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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.↗

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↗

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.↗

NASA NTRS1972

On the application of Rice's exceedance statistics to atmospheric turbulence.

Discrepancies produced by the application of Rice's exceedance statistics to atmospheric turbulence are examined. First- and second-order densities from several data sources have been measured for this purpose. Particular care was paid to each selection of turbulence that provides stationary mean and variance over the entire segment. Results show that even for a stationary segment of turbulence, the process is still highly non-Gaussian, in spite of a Gaussian appearance for its first-order distribution. Data also indicate strongly non-Gaussian second-order distributions. It is therefore concluded that even stationary atmospheric turbulence with a normal first-order distribution cannot be considered a Gaussian process, and consequently the application of Rice's exceedance statistics should be approached with caution.

Chen, W. Y.↗

NASA NTRS1993

Kurtosis, skewness, and non-Gaussian cosmological density perturbations

Cosmological topological defects as well as some nonstandard inflation models can give rise to non-Gaussian density perturbations. Skewness and kurtosis are the third and fourth moments that measure the deviation of a distribution from a Gaussian. Measurement of these moments for the cosmological density field and for the microwave background temperature anisotropy can provide a test of the Gaussian nature of the primordial fluctuation spectrum. In the case of the density field, the importance of measuring the kurtosis is stressed since it will be preserved through the weakly nonlinear gravitational evolution epoch. Current constraints on skewness and kurtosis of primeval perturbations are obtained from the observed density contrast on small scales and from recent COBE observations of temperature anisotropies on large scales. It is also shown how, in principle, future microwave anisotropy experiments might be able to reveal the initial skewness and kurtosis. It is shown that present data argue that if the initial spectrum is adiabatic, then it is probably Gaussian, but non-Gaussian isocurvature fluctuations are still allowed, and these are what topological defects provide.

Luo, Xiaochun↗

NASA NTRS1983

Approximation to the Probability Density at the Output of a Photmultiplier Tube

The probability density of the integrated output of a photomultiplier tube (PMT) is approximated by the Gaussian, Rayleigh, and Gamma probability densities. The accuracy of the approximations depends on the signal energy alpha: the Gamma distribution is accurate for all alpha, the Raleigh distribution is accurate for small alpha (approximate or less than 1 photon) and the Gaussian distribution is accurate for large alpha (approximate or greater than 10 photons).

Stokey, R. J.↗

NASA NTRS1994

Skewness in large-scale structure and non-Gaussian initial conditions

We compute the skewness of the galaxy distribution arising from the nonlinear evolution of arbitrary non-Gaussian intial conditions to second order in perturbation theory including the effects of nonlinear biasing. The result contains a term identical to that for a Gaussian initial distribution plus terms which depend on the skewness and kurtosis of the initial conditions. The results are model dependent; we present calculations for several toy models. At late times, the leading contribution from the initial skewness decays away relative to the other terms and becomes increasingly unimportant, but the contribution from initial kurtosis, previously overlooked, has the same time dependence as the Gaussian terms. Observations of a linear dependence of the normalized skewness on the rms density fluctuation therefore do not necessarily rule out initially non-Gaussian models. We also show that with non-Gaussian initial conditions the first correction to linear theory for the mean square density fluctuation is larger than for Gaussian models.

Fry, J. N.↗

NASA NTRS1978

Efficiency degradation due to tracking errors for point focusing solar collectors

An important parameter in the design of point focusing solar collectors is the intercept factor which is a measure of efficiency and of energy available for use in the receiver. Using statistical methods, an expression of the expected value of the intercept factor is derived for various configurations and control law implementations. The analysis assumes that a radially symmetric flux distribution (not necessarily Gaussian) is generated at the focal plane due to the sun's finite image and various reflector errors. The time-varying tracking errors are assumed to be uniformly distributed within the threshold limits and allows the expected value calculation.

