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At least 1,441 records · Page 80

Spatial aspects of low- and medium-energy electron degradation in N2

Spatial (radial and longitudinal) yield spectra for electron energy degradation in molecular nitrogen gas for 25-eV to 10-keV incident electrons have been generated by using a Monte Carlo technique. These spatial yield spectra associated with the electron degradation process can be employed to calculate a 'yield' for any inelastic state at any position in the medium. These have been analytically represented in terms of a model containing three simple 'microplumes'. Five-dimensional yield spectra which contain the information about the polar angle of the electron have also been analytically represented within the framework of the microplume model. Aeronomical and radiological applications of our model are discussed.

Singhal, R. F.↗

Rates for neutron-capture reactions on tungsten isotopes in iron meteorites

High-precision W isotopic analyses by Harper and Jacobsen indicate the W-182/W-183 ratio in the Toluca iron meteorite is shifted by -(3.0 +/- 0.9) x 10(exp -4) relative to a terrestrial standard. Possible causes of this shift are neutron-capture reactions on W during Toluca's approximately 600-Ma exposure to cosmic ray particles or radiogenic growth of W-182 from 9-Ma Hf-182 in the silicate portion of the Earth after removal of W to the Earth's core. Calculations for the rates of neutron-capture reactions on W isotopes were done to study the first possibility. The LAHET Code System (LCS) which consists of the Los Alamos High Energy Transport (LAHET) code and the Monte Carlo N-Particle(MCNP) transport code was used to numerically simulate the irradiation of the Toluca iron meteorite by galactic-cosmic-ray (GCR) particles and to calculate the rates of W(n, gamma) reactions. Toluca was modeled as a 3.9-m-radius sphere with the composition of a typical IA iron meteorite. The incident GCR protons and their interactions were modeled with LAHET, which also handled the interactions of neutrons with energies above 20 MeV. The rates for the capture of neutrons by W-182, W-183, and W-186 were calculated using the detailed library of (n, gamma) cross sections in MCNP. For this study of the possible effect of W(n, gamma) reactions on W isotope systematics, we consider the peak rates. The calculated maximum change in the normalized W-182/W-183 ratio due to neutron-capture reactions cannot account for more than 25% of the mass 182 deficit observed in Toluca W.

Masarik, J.↗

Conflict Probability Estimation for Free Flight

The safety and efficiency of free flight will benefit from automated conflict prediction and resolution advisories. Conflict prediction is based on trajectory prediction and is less certain the farther in advance the prediction, however. An estimate is therefore needed of the probability that a conflict will occur, given a pair of predicted trajectories and their levels of uncertainty. A method is developed in this paper to estimate that conflict probability. The trajectory prediction errors are modeled as normally distributed, and the two error covariances for an aircraft pair are combined into a single equivalent covariance of the relative position. A coordinate transformation is then used to derive an analytical solution. Numerical examples and Monte Carlo validation are presented.

Paielli, Russell A.↗

Behavior of Filters and Smoothers for Strongly Nonlinear Dynamics

The Kalman filter is the optimal filter in the presence of known gaussian error statistics and linear dynamics. Filter extension to nonlinear dynamics is non trivial in the sense of appropriately representing high order moments of the statistics. Monte Carlo, ensemble-based, methods have been advocated as the methodology for representing high order moments without any questionable closure assumptions. Investigation along these lines has been conducted for highly idealized dynamics such as the strongly nonlinear Lorenz model as well as more realistic models of the means and atmosphere. A few relevant issues in this context are related to the necessary number of ensemble members to properly represent the error statistics and, the necessary modifications in the usual filter situations to allow for correct update of the ensemble members. The ensemble technique has also been applied to the problem of smoothing for which similar questions apply. Ensemble smoother examples, however, seem to be quite puzzling in that results state estimates are worse than for their filter analogue. In this study, we use concepts in probability theory to revisit the ensemble methodology for filtering and smoothing in data assimilation. We use the Lorenz model to test and compare the behavior of a variety of implementations of ensemble filters. We also implement ensemble smoothers that are able to perform better than their filter counterparts. A discussion of feasibility of these techniques to large data assimilation problems will be given at the time of the conference.

