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At least 289 records · Page 16

Inversion of surface parameters using fast learning neural networks

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.

Dawson, M. S.↗

A probabilistic model of a porous heat exchanger

This paper presents a probabilistic one-dimensional finite element model for heat transfer processes in porous heat exchangers. The Galerkin approach is used to develop the finite element matrices. Some of the submatrices are asymmetric due to the presence of the flow term. The Neumann expansion is used to write the temperature distribution as a series of random variables, and the expectation operator is applied to obtain the mean and deviation statistics. To demonstrate the feasibility of the formulation, a one-dimensional model of heat transfer phenomenon in superfluid flow through a porous media is considered. Results of this formulation agree well with the Monte-Carlo simulations and the analytical solutions. Although the numerical experiments are confined to parametric random variables, a formulation is presented to account for the random spatial variations.

Agrawal, O. P.↗

Detection of atmospheric pressure loading using very long baseline interferometry measurements

Loading of the Earth by the temporal redistribution of global atmospheric mass is likely to displace the positions of geodetic monuments by tens of millimeters both vertically and horizontally. Estimates of these displacements are determined by convolving National Meteorological Center (NMC) global values of atmospheric surface pressure with Farrell's elastic Green's functions. An analysis of the distances between radio telescopes determined by very long baseline interferometry (VLBI) between 1984 and 1992 reveals that in many of the cases studied there is a significant contribution to baseline length change due to atmospheric pressure loading. Our analysis covers intersite distances of between 1000 and 10,000 km and is restricted to those baselines measured more than 100 times. Accounting for the load effects (after first removing a best fit slope) reduces the weighted root-mean-square (WRMS) scatter of the baseline length residuals on 11 of the 22 baselines investigated. The slight degradation observed in the WRMS scatter on the remaining baselines is largely consistent with the expected statistical fluctuations when a small correction is applied to a data set having a much larger random noise. The results from all baselines are consistent with approximately 60% of the computed pressure contribution being present in the VLBI length determinations. Site dependent coefficients determined by fitting local pressure to the theoretical radial displacement are found to reproduce the deformation caused by the regional pressure to within 25% for most inland sites. The coefficients are less reliable at near coastal and island stations.

Vandam, T. M.↗

Comparison of Histograms for Use in Cloud Observation and Modeling

Cloud observation and cloud modeling data can be presented in histograms for each characteristic to be measured. Combining information from single-cloud histograms yields a summary histogram. Summary histograms can be compared to each other to reach conclusions about the behavior of an ensemble of clouds in different places at different times or about the accuracy of a particular cloud model. As in any scientific comparison, it is necessary to decide whether any apparent differences are statistically significant. The usual methods of deciding statistical significance when comparing histograms do not apply in this case because they assume independent data. Thus, a new method is necessary. The proposed method uses the Euclidean distance metric and bootstrapping to calculate the significance level.

Green, Lisa↗

LES of High-Reynolds-Number Coanda Flow Separating from a Rounded Trailing Edge of a Circulation Control Airfoil

This slide presentation reviews the Large Eddy Simulation of a high reynolds number Coanda flow that is separated from a round trailing edge of a ciruclation control airfoil. The objectives of the study are: (1) To investigate detailed physics (flow structures and statistics) of the fully turbulent Coanda jet applied to a CC airfoil, by using LES (2) To compare LES and RANS results to figure out how to improve the performance of existing RANS models for this type of flow.

Nichino, Takafumi↗

Peak Wind Forecasts for the Launch-Critical Wind Towers on Kennedy Space Center/Cape Canaveral Air Force Station, Phase IV

This final report describes the development of a peak wind forecast tool to assist forecasters in determining the probability of violating launch commit criteria (LCC) at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The peak winds arc an important forecast clement for both the Space Shuttle and Expendable Launch Vehicle (ELV) programs. The LCC define specific peak wind thresholds for each launch operation that cannot be exceeded in order to ensure the safety of the vehicle. The 45th Weather Squadron (45 WS) has found that peak winds are a challenging parameter to forecast, particularly in the cool season months of October through April. Based on the importance of forecasting peak winds, the 45 WS tasked the Applied Meteorology Unit (AMU) to update the statistics in the current peak-wind forecast tool to assist in forecasting LCC violations. The tool includes onshore and offshore flow climatologies of the 5-minute mean and peak winds and probability distributions of the peak winds as a function of the 5-minute mean wind speeds.