Hughes, R. O.↗

NASA NTRS1986

Statistics of density maxima and the large-scale matter distribution

High peaks in Gaussian noise display enhanced clustering. The enhancement takes two forms: on large scales one obtains a linear amplification of the correlation function which is independent of scale. On smaller scales, but larger than the mass scale of the peaks themselves, a nonlinear (exponential) enhancement of the number density of high peaks in overdense regions arises. The large-scale correlations of Abell's rich clusters can be understood as a manifestation of this phenomenon. If the formation of bright galaxies favors the high overdensity peaks then the number of galaxies (per unit mass) in clusters and groups may be considerably enhanced. Consequences of these ideas for the density parameter and the large-scale matter distribution are discussed.

Kaiser, N.↗

NASA NTRS2012

Emperical Tests of Acceptance Sampling Plans

Acceptance sampling is a quality control procedure applied as an alternative to 100% inspection. A random sample of items is drawn from a lot to determine the fraction of items which have a required quality characteristic. Both the number of items to be inspected and the criterion for determining conformance of the lot to the requirement are given by an appropriate sampling plan with specified risks of Type I and Type II sampling errors. In this paper, we present the results of empirical tests of the accuracy of selected sampling plans reported in the literature. These plans are for measureable quality characteristics which are known have either binomial, exponential, normal, gamma, Weibull, inverse Gaussian, or Poisson distributions. In the main, results support the accepted wisdom that variables acceptance plans are superior to attributes (binomial) acceptance plans, in the sense that these provide comparable protection against risks at reduced sampling cost. For the Gaussian and Weibull plans, however, there are ranges of the shape parameters for which the required sample sizes are in fact larger than the corresponding attributes plans, dramatically so for instances of large skew. Tests further confirm that the published inverse-Gaussian (IG) plan is flawed, as reported by White and Johnson (2011).

White, K. Preston, Jr.↗

NASA NTRS2011

On the Response of a Nonlinear Structure to High Kurtosis Non-Gaussian Random Loadings

This paper is a follow-on to recent work by the authors in which the response and high-cycle fatigue of a nonlinear structure subject to non-Gaussian loadings was found to vary markedly depending on the nature of the loading. There it was found that a non-Gaussian loading having a steady rate of short-duration, high-excursion peaks produced essentially the same response as would have been incurred by a Gaussian loading. In contrast, a non-Gaussian loading having the same kurtosis, but with bursts of high-excursion peaks was found to elicit a much greater response. This work is meant to answer the question of when consideration of a loading probability distribution other than Gaussian is important. The approach entailed nonlinear numerical simulation of a beam structure under Gaussian and non-Gaussian random excitations. Whether the structure responded in a Gaussian or non-Gaussian manner was determined by adherence to, or violations of, the Central Limit Theorem. Over a practical range of damping, it was found that the linear response to a non-Gaussian loading was Gaussian when the period of the system impulse response is much greater than the rate of peaks in the loading. Lower damping reduced the kurtosis, but only when the linear response was non-Gaussian. In the nonlinear regime, the response was found to be non-Gaussian for all loadings. The effect of a spring-hardening type of nonlinearity was found to limit extreme values and thereby lower the kurtosis relative to the linear response regime. In this case, lower damping gave rise to greater nonlinearity, resulting in lower kurtosis than a higher level of damping.