Zhu, Yanqui↗

Separating Gravitational Wave Signals from Instrument Artifacts

Central to the gravitational wave detection problem is the challenge of separating features in the data produced by astrophysical sources from features produced by the detector. Matched filtering provides an optimal solution for Gaussian noise, but in practice, transient noise excursions or "glitches" complicate the analysis. Detector diagnostics and coincidence tests can be used to veto many glitches which may otherwise be misinterpreted as gravitational wave signals. The glitches that remain can lead to long tails in the matched filter search statistics and drive up the detection threshold. Here we describe a Bayesian approach that incorporates a more realistic model for the instrument noise allowing for fluctuating noise levels that vary independently across frequency bands, and deterministic "glitch fitting" using wavelets as "glitch templates", the number of which is determined by a trans-dimensional Markov chain Monte Carlo algorithm. We demonstrate the method's effectiveness on simulated data containing low amplitude gravitational wave signals from inspiraling binary black hole systems, and simulated non-stationary and non-Gaussian noise comprised of a Gaussian component with the standard LIGO/Virgo spectrum, and injected glitches of various amplitude, prevalence, and variety. Glitch fitting allows us to detect significantly weaker signals than standard techniques.

Littenberg, Tyson B.↗

Models of the hard X-ray spectrum of AM Herculis and implications for the accretion rate

Phenomenological fits to the hard X-ray spectrum of AM Hercules have failed to explain the high equivalent width (0.8 + or - 0.1 keV) of Fe K-alpha emission. The scattering and fluorescent line production in a cold or partially ionized accretion column of hard X-rays emitted at the base are investigated using the Monte Carlo method. It is shown that the Fe emission equivalent width observed in the spectrum of AM Her can be explained without resorting to an overabundance of Fe in the accreting material. For sufficient optical depth across the accretion column, equivalent widths of K-alpha emission even larger than the observed values can be obtained. The accretion rate and gravitational power can be deduced from the optical depth across the column, if the column size is known, and, together with the observed hard X-ray and polarized light luminosities, imply a lower limit for the luminosity in the UV to soft X-ray range, for which the observations give model-dependent values.

Swank, J. H.↗

Simplified Worst-Case Analysis of Complex Systems

Statistical method avoids excessive computer time. Technique involves simplified Monte Carlo simulation of system with randomly chosen parameters and comparison of tolerance extremes of several of worst-case situations found. Resulting combination of tolerance extremes then used in detailed analysis - one that makes use of full complex nonlinear model capable of accurate simulations.

Pond, C. L.↗

Probalistic structural analysis methods for select space propulsion system structural components

A summary of the status of this five-year project which is now in its third year of research and development is presented. The goal of the project is the development of several methodologies for probabilistic structural modeling. Probabilistic structural modeling consists of stochastic models of material properties, part geometries, boundary conditions, as well as loading conditions. The current presentation focuses on one methodology - coupling of an advanced finite element structural analysis code with probabilistic modeling strategies. The essential algorithm developments for combining the finite element and probabilistic analysis methods are reported. The validity of the resulting probabilistic structural analysis method is confirmed through a series of test problems with exact results based on Monte Carlo simulations. Additionally, the applicability of the method to a Space Propulsion System (a turbine blade) is demonstrated for static stresses.

Cruse, T. A.↗

Decoupled predictions of radiative heating in air using a particle simulation method

A particle simulation technique with decoupled radiation is used to estimate the radiative emission along the stagnation streamline and the radiative heating at the stagnation point of a blunt-nosed vehicle entering the earth's atmosphere at hypersonic speed. The direct simulation Monte Carlo (DSMC) method is used to compute the fluid mechanics of the weakly ionized flow. The radiative emission is computed using the NEQAIR computer code with the radiation decoupled from the flowfield solution. It is concluded that the new models make it possible to decrease the predicted total radiative heating at the stagnation point of the vehicle by a factor of 15. A comparison of the DSMC approach with a continuum flow model shows that the total predicted radiative heating estimates agree within a factor of 2.

Boyd, Iain D.↗

Properties of a B0 I stellar wind and interstellar grains derived from Ginga observations of the binary X-ray pulsar 4U 1538-52

From measurements of the X-ray eclipse phenomena of the binary X-ray pulsar 4U 1538-52, we derive properties of the stellar wind of its B0 I companion, QV Nor, and a constraint on models of interstellar grains. Estimates of the wind density as a function of the distance from the center of QV Nor are obtained from an analysis of the variation of X-ray attenuation during an eclipse egress. A Monte Carlo computation of the absorption and scattering of X-rays in the X-ray-ionized wind accounts for approximately two-thirds of the spectrum of X-rays with energies above 4.5 keV observed during the eclipse. Our upper limit on R(sub XV) is 0.06/mag, which implies that the X-ray scattering efficiency of interstellar dust is less than expected for solid grains with a size distribution of the form n(sub g)(a) approximately a(exp -3.5) in the range from 0.005 to 0.25 microns and composed of silicate (R(sub XV) = 0.22/mag) or a silicate-graphite mixture (R(sub XV) = 0.11/mag) as derived from the calculations of Martin & Rouleau (1991). This lends support to the idea (Mathis & Whiffen 1989) that interstellar grains are 'fluffy' aggregates with an average bulk density less than that of their constitutent particles. Such aggregates would have a smaller ratio of X-ray scattering efficiency to optical extinction efficiency compared with solid grains of the same material.