Crawford, Winifred↗

An Objective Verification of the North American Mesoscale Model for Kennedy Space Center and Cape Canaveral Air Force Station

The 45th Weather Squadron (45 WS) Launch Weather Officers use the 12-km resolution North American Mesoscale (NAM) model (MesoNAM) text and graphical product forecasts extensively to support launch weather operations. However, the actual performance of the model at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) has not been measured objectively. In order to have tangible evidence of model performance, the 45 WS tasked the Applied Meteorology Unit to conduct a detailed statistical analysis of model output compared to observed values. The model products are provided to the 45 WS by ACTA, Inc. and include hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The objective analysis compared the MesoNAM forecast winds, temperature and dew point, as well as the changes in these parameters over time, to the observed values from the sensors in the KSC/CCAFS wind tower network. Objective statistics will give the forecasters knowledge of the model's strength and weaknesses, which will result in improved forecasts for operations.

Bauman, William H., III↗

Classification of Ascension Island and Natal Ozonesondes Using Self-Organizing Maps

Ozone profiles from balloon-borne ozonesondes are used for development of satellite algorithms and in chemistry-climate model initialization, assimilation and evaluation. An important issue in the application of these profiles is how best to treat variations where varying photochemical and dynamical influences can cause the ozone mixing ratio in the tropospheric segments of the profile to change by of a factor of 2-3 within a day. Clustering techniques are an ideal way to approach the statistical classification of profile data and we apply self-organizing maps to tropical tropospheric SHADOZ data, hypothesizing that the data will sort according to various influences on ozone, namely anthropogenic sources like biomass burning, meteorological conditions, and stratospheric or extra-tropical intrusions. Self-organizing maps, that use a learning algorithm to reveal the most prominent features of a data set according to a specified number of clusters, have been determined for the 1998-2009 SHADOZ profiles over Ascension Island (512 profiles, 7.98 deg. S, 14.42 deg. W) and Natal, Brazil (425 profiles, 5.42degS, 35.38degW). The 2 × 2 self-organizing map, which creates 4 clusters, reveals that deviations from the average ozone in the free troposphere include both increased ozone resulting from seasonal biomass burning in Africa and locally reduced ozone brought about by convective lifting of unpolluted boundary-layer air. Expanding to a 4 × 4 self-organizing map shows how biomass burning influences the yearly cycle of tropospheric ozone at Ascension Island and captures the seasonality of ozone at both Ascension Island and Natal. Comparing Ascension Island and Natal using a 4 × 4 self-organizing map at each site reveals similarities in mid-tropospheric ozone, but shows differences in lower-tropospheric ozone due to Ascension Island being closer to African biomass burning and more affected by descent from the mean Walker circulation, with less convective activity, than Natal.

algorithms↗

Astronaut Preflight Cardiovascular Variables Associated with Vascular Compliance are Highly Correlated with Post-Flight Eye Outcome Measures in the Visual Impairment Intracranial Pressure (VIIP) Syndrome Following Long Duration Spaceflight