Rizzi, Stephen A.↗

NASA NTRS1993

Physics of debris clouds from hypervelocity impacts

The protection scheme developed for long duration space platforms relies primarily upon placing thin metal plates or 'bumpers' around flight critical components. The effectiveness of this system is highly dependent upon its ability to break up and redistribute the momentum of any particle which might otherwise strike the outer surface of the spacecraft. Therefore it is of critical importance to design the bumpers such that maximum dispersion of momentum is achieved. This report is devoted to an in-depth study into the design and development of a laboratory instrument which would permit the in-situ monitoring of the momentum distribution as the impact event occurs. A series of four designs were developed, constructed and tested culminating with the working instrument which is currently in use. Each design was individually tested using the Space Environmental Effects Facility (SEEF) at the Marshall Space Flight Center in Huntsville, Alabama. Along with the development of the device, an experimental procedure was developed to assist in the investigation of various bumper materials and designs at the SEEF. Preliminary results were used to compute data which otherwise were not experimentally obtainable. These results were shown to be in relative agreement with previously obtained values derived through other methods. The results of this investigation indicated that momentum distribution could in fact be measured in-situ as the impact event occurred thus giving a more accurate determination of the effects of experimental parameters on the momentum spread. Data produced by the instrument indicated a Gaussian-type momentum distribution. A second apparatus was developed and it was placed before the shield in the line of travel utilized a plate to collect impact debris scattered backwards. This plate had a passage hole in the center to allow the particle to travel through it and impact the proposed shield material. Applying the law of conservation of angular momentum a backward momentum vector was determined from the angular velocity of the plate. The forward scattered and backward scattered momentum values were then analyzed to judge the distribution of debris. Loss of momentum was attributed to the inaccuracies of the means of measurement. Assumptions of symmetrical debris for the forward and backward scattered directions also contributed to this loss.

Zee, Ralph↗

NASA NTRS1983

Spectral characteristics of the return

Doppler spectra of VHF radar returns typically indicate a Gaussian back-ground shape with superimposed spikes. An average of 10 Doppler spectra are shown which are calculated from a time series of seven min of complex data. A proper Gaussian fit to the background distribution is possible by neglecting the strong amplitude spikes. If this background distribution is due to beam width broadening, either diffuse reflection or rather isotropic scattering is required. If beam width broadening is neglected, the width of the distribution is given by turbulent velocity fluctuations. The reflected component is about 1/3 of the scattered component. It is assumed that the amplitude spikes due to diffuse reflection indicate a Gaussian frequency distribution such as for the amplitudes due to scattering.

Rottger, J.↗

NASA NTRS1980

An experimental study of the surface elevation probability distribution and statistics of wind-generated waves

Laboratory experiments were performed to measure the surface elevation probability density function and associated statistical properties for a wind-generated wave field. The laboratory data along with some limited field data were compared. The statistical properties of the surface elevation were processed for comparison with the results derived from the Longuet-Higgins (1963) theory. It is found that, even for the highly non-Gaussian cases, the distribution function proposed by Longuet-Higgins still gives good approximations.

Huang, N. E.↗

NASA NTRS1982

A study of the feasibility of statistical analysis of airport performance simulation

The feasibility of conducting a statistical analysis of simulation experiments to study airport capacity is investigated. First, the form of the distribution of airport capacity is studied. Since the distribution is non-Gaussian, it is important to determine the effect of this distribution on standard analysis of variance techniques and power calculations. Next, power computations are made in order to determine how economic simulation experiments would be if they are designed to detect capacity changes from condition to condition. Many of the conclusions drawn are results of Monte-Carlo techniques.

Myers, R. H.↗

NASA NTRS1986

Study of the ammonia ice cloud layer in the north tropical zone of Jupiter from the infrared interferometric experiment on Voyager

An average of 51 Voyager 1 IRIS spectra of Jupiter's North Tropical Zone was analyzed to infer the abundance, vertical extent, and size distribution of the particles making up the ammonia cloud in this region. It is assumed that the cloud base coincides with the level at which 100% saturation of ammonia vapor occurs. The vertical distribution of particulates above this level is determined by assuming a constant total ammonia mixing ratio and adjusting the two phases so that the vapor is saturated throughout the cloud. A constant scaling factor then adjusts the base number density. A radiative transfer program is used that includes the effects of absorption and emission of all relevant gases as well as anisotropic scattering by cloud particles. Mie scattering from a gaussian particle size distribution is assumed. The vertical thermal structure is inferred from a temperature retrieval program that utilizes the collision induced S(0) and S(1) molecular hydrogen lines between 300 and 700.cm, and the 1304.cm methane band.

Shaffer, William A.↗