Clark, George W.↗

Ultraviolet Galaxy Counts From STIS Observations of The Hubble Deep Fields

We present galaxy counts in the near and far ultraviolet (NUV and FUV) obtained from Space Telescope Imaging Spectrograph (STIS) observations of portions of the Hubble Deep Field North, (HDFN), the Hubble Deep Field South, (HDFS) and a parallel field near the HDFN. All three fields have deep (AB>29) optical imaging, and we determine magnitudes by taking the ultraviolet flux detected within the limiting optical isophote. An analysis of the UV-optical colors of detected objects, combined with a visual inspection of the UV images, indicates that there are no detectable objects in the UV images which are not also detected in the optical. We measure the detection area and completeness as a function of magnitude by taking the size-magnitude distribution of galaxies in the entire HDFN WFPC2 V+I image, applying the measured UV-optical colors from the detected galaxies, and determining the total area over which each galaxy would have been detected in the UV images. The average area for the simulated galaxies in each UV magnitude bin, (including galaxies which would not be detected at all), provides the effective area and completeness for the bin. We test this procedure with Monte Carlo simulations. The galaxy counts reach to AB=29 in both the NUV and FUV; 1 magnitude fainter than the HDF F30OW counts, and 7 magnitudes fainter than balloon-based counts. We compare our measured counts to various models.

Gardner, J. P.↗

Simulation of TGF-Beta Activation by Low-Dose HZE Radiation in a Cell Culture

High charge (Z) and energy (E) (HZE) nuclei comprised in the galactic cosmic rays are main contributors to space radiation risk. They induce many lesions in living matter such as non-specific oxidative damage and the double-strand breaks (DSBs), which are considered key precursors of early and late effects of radiation. There is increasing evidence that cells respond collectively rather than individually to radiation, suggesting the importance of cell signaling1. The transforming growth factor (TGF ) is a signaling peptide that is expressed in nearly all cell type and regulates a large array of cellular processes2. TGF have been shown to mediate cellular response to DNA damage3 and to induce apoptosis in non-irradiated cells cocultured with irradiated cells4. TFG molecules are secreted by cells in an inactive complex known as the latency-associated peptide (LAP). TGF is released from the LAP by a conformational change triggered by proteases, thrombospondin-1, integrins, acidic conditions and .OH radical5. TGF then binds to cells receptors and activates a cascade of events mediated by Smad proteins6, which might interfere with the repair of DNA. Meanwhile, increasingly sophisticated Brownian Dynamics (BD) algorithms have appeared recently in the literature7 and can be applied to study the interaction of molecules with receptors. These BD computer models have contributed to the elucidation of signal transduction, ligand accumulation and autocrine loops in the epidermal growth factor (EGF) and its receptor (EFGR) system8. To investigate the possible roles of TGF in an irradiated cell culture, our Monte-Carlo simulation codes of the radiation track structure9 will be used to calculate the activation of TFG triggered by .OH produced by low doses of HZE ions. The TGF molecules will then be followed by a BD algorithm in a medium representative of a cell culture to estimate the number of activated receptors.

Plante, Ianik↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Gas Turbine Engines↗

Sensor Selection for Aircraft Engine Performance Estimation and Gas Path Fault Diagnostics

This paper presents analytical techniques for aiding system designers in making aircraft engine health management sensor selection decisions. The presented techniques, which are based on linear estimation and probability theory, are tailored for gas turbine engine performance estimation and gas path fault diagnostics applications. They enable quantification of the performance estimation and diagnostic accuracy offered by different candidate sensor suites. For performance estimation, sensor selection metrics are presented for two types of estimators including a Kalman filter and a maximum a posteriori estimator. For each type of performance estimator, sensor selection is based on minimizing the theoretical sum of squared estimation errors in health parameters representing performance deterioration in the major rotating modules of the engine. For gas path fault diagnostics, the sensor selection metric is set up to maximize correct classification rate for a diagnostic strategy that performs fault classification by identifying the fault type that most closely matches the observed measurement signature in a weighted least squares sense. Results from the application of the sensor selection metrics to a linear engine model are presented and discussed. Given a baseline sensor suite and a candidate list of optional sensors, an exhaustive search is performed to determine the optimal sensor suites for performance estimation and fault diagnostics. For any given sensor suite, Monte Carlo simulation results are found to exhibit good agreement with theoretical predictions of estimation and diagnostic accuracies.