The detection of the first VIIP case occurred in 2005, and adequate eye outcome measures were available for 31 (67.4%) of the 46 long duration US crewmembers who had flown on the ISS since its first crewed mission in 2000. Therefore, this analysis is limited to a subgroup (22 males and 9 females). A "cardiovascular profile" for each astronaut was compiled by examining twelve individual parameters; eleven of these were preflight variables: systolic blood pressure, pulse pressure, body mass index, percentage body fat, LDL, HDL, triglycerides, use of anti‐lipid medication, fasting serum glucose, and maximal oxygen uptake in ml/kg. Each of these variables was averaged across three preflight annual physical exams. Astronaut age prior to the long duration mission, and inflight salt intake was also included in the analysis. The group of cardiovascular variables for each crew member was compared with seven VIIP eye outcome variables collected during the immediate post‐flight period: anterior-posterior axial length of the globe measured by ultrasound and optical biometry; optic nerve sheath diameter, optic nerve diameter, and optic nerve to sheath ratio‐ each measured by ultrasound and magnetic resonance imaging (MRI), intraocular pressure (IOP), change in manifest refraction, mean retinal nerve fiber layer (RNFL) on optical coherence tomography (OCT), and RNFL of the inferior and superior retinal quadrants. Since most of the VIIP eye outcome measures were added sequentially beginning in 2005, as knowledge of the syndrome improved, data were unavailable for 22.0% of the outcome measurements. To address the missing data, we employed multivariate multiple imputation techniques with predictive mean matching methods to accumulate 200 separate imputed datasets for analysis. We were able to impute data for the 22.0% of missing VIIP eye outcomes. We then applied Rubin's rules for collapsing the statistical results across our 200 multiply imputed data sets to assess the canonical correlation between the eye outcomes and the twelve astronaut cardiovascular variables available for all 31 subjects. Results: A highly significant canonical correlation was observed among the canonical solutions (p<.00001), with an average best canonical correlation of.97. The results suggest a strong association between astronauts' measures of cardiovascular health and the seven eye outcomes of the VIIP syndrome used in this analysis. Furthermore, the "joint test" revealed a significant difference in cardiovascular profile between male and female astronauts (Prob > F = 0.00001). Overall, female astronauts demonstrated a significantly healthier cardiovascular status. Individually, the female astronauts had significantly healthier profiles on seven of twelve cardiovascular variables than the men (p values ranging from <0.0001 to <0.05). Male astronauts did not demonstrate significantly healthier values on any of the twelve cardiovascular variables measured

Otto, Christian↗

Stochastic-Strength-Based Damage Simulation Tool for Ceramic Matrix and Polymer Matrix Composite Structures

Stochastic-based, discrete-event progressive damage simulations of ceramic-matrix composite and polymer matrix composite material structures have been enabled through the development of a unique multiscale modeling tool. This effort involves coupling three independently developed software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/ Life), and (3) the Abaqus finite element analysis (FEA) program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating unit cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC. Abaqus is used at the global scale to model the overall composite structure. An Abaqus user-defined material (UMAT) interface, referred to here as "FEAMAC/CARES," was developed that enables MAC/GMC and CARES/Life to operate seamlessly with the Abaqus FEA code. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events, which incrementally progress and lead to ultimate structural failure. This report describes the FEAMAC/CARES methodology and discusses examples that illustrate the performance of the tool. A comprehensive example problem, simulating the progressive damage of laminated ceramic matrix composites under various off-axis loading conditions and including a double notched tensile specimen geometry, is described in a separate report.

composite structures↗

Stochastic-Strength-Based Damage Simulation of Ceramic Matrix Composite Laminates

