH USING A FREE-ELECTRON LASER OSCILLATOR

Strong Hadron Cooling (SHC), utilizing the coherent electron cooling scheme, has been extensively investigated for the Electron Ion Collider (EIC). Throughout our cooling optimization studies, we realized that a Super-Gaussian electron bunch offers enhanced performance in comparison to a Gaussian bunch. Our approach involves initiating the electron beam distribution in a double peak form, transitioning them into a Super-Gaussian distribution due to the longitudinal space charge. Subsequently, a chicane within the linac section compresses the bunch to meet the required bunch length. We tuned a third harmonic cavity amplitude to reduce the nonlinear term of the chicane. Moreover, given the low initial current leading to a small but non-uniform slice energy spread, we evaluated utilizing laser heating techniques to achieve a uniformly distributed slice energy spread. In this report, we discuss the concepts and simulation results

Wang, E.↗
NASA NTRSDate not supplied

Characterizing Spatiotemporal Uncertainty in Interpolated Meteorological Data

Interpolated meteorological data invariably contain errors. These errors have structure in time and space, particularly autocorrelation, which can cause the effects of errors to compound when model outputs are aggregated temporally or spatially. One way to account for this uncertainty is with a probabilistic model from which samples can be drawn that are coherent with respect to underlying spatial and temporal covariance structure. This work describes a probabilistic method for spatial interpolation of point-wise meteorological time series. Observational data from weather stations are generally sparse in space and dense in time (but sometimes missing). The method works by projecting time series onto orthogonal basis vectors and spatially interpolating each resulting component independently. Under suitable assumptions, and data transformations to better satisfy those assumptions, Gaussian process regression provides a complete description of the joint predictive distribution over a Gaussian random field. Spatiotemporally coherent realizations are generated as the sum of conditional (spatial) simulations of each orthogonal (temporal) component. Data-derived and generic orthogonal bases are considered. In addition to spatial interpolation, imputation of missing observational data is examined. The method is applied using near-surface air temperature over the Western United States and validated by comparing theoretical versus actual coverage of predictive distributions and analyzing the degree to which spatial and temporal covariance structure is reproduced. Computational considerations, relating to conditional simulation of random fields, are also addressed.

Conor T Doherty↗
DOE OSTI2023

Maximum entropy distributions of dark matter in ΛCDM cosmology

Context. Small-scale challenges to ΛCDM cosmology require a deeper understanding of dark matter physics. Aims. This paper aims to develop the maximum entropy distributions for dark matter particle velocity (denoted by X ), speed (denoted by Z ), and energy (denoted by E ) that are especially relevant on small scales where system approaches full virialization. Methods. For systems involving long-range interactions, a spectrum of halos of different sizes is required to form to maximize system entropy. While the velocity in halos can be Gaussian, the velocity distribution throughout the entire system, involving all halos of different sizes, is non-Gaussian. With the virial theorem for mechanical equilibrium, we applied the maximum entropy principle to the statistical equilibrium of entire system, such that the maximum entropy distribution of velocity (the X distribution) could be analytically derived. The halo mass function was not required in this formulation, but it did indeed result from the maximum entropy. Results. The predicted X distribution involves a shape parameter α and a velocity scale, v 0 . The shape parameter α reflects the nature of force ( α → 0 for long-range force or α → ∞ for short-range force). Therefore, the distribution approaches Laplacian with α → 0 and Gaussian with α → ∞. For an intermediate value of α , the distribution naturally exhibits a Gaussian core for v ≪ v 0 and exponential wings for v ≫ v 0 , as confirmed by N -body simulations. From this distribution, the mean particle energy of all dark matter particles with a given speed, v , follows a parabolic scaling for low speeds (∝ v 2 for v ≪ v 0 in halo core region, i.e., “Newtonian”) and a linear scaling for high speeds (∝ v for v ≫ v 0 in halo outskirt, i.e., exhibiting “non-Newtonian” behavior due to long-range gravity). We compared our results against N -body simulations and found a good agreement.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1994

