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At least 73 records · Page 4

Using Controlled Impact Experiments to Understand the Effects of Cohesive Blocks on the Cratering Process

When considering large-scale impact events that occur in the gravity-regime, smallscale target heterogeneities (on order of the projectile diameter) are anticipated to have a minimal effect on the cratering process and are therefore not considered in scaling relations [1-3]. Such heterogeneities and other details of the target's strength and structure, however, become increasingly influential as the magnitude of the impact decreases [4]. At the scale of craters forming mostly in regolith on the Moon (< a few meters), for example, target properties such as cohesive strength, density, porosity, and friction have more leverage than gravity to influence the resultant crater dimensions [5]. Further complications beyond just target properties can manifest in many forms, such as subsurface layers [6]; the presence of random, competent blocks [7]; buried lenses of impact melt; and/or pockets of regolith compacted or indurated to varying degrees by previous impacts. Summing the total effect of target properties and any additional heterogeneities for integration into scaling relations is not straightforward, as each individual parameter will have unequal, and so far, unquantified, effects on the final crater. Even when craters are produced under a best-case scenario of controlled laboratory conditions, understanding the entire relevant parameter space can be a formidable task, and deconvolution of all the contributing factors can be a complex undertaking. To begin the process of quantifying such effects, we are conducting an extensive series of impact experiments to build a framework for the interpretation of craters observed on the characteristically complex surfaces throughout the solar system. Here we present the first, and simplest, configuration to be examined in this multi-year experimental campaign: one in which solitary, cohesive blocks are placed in the path of the projectile’s trajectory at different burial depths in granular, sand targets. Among the variables to be investigated in this configuration are the influence of block size, compressive strength, and burial depth.

impact crater↗

ESTIMATION OF THE SPACE SHUTTLE ROLLOUT FORCING FUNCTION

The Space Shuttle Vehicle is assembled in the Vertical Assembly Building (VAB) at Kennedy Space Flight Center in Florida. The Vehicle is stacked on a Mobile Launch Platform (MLP) that weighs eight million pounds. A Crawler Transporter (CT) then carries the MLP and the stacked vehicle (12 million pounds total weight) to the launch complex located 5 miles away. This operation is performed at 0.9 mph resulting in a 4.5-hour transport. A recent test was performed to monitor the dynamic environment that was produced during rollout. It was found that the rollout is a harmonic-rich dynamic environment that was previously not understood. This paper will describe work that has been performed to estimate the forcing function that is produced in the transportation process. The rollout analysis team has determined that there are two families of harmonics of the drive train, which excite the system as a function of CT speed. There are also excitation sources, which are random or narrow-band in frequency and are not a function of CT speed. This presentation will discuss the application of the Sum of Weighted Accelerations Technique (SWAT) to further refine this understanding by estimating the forces and moments at the center-of-mass.

James, George H., III↗

Model of Image Artifacts from Dust Particles

A mathematical model of image artifacts produced by dust particles on lenses has been derived. Machine-vision systems often have to work with camera lenses that become dusty during use. Dust particles on the front surface of a lens produce image artifacts that can potentially affect the performance of a machine-vision algorithm. The present model satisfies a need for a means of synthesizing dust image artifacts for testing machine-vision algorithms for robustness (or the lack thereof) in the presence of dust on lenses. A dust particle can absorb light or scatter light out of some pixels, thereby giving rise to a dark dust artifact. It can also scatter light into other pixels, thereby giving rise to a bright dust artifact. For the sake of simplicity, this model deals only with dark dust artifacts. The model effectively represents dark dust artifacts as an attenuation image consisting of an array of diffuse darkened spots centered at image locations corresponding to the locations of dust particles. The dust artifacts are computationally incorporated into a given test image by simply multiplying the brightness value of each pixel by a transmission factor that incorporates the factor of attenuation, by dust particles, of the light incident on that pixel. With respect to computation of the attenuation and transmission factors, the model is based on a first-order geometric (ray)-optics treatment of the shadows cast by dust particles on the image detector. In this model, the light collected by a pixel is deemed to be confined to a pair of cones defined by the location of the pixel s image in object space, the entrance pupil of the lens, and the location of the pixel in the image plane (see Figure 1). For simplicity, it is assumed that the size of a dust particle is somewhat less than the diameter, at the front surface of the lens, of any collection cone containing all or part of that dust particle. Under this assumption, the shape of any individual dust particle artifact is the shape (typically, circular) of the aperture, and the contribution of the particle to the attenuation factor for a given pixel is the fraction of the cross-sectional area of the collection cone occupied by the particle. Assuming that dust particles do not overlap, the net transmission factor for a given pixel is calculated as one minus the sum of attenuation factors contributed by all dust particles affecting that pixel. In a test, the model was used to synthesize attenuation images for random distributions of dust particles on the front surface of a lens at various relative aperture (F-number) settings. As shown in Figure 2, the attenuation images resembled dust artifacts in real test images recorded while the lens was aimed at a white target.

Willson, Reg↗

Distributed memory approaches for robotic neural controllers

The suitability is explored of two varieties of distributed memory neutral networks as trainable controllers for a simulated robotics task. The task requires that two cameras observe an arbitrary target point in space. Coordinates of the target on the camera image planes are passed to a neural controller which must learn to solve the inverse kinematics of a manipulator with one revolute and two prismatic joints. Two new network designs are evaluated. The first, radial basis sparse distributed memory (RBSDM), approximates functional mappings as sums of multivariate gaussians centered around previously learned patterns. The second network types involved variations of Adaptive Vector Quantizers or Self Organizing Maps. In these networks, random N dimensional points are given local connectivities. They are then exposed to training patterns and readjust their locations based on a nearest neighbor rule. Both approaches are tested based on their ability to interpolate manipulator joint coordinates for simulated arm movement while simultaneously performing stereo fusion of the camera data. Comparisons are made with classical k-nearest neighbor pattern recognition techniques.

Jorgensen, Charles C.↗

Performance of a Strapdown Ring Laser Gyro Tetrad Inertial Navigation System in a helicopter flight environment

Results are presented for the first flight demonstration test of a strapdown laser inertial navigation system in a helicopter environment. It is noted that acceptable navigation accuracies were obtained with system alignment times as short as 5 min or less, and that the use of all four available sensors in the navigation algorithm did not significantly improve performance over that achievable by means of only three orthogonal sensors. Failure detection by means of the parity residual from four axes proved successful for failure levels far below the noise threshold of flight control sensing requirements. Summing the gyro parity residual for a period of 13-20 min can yield step-shifted laser gyro sensor bias error detection comparable to the gyro random shift specification.

Carestia, R. A.↗

Television noise-reduction device

System greatly improves signal-to-noise ratio with little or no loss in picture resolution. By storage of luminance component, which is summed with chrominance component, system performs mathematical integration of basically-repetitive television signals. Integration of signals over interval of their repetition causes little change in original signals and eliminates random noise.

Stamps, J. C.↗

Hybrid analog-digital associative neural network

Random access memory is used to store synaptic information in the form of a matrix of rows and columns of binary digits. N rows read in sequence are processed through switches and resistors, and a summing amplifier to N neural amplifiers in sequence, one row for each amplifier, using a first array of sample-and-hold devices S/H1 for commutation. The outputs of the neural amplifiers are stored in a second array of sample-and-hold devices S/H2 so that after N rows are processed, all of the second array of sample-and-hold devices are updated. A second memory may be added for binary values of 0 and -1, and processed simultaneously with the first to provide for values of 1, 0, and -1, the results of which are combined in a difference amplifier.

Moopenn, Alexander W.↗

Hybrid analog-digital associative neural network

Random access memory is used to store synaptic information in the form of a matrix of rows and columns of binary digits. N rows read in sequence are processed through switches and resistors, and a summing amplifier to N neural amplifiers in sequence, one row for each amplifier, using a first array of sample-and-hold devices S/H1 for commutation. The outputs of the neural amplifiers are stored in a second array of sample-and-hold devices S/H2 so that after N rows are processed, all of said second array of sample-and-hold devices are updated. A second memory may be added for binary values of 0 and -1, and processed simultaneously with the first to provide for values of 1, 0, and -1, the results of which are combined in a difference amplifier.

Moopenn, Alexander W.↗

A Numerical Simulation of Scattering from One-Dimensional Inhomogeneous Dielectric Random Surfaces

In this paper, an efficient numerical solution for the scattering problem of inhomogeneous dielectric rough surfaces is presented. The inhomogeneous dielectric random surface represents a bare soil surface and is considered to be comprised of a large number of randomly positioned dielectric humps of different sizes, shapes, and dielectric constants above an impedance surface. Clods with nonuniform moisture content and rocks are modeled by inhomogeneous dielectric humps and the underlying smooth wet soil surface is modeled by an impedance surface. In this technique, an efficient numerical solution for the constituent dielectric humps over an impedance surface is obtained using Green's function derived by the exact image theory in conjunction with the method of moments. The scattered field from a sample of the rough surface is obtained by summing the scattered fields from all the individual humps of the surface coherently ignoring the effect of multiple scattering between the humps. The statistical behavior of the scattering coefficient sigma(sup 0) is obtained from the calculation of scattered fields of many different realizations of the surface. Numerical results are presented for several different roughnesses and dielectric constants of the random surfaces. The numerical technique is verified by comparing the numerical solution with the solution based on the small perturbation method and the physical optics model for homogeneous rough surfaces. This technique can be used to study the behavior of scattering coefficient and phase difference statistics of rough soil surfaces for which no analytical solution exists.

Sarabandi, Kamal↗

Fidelity Analysis of Sampled Imaging Systems

Many modeling, simulation and performance analysis studies of sampled imaging systems are inherently incomplete because they are conditioned on a discrete-input, discrete-output model that only accounts for blurring during image acquisition and additive noise. For those sampled imaging systems where the effects of digital image acquisition, digital filtering and reconstruction are significant, the modeling, simulation and performance analysis should be based on a more comprehensive continuous-input, discrete-processing, continuous-output end-to-end model. This more comprehensive model should properly account for the low-pass filtering effects of image acquisition prior to sampling, the potentially important noiselike effects of the aliasing caused by sampling, additive noise due to device electronics and quantization, the generally high-boost filtering effects of digital processing, and the low-pass filtering effects of image reconstruction. This model should not, however, be so complex as to preclude significant mathematical analysis, particularly the mean-square (fidelity) type of analysis so common in linear system theory. We demonstrate that, although the mathematics of such a model is more complex, the increase in complexity is not so great as to prevent a complete fidelity-metric analysis at both the component level and at the end-to-end system level: that is, computable mean-square-based fidelity metrics are developed by which both component-level and system-level performance can be quantified. In addition, we demonstrate that system performance can be assessed qualitatively by visualizing the output image as the sum of three component images, each of which relates to a corresponding fidelity metric. The cascaded, or filtered, component accounts for the end-to-end system filtering of image acquisition, digital processing, and image reconstruction; the random noise component accounts for additive random noise, modulated by digital processing and image reconstruction filtering; and the aliased noise component accounts for the frequency folding effect of sampling, modulated by digital processing and image reconstruction filtering.

Park, Stephen K.↗

Calculating the bidirectional reflectance of natural vegetation covers using Boolean models and geometric optics

The bidirectional radiance or reflectance of a forest or woodland can be modeled using principles of geometric optics and Boolean models for random sets in a three dimensional space. This model may be defined at two levels, the scene includes four components; sunlight and shadowed canopy, and sunlit and shadowed background. The reflectance of the scene is modeled as the sum of the reflectances of the individual components as weighted by their areal proportions in the field of view. At the leaf level, the canopy envelope is an assemblage of leaves, and thus the reflectance is a function of the areal proportions of sunlit and shadowed leaf, and sunlit and shadowed background. Because the proportions of scene components are dependent upon the directions of irradiance and exitance, the model accounts for the hotspot that is well known in leaf and tree canopies.

Strahler, Alan H.↗

A study of the Lute Metering Structure

Two Metering Structure configurations were investigated. The first case was the traditional style metering structure which is larger than the outside diameter of the primary mirror. The second case investigated was the center support concept in which the outside diameter of the structure is less than the inside diameter of the primary mirror. Beryllium was used as the baseline material for this study. Four other materials were considered as candidates for the metering structure. These materials are: Graphite Epoxy, Aluminum, Titanium, and Invar. The loading conditions used for this study were estimated to be: Quasi Static: 6.0 G (all three directions); and Random Vibration: 30.0 G (applied 1 axis at a time). Taking advantage of symmetry, it was necessary to apply the lateral loading to only one axis. These loads were applied to both concepts and to all material configurations. The loadings as described above were based on the best available information and is felt to be adequate for this study since it was consistently used for all configurations. A load factor 2.00 was applied to both quasi static and random vibration loads. The allowable stresses are conservatively based yield strength of the material, except for the struts which are controlled by elastic stability. The stresses determined from each individual loading direction were conservatively combined by the absolute sum method.

Foreman, James W.↗

Interaction between vestibulosympathetic and skeletal muscle reflexes on sympathetic activity in humans

Evidence from animals indicates that skeletal muscle afferents activate the vestibular nuclei and that both vestibular and skeletal muscle afferents have inputs to the ventrolateral medulla. The purpose of the present study was to investigate the interaction between the vestibulosympathetic and skeletal muscle reflexes on muscle sympathetic nerve activity (MSNA) and arterial pressure in humans. MSNA, arterial pressure, and heart rate were measured in 17 healthy subjects in the prone position during three experimental trials. The three trials were 2 min of 1) head-down rotation (HDR) to engage the vestibulosympathetic reflex, 2) isometric handgrip (IHG) at 30% maximal voluntary contraction to activate skeletal muscle afferents, and 3) HDR and IHG performed simultaneously. The order of the three trials was randomized. HDR and IHG performed alone increased total MSNA by 46 +/- 16 and 77 +/- 24 units, respectively (P < 0.01). During the HDR plus IHG trial, MSNA increased 142 +/- 38 units (P < 0.01). This increase was not significantly different from the sum of the individual trials (130 +/- 41 units). This finding was also observed with mean arterial pressure (sum = 21 +/- 2 mmHg and HDR + IHG = 22 +/- 2 mmHg). These findings suggest that there is an additive interaction for MSNA and arterial pressure when the vestibulosympathetic and skeletal muscle reflexes are engaged simultaneously in humans. Therefore, no central modulation exists between these two reflexes with regard to MSNA output in humans.

NASA Discipline Neuroscience↗

Guiding center model to interpret neutral particle analyzer results

The theoretical model is discussed, which accounts for drift and cyclotron components of ion motion in a partially ionized plasma. Density and velocity distributions are systematically precribed. The flux into the neutral particle analyzer (NPA) from this plasma is determined by summing over all charge exchange neutrals in phase space which are directed into apertures. Especially detailed data, obtained by sweeping the line of sight of the apertures across the plasma of the NASA Lewis HIP-1 burnout device, are presented. Selection of randomized cyclotron velocity distributions about mean azimuthal drift yield energy distributions which compared well with experiment. Use of data obtained with a bending magnet on the NPA showed that separation between energy distribution curves of various mass species correlate well with a drift divided by mean cyclotron energy parameter of the theory. Use of the guiding center model in conjunction with NPA scans across the plasma aid in estimates of ion density and E field variation with plasma radius.

Englert, G. W.↗

Socio-psychological airplane noise investigation in the districts of three Swiss airports: Zurich, Geneva and Basel

The results of noise measurements and calculations are available in the form of noise maps for each of the three areas. To measure the stress due to airplane noise the Noise and Number Index (NNI) was applied. In the vicinities of the airports, 400 households were randomly selected in each of the three noise zones (of 10 NNI intervals each). A total of 3939 questionnaires could be evaluated, one quarter of which came from areas without airplane noise. Concurrently, traffic noise was measured in areas of Basel and expressed in sum total levels L sub 50 and the reaction of 944 persons was elicited by interrogation.

Graf, R.↗

Communication Limits Due to Photon-Detector Jitter

A theoretical and experimental study was conducted of the limit imposed by photon-detector jitter on the capacity of a pulse-position-modulated optical communication system in which the receiver operates in a photon-counting (weak-signal) regime. Photon-detector jitter is a random delay between impingement of a photon and generation of an electrical pulse by the detector. In the study, jitter statistics were computed from jitter measurements made on several photon detectors. The probability density of jitter was mathematically modeled by use of a weighted sum of Gaussian functions. Parameters of the model were adjusted to fit histograms representing the measured-jitter statistics. Likelihoods of assigning detector-output pulses to correct pulse time slots in the presence of jitter were derived and used to compute channel capacities and corresponding losses due to jitter. It was found that the loss, expressed as the ratio between the signal power needed to achieve a specified capacity in the presence of jitter and that needed to obtain the same capacity in the absence of jitter, is well approximated as a quadratic function of the standard deviation of the jitter in units of pulse-time-slot duration.

Moision, Bruce E.↗

Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in Ref. [2]. First, the adaptive Gaussian sum propagation is explained and then the new marginalized adaptive Gaussian sum propagation is derived. Finally, an example simulation is presented.

state estimation↗