The Finite Element Analysis-Micromechanics Analysis Code/Ceramics Analysis and Reliability Evaluation of Structures (FEAMAC/CARES) program was used to characterize and predict the progressive damage response of silicon-carbide-fiber-reinforced reaction-bonded silicon nitride matrix (SiC/RBSN) composite laminate tensile specimens. Studied were unidirectional laminates [0] (sub 8), [10] (sub 8), [45] (sub 8), and [90] (sub 8); cross-ply laminates [0 (sub 2) divided by 90 (sub 2),]s; angled-ply laminates [plus 45 (sub 2) divided by -45 (sub 2), ]s; doubled-edge-notched [0] (sub 8), laminates; and central-hole laminates. Results correlated well with the experimental data. This work was performed as a validation and benchmarking exercise of the FEAMAC/CARES program. FEAMAC/CARES simulates stochastic-based discrete-event progressive damage of ceramic matrix composite and polymer matrix composite material structures. It couples three software programs: (1) the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC), (2) the Ceramics Analysis and Reliability Evaluation of Structures Life Prediction Program (CARES/Life), and (3) the Abaqus finite element analysis program. MAC/GMC contributes multiscale modeling capabilities and micromechanics relations to determine stresses and deformations at the microscale of the composite material repeating-unit-cell (RUC). CARES/Life contributes statistical multiaxial failure criteria that can be applied to the individual brittle-material constituents of the RUC, and Abaqus is used to model the overall composite structure. For each FEAMAC/CARES simulation trial, the stochastic nature of brittle material strength results in random, discrete damage events that incrementally progress until ultimate structural failure.

composite structures↗

Evaluation of Classifier Complexity for Delay Tolerant Network Routing

The growing popularity of small cost effective satellites (SmallSats, CubeSats, etc.) creates the potential for a variety of new science applications involving multiple nodes functioning together or independently to achieve a task, such as swarms and constellations. As this technology develops and is deployed for missions in Low Earth Orbit and beyond, the use of delay tolerant networking (DTN) techniques may improve communication capabilities within the network. In this paper, a network hierarchy is developed from heterogeneous networks of SmallSats, surface vehicles, relay satellites and ground stations which form an integrated network. There is a tradeoff between complexity, flexibility, and scalability of user defined schedules versus autonomous routing as the number of nodes in the network increases. To address these issues, this work proposes a machine learning classifier based on DTN routing metrics. A framework is developed which will allow for the use of several categories of machine learning algorithms (decision tree, random forest and deep learning) to be applied to a dataset of historical network statistics, which allows for the evaluation of algorithm complexity versus performance to be explored. We develop the emulation of a hierarchical network, consisting of tens of nodes which form a cognitive network architecture. CORE (Common Open Research Emulator) is used to emulate the network using bundle protocol and DTN IP neighbor discovery.

Dudukovich, Rachel↗

Hybrid MD-Nernst Planck Model of Alpha-hemolysin Conductance Properties

Motivated by experiments in which an applied electric field translocates polynucleotides through an alpha-hemolysin protein channel causing ionic current transient blockade, a hybrid simulation model is proposed to predict the conductance properties of the open channel. Time scales corresponding to ion permeation processes are reached using the Poisson-Nemst-Planck (PNP) electro-diffusion model in which both solvent and local ion concentrations are represented as a continuum. The diffusion coefficients of the ions (K(+) and Cl(-)) input in the PNP model are, however, calculated from all-atom molecular dynamics (MD). In the MD simulations, a reduced representation of the channel is used. The channel is solvated in a 1 M KCI solution, and an external electric field is applied. The pore specific diffusion coefficients for both ionic species are reduced 5-7 times in comparison to bulk values. Significant statistical variations (17-45%) of the pore-ions diffusivities are observed. Within the statistics, the ionic diffusivities remain invariable for a range of external applied voltages between 30 and 240mV. In the 2D-PNP calculations, the pore stem is approximated by a smooth cylinder of radius approx. 9A with two constriction blocks where the radius is reduced to approx. 6A. The electrostatic potential includes the contribution from the atomistic charges. The MD-PNP model shows that the atomic charges are responsible for the rectifying behaviour and for the slight anion selectivity of the a-hemolysin pore. Independent of the hierarchy between the anion and cation diffusivities, the anionic contribution to the total ionic current will dominate. The predictions of the MD-PNP model are in good agreement with experimental data and give confidence in the present approach of bridging time scales by combining a microscopic and macroscopic model.

Cozmuta, Ioana↗

On the probability of magnification by cosmologically distributed gravitational lenses

An analytical method for calculating the statistical properties of source magnification caused by gravitational lenses randomly distributed throughout the universe is presented. Two lenses are considered at different redshifts to show that such an assumption is a statistically adequate approximation. The derived general formulas are applied to point-mass lenses with both point and extended sources. Analytical results of the magnification probability for point sources are accurate to within 10 percent in comparison with the available numerical simulations to moderate redshifts of less than about 2. In terms of the flux conservation, the results are accurate to within 18 percent at a redshift of 6 with respect to the Dyer-Roeder model of a clumpy universe. It is concluded that the present formulas are adequate for statistical studies of magnification by random gravitational lenses on cosmological scales.

Pei, Yichuan C.↗

Statistical theory of cubic Langmuir turbulence

The cubic direct interaction approximation is applied to a truncated (in Fourier space) version of the cubically nonlinear Schroedinger equation model of Langmuir physics. The results are compared (in the three-mode case) to those for an ensemble of numerical solutions of the dynamical equations with 10,000 different sets of Gaussianly distributed initial conditions. In the undriven, undamped case, the statistical theory (but not the ensemble) evolves to a state of thermal equilibrium. In the driven, damped case, the statistical theory appears to evolve to a state close to that corresponding to one of the limit cycles of the dynamical equations.

Sun, G.-Z.↗

Shielding Effectiveness in a Two-Dimensional Reverberation Chamber Using Finite-Element Techniques

Reverberation chambers are attaining an increased importance in determination of electromagnetic susceptibility of avionics equipment. Given the nature of the variable boundary condition, the ability of a given source to couple energy into certain modes and the passband characteristic due the chamber Q, the fields are typically characterized by statistical means. The emphasis of this work is to apply finite-element techniques at cutoff to the analysis of a two-dimensional structure to examine the notion of shielding-effectiveness issues in a reverberating environment. Simulated mechanical stirring will be used to obtain the appropriate statistical field distribution. The shielding effectiveness (SE) in a simulated reverberating environment is compared to measurements in a reverberation chamber. A log-normal distribution for the SE is observed with implications for system designers. The work is intended to provide further refinement in the consideration of SE in a complex electromagnetic environment.

Bunting, Charles F.↗

Statistical approach to cubic Langmuir turbulence

Previous work on the cubic direct interaction approximation applied to the truncated (in Fourier space) cubically nonlinear Schroedinger equation model of Langmuir turbulence is extended to more modes. In the undriven, undamped case, excellent agreement between the statistical theory and a numerical ensemble of solutions of the dynamic equations is obtained. In the driven, damped case, satisfactory agreement is obtained provided the dynamic ensemble is limited to initial conditions in the basin of attraction.

Sun, G.-Z.↗

It's All Relative: A Validation of Radiation Quality Comparison Metrics

Historically, the relative biological effectiveness (RBE) has been calculated to quantify the difference between heavy ion and gamma ray radiation. The RBE is then applied to gamma ray data to predict the effects of heavy ions in humans. The RBE is an iso-effect dose-to-dose ratio which, due to its counterintuitive nature, has been commonly miscalculated as an iso-dose effect-to-effect ratio. A paper recently published by Shuryak et al described this second measure intentionally for the first time in 2017, referring to it as the radiation effects ratio (RER). In this study, we utilized simulations to test the ability of both the RBE and the RER to predict known heavy ion effects. RBEs and RERs were calculated using mouse data from Chang et al, and the ability of the RBE and RER to predict the heavy ion data from which they were calculated was verified. Statistical transformations often utilized during data analysis were applied to the gamma and heavy ion data to determine whether RBE and RER are each uniquely defined measures. Scale changes are expected when translating effects from mice to humans and between human populations; gamma and heavy ion data were transformed to represent potential scale changes. The ability of the RBE and RER to predict the transformed heavy ion data from the transformed gamma data was then tested. The RBE but not the RER was uniquely defined after all statistical transformations. The RBE correctly predicted the scale-transformed heavy ion data, while the RER did not. This presentation describes potential implications for both metrics in light of these findings.

Chappell, L. J.↗