The response of the SSM/I to the marine environment. Part 2: A parameterization of the effect of the sea surface slope distribution on emission and reflection

Based on a geometric optics model and the assumption of an isotropic Gaussian surface slope distribution, the component of ocean surface microwave emissivity variation due to large-scale surface roughness is parameterized for the frequencies and approximate viewing angle of the Special Sensor Microwave/Imager. Independent geophysical variables in the parameterization are the effective (microwave frequency dependent) slope variance and the sea surface temperature. Using the same physical model, the change in the effective zenith angle of reflected sky radiation arising from large-scale roughness is also parameterized. Independent geophysical variables in this parameterization are the effective slope variance and the atmospheric optical depth at the frequency in question. Both of the above model-based parameterizations are intended for use in conjunction with empirical parameterizations relating effective slope variance and foam coverage to near-surface wind speed. These empirical parameterizations are the subject of a separate paper.

Petty, Grant W.↗
DOE OSTI2023

A simple, flexible technique for RF cavity wake-field calculations

It is typical in the accelerator field to model machine components, especially RF cavities, as parallel RLC resonators. In the interest of simulating and diagnosing beam instabilities, knowledge of the time-domain voltage waveform over an equivalent resonator by a bunch current often proves useful. This waveform may be found by convolving the bunch current with the RLC resonator impulse response. While analytical and quasi-analytical expressions are available in this regime for common distributions such as the Gaussian, analogous results for less standard distributions are difficult to obtain using direct methods, which opens the door for the development of a more generalized technique. In this paper, a formulation is created that allows for the simple computation of the time-domain voltage waveform of and RLC resonator. The formulation uses the Cauchy Residue Theorem to extract the convolution result from the Fourier Domain, and it only requires that the current distribution Fourier Transform be holomorphic and known at one specific evaluation point. This greatly simplifies the computation of the time domain voltage for a large amount of bunch distributions both common and uncommon.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Parametric description of intermittent probability distribution functions in solar wind and magnetohydrodynamic turbulence

ABSTRACT In this work, we find empirical evidence that the scale-dependent statistical properties of solar wind and magnetohydrodynamic (MHD) turbulence can be described in terms of a family of parametric probability distribution functions (PDFs) known as Normal Inverse Gaussian (NIG). Understanding these PDFs is one of the most important goals in turbulence theory, as they are inherently connected to the intermittent properties of solar wind turbulence. We investigate the properties of PDFs of Elsasser increments based on a large statistical sample from solar wind observations and high-resolution numerical simulations of MHD turbulence. In order to measure the PDFs and their corresponding properties, three experiments are presented: fast and slow solar wind for experimental data and a simulation of reduced MHD (RMHD) turbulence. Conditional statistics on a 23-yr-long sample of WIND data near 1 au and high-resolution pseudo-spectral simulation of steadily driven RMHD turbulence on a $2048^3$ mesh are used to construct scale-dependent PDFs. The empirical PDFs are fitted to NIG distributions, which depend on four free parameters. Our analysis shows that NIG distributions accurately capture the evolution of the PDFs, with scale-dependent parameters, from large scales characterized by a Gaussian distribution, turning to exponential tails within the inertial range and stretched exponentials at dissipative scales. We also show that empirically-measured NIG parameters exhibit well-defined scaling properties that are similar across the three empirical data sets, which may be indicative of universal behaviour.

Astronomy & Astrophysics↗
DOE OSTI2023

Deployment of Gaussian Surrogate Model for Ad-Hoc Adjustments to Elastic Scattering Angular Distributions [Slides]

This presentation is on the deployment of gaussian surrogate model for ad-hoc adjustments to elastic scattering angular distributions. Discussed throughout the presentation is motivation for this lecture. Specifically, the gaussian surrogate models, validation of method with Pb-208, and the application on Be-9 are highlighted. The presentation concludes with a summary.

97 MATHEMATICS AND COMPUTING↗