Diagnosis↗

Assimilation of satellite microwave observations over the rainbands of tropical cyclones

A novel Bayesian Monte Carlo integration (BMCI) technique was developed to retrieve geophysical variables from satellite microwave radiometer data in the presence of tropical cyclones. The BMCI technique includes three steps: generating a stochastic database, simulating satellite brightness temperatures using a radiative transfer model, and retrieving geophysical variables such as profiles of temperature, relative humidity, and cloud liquid and ice water content from real observations. The technique also provides uncertainty estimates for each retrieval and can output the error covariance matrix of selected parameters. The measurements from the Advanced Technology Microwave Sounder (ATMS) on board Suomi National Polar-Orbiting Partnership (Suomi NPP) and the Global Precipitation Measurement (GPM) Microwave Imager (GMI) were used as input. A new technique was developed to correct the ATMS and GMI observations for the beam-filling effect, which is due to small-scale variability of precipitation and clouds when compared with the instrument footprint and also the nonlinear relation between the brightness temperature and precipitation. In addition, the assimilation of the BMCI retrievals into the NASA GEOS model is discussed for Hurricane Maria. The results show that assimilating the BMCI retrievals can influence the dynamical features of the cyclone, including a stronger warm core, a symmetric eye, and vertically aligned wind columns. Two possible factors that may limit the impact of the BMCI retrievals include 1) the resolution of the model (about 25 km), which was too coarse to show the potential of the BMCI data in improving the representation of tropical storms in the model forecast, and 2) the data assimilation system not being able to consider vertically correlated observation errors.

Isaac Moradi↗

Fluid Creep Effects on Near-Wall Solute Transport for Non-Isothermal Ampoules

There is a growing practical and theoretical interest in developing accurate macroscopic modelling for flows arising in chemical or physical vapor transport (VT) crystal growth experiments, including those conducted in reduced gravity environments. Rosner was the first person to point out that previously neglected rarefield gas dynamics phenomena (Stefan and bouyancy-driven flows) become rather important sources of convection. In particular, the combination of rarefaction and strong gradients of temperature (and/or concentration) tangential to the side-walls of the ampoule induces convective flows known as thermal (and concentration) 'creep' respectively. His order-of-magnitude estimates revealed that thermal creep effects can be non-negligible even at normal gravitational levels. On the macroscopic level, the bulk fluid mechanics can be adequately described by the familiar macroscopic equations as long as the boundary conditions are modified to account for the integrated effect of kinetic boundary layers adjacent to solid boundaries. Motivated by the growing importance of these phenomena, we have embarked on a series of computational studies to elucidate these fundamental creep-induced effects for a rarefied gas in simple, two-dimensional confined geometries. However, unlike previous related studies, we resort to a microscopic description of the gas, mathematically expressed by the Boltzmann integro-differential equation. We employ the direct simulation Monte Carlo (DSMC) method of Bird, the theoretical foundations and several practical applications. In the case of thermally induced flows, the no-time counter method of Bird is used, as implemented for a hard-sphere gas. The scheme has been also extended to account for realistic molecular interaction models, an extension necessary if the diffusion physics underlying concentration creep are to be captured.

Papadopoulos, Dimitrios↗

A Monte Carlo investigation of thrust imbalance of solid rocket motor pairs

A technique is described for theoretical, statistical evaluation of the thrust imbalance of pairs of solid-propellant rocket motors (SRMs) firing in parallel. Sets of the significant variables, determined as a part of the research, are selected using a random sampling technique and the imbalance calculated for a large number of motor pairs. The performance model is upgraded to include the effects of statistical variations in the ovality and alignment of the motor case and mandrel. Effects of cross-correlations of variables are minimized by selecting for the most part completely independent input variables, over forty in number. The imbalance is evaluated in terms of six time - varying parameters as well as eleven single valued ones which themselves are subject to statistical analysis. A sample study of the thrust imbalance of 50 pairs of 146 in. dia. SRMs of the type to be used on the space shuttle is presented. The FORTRAN IV computer program of the analysis and complete instructions for its use are included. Performance computation time for one pair of SRMs is approximately 35 seconds on the IBM 370/155 using the FORTRAN H compiler.

Sforzini, R. H.↗