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At least 235 records · Page 13

Cometary water on Venus - Implications of stochastic impacts

Attention is given to a Venus water abundance model, incorporating a stochastic cometary source and nonthermal hydrogen escape, that reproduces both the near-steady-state balance between escape loss and infall replenishment implied by Venus' short water lifetime, and the consistency of the observed deuterium-to-hydrogen ratio with a steady state. It is shown that the stochastic variability of each of these quantities is large. Water's quasi-steady state on Venus is judged to be mediated by comet impacts, leading to an obscuration of the early water history of Venus by the history of random impacts.

Grinspoon, David H.↗

Design Of Combined Stochastic Feedforward/Feedback Control

Methodology accommodates variety of control structures and design techniques. In methodology for combined stochastic feedforward/feedback control, main objectives of feedforward and feedback control laws seen clearly. Inclusion of error-integral feedback, dynamic compensation, rate-command control structure, and like integral element of methodology. Another advantage of methodology flexibility to develop variety of techniques for design of feedback control with arbitrary structures to obtain feedback controller: includes stochastic output feedback, multiconfiguration control, decentralized control, or frequency and classical control methods. Control modes of system include capture and tracking of localizer and glideslope, crab, decrab, and flare. By use of recommended incremental implementation, control laws simulated on digital computer and connected with nonlinear digital simulation of aircraft and its systems.

Halyo, Nesim↗

Stochastic modeling of crack initiation and short-crack growth under creep and creep-fatigue conditions

A simplified stochastic model is proposed for crack initiation and short-crack growth under creep and creep-fatigue conditions. Material inhomogeneity provides the random nature of crack initiation and early growth. In the model, the influence of microstructure is introduced by the variability of: (1) damage accumulation along grain boundaries, (2) critical damage required for crack initiation or growth, and (3) the grain-boundary length. The probabilities of crack initiation and growth are derived by using convolution integrals. The model is calibrated and used to predict the crack density and crack-growth rate of short cracks of 304 stainless steel under creep and creep-fatigue conditions. The mean-crack initiation lives are predicted to be within an average deviation of about 10 percent from the experimental results. The predicted cumulative distributions of crack-growth rate follow the experimental data closely. The applicability of the simplified stochastic model is discussed and the future research direction is outlined.

Kitamura, Takayuki↗

Stochastic time-optimal control problems

Two types of stochastic time-optimal controls in a one-dimensional setting are considered. Multidimensional problems, in the case of complete state information available and the system modeled by stochastic differential equations, are studied under the formulation of minimizing the expected transient-response time. The necessary condition of optimality is the satisfaction for the value function of a parabolic partial differential equation with boundary conditions. The sufficient condition of optimality is also provided, based on Dynkin's formula. Finally, three examples are given.

Zhang, W.↗

Stochastic Feedforward Control Technique

Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.

Halyo, Nesim↗

Stochastic robustness of linear control systems

A simple numerical procedure for estimating the stochastic robustness of a linear, time-invariant system is described. Monte Carlo evaluation of the system's eigenvalues allows the probability of instability and the related stochastic root locus to be estimated. This definition of robustness is an alternative to existing deterministic definitions that address both structured and unstructured parameter variations directly. This analysis approach treats not only Gaussian parameter uncertainties but non-Gaussian cases, including uncertain-but-bounded variations. Trivial extensions of the procedure admit alternate discriminants to be considered. Thus, the probabilities that stipulated degrees of instability will be exceeded or that closed-loop roots will leave desirable regions also can be estimated. Results are particularly amenable to graphical presentation.

Stengel, Robert F.↗

Stochastic shock waves as a candidate mechanism for the formation of the He I 10830-A line in cool giant stars

The question of whether strong shocks produced in time-dependent stochastic wave models can explain the formation of the He I 10830-A line in cool giant stars is examined. The research is based on the ab initio chromosphere model for Arcturus by Cuntz (1987), showing that a stochastic distribution of wave periods leads to overtaking and merging of shocks, which occasionally produce very strong shocks with temperatures larger than 40,000 K in the postshock regions. These temperatures can easily produce a significant population in the 2s 3S state by electron collisional excitation. The 10830-A line occurs in absorption when the densities in the shocks exceed 10 million/cu cm.

Cuntz, Manfred↗

Stochastic robustness of linear time-invariant control systems

A simple numerical procedure for estimating the stochastic robustness of a linear, time-invariant system is described. Monte Carlo evaluation of the system's eigenvalues allows the probability of instability and the related stochastic root locus to be estimated. This definition of robustness is an alternative to existing deterministic definitions that address both structured and unstructured parameter variations directly. This analysis approach treats not only Gaussian parameter uncertainties but also non-Gaussian cases, including uncertain-but-bounded variations. Trivial extensions of the procedure permit alternate discriminants to be considered. Thus the probabilities that stipulated degrees of instability will be exceeded or that closed-loop roots will leave desirable regions can also be estimated. Results are particularly amenable to graphical presentation.

Stengel, Robert F.↗

Stochastic estimation of coherent structures in turbulent boundary layers

The stochastic estimation technique is described as well as its extension to two-point and space-time conditional estimates. Based on the experimental data of Guezennec (1985), a comparison is made between the stochastic estimates and the conventional ensemble averaging results. As only the normal velocity and streamwise components were measured at each point on the sampling grid, the assumption of statistical symmetry in the spanwise direction about the centerline was used and the spanwise velocity component was reconstructed by integrating the continuity equation from the centerline outward.

Guezennec, Y. G.↗

The He I 10830 line in Arcturus produced by stochastic shocks

An investigation is conducted as to whether strong shocks produced in time-dependent stochastic wave models can explain the formation of the He I 10830 line in a cool giant star like Arcturus. The exploratory research is based on the work of Cuntz (1987) who found that stochastic waves lead to overtaking and merging of shocks producing occasionally very strong shocks with temperatures larger than 40,000 K in the postshock regions.

Cuntz, Manfred↗

Magnetohydrodynamic turbulence dissipation and stochastic proton acceleration in solar flares

The Alfven and fast magnetosonic wave MHD modes can stochastically accelerate protons from super-Alfvenic to ultrarelativistic energies in solar flares. It is the Landau resonance, however, which generates most of the magnetosonic wave energy being dissipated on electron heating rather than on stochastic proton acceleration. Alfven waves are also subject to a nonlinear wave-particle interaction, and nonlinear Landau damping can selectively and efficiently heat the ambient protons to preaccelerate many to super-Alfvenic speeds. A spectrum of Alfven waves can therefore energize protons from low-temperature thermal to ultrarelativistic energies through a combination of linear and nonlinear particle-wave interactions.

Miller, James A.↗

Estimation of optical flow in airborne electro-optical sensors by stochastic approximation

The essence of motion or range estimation by passive electrooptical means is the ability to determine the correspondence of picture elements in pairs of image frames and to estimate their coordinates and their disparity (relative shifts) in the image plane of an electrooptical imaging sensor. The disparity can be in successive frames due to self-motion or in simultaneous frames of a stereo pair. A key issue is to provide these estimates on-line. This paper describes the theoretical background of such an interframe shift estimator. It is based on a stochastic gradient algorithm, specifically implementing a form of stochastic approximation, which can achieve rapid convergence of the shift estimate. Analytical and numerical simulation examples for random texture and isolated features validate the feasibility and the effectiveness of the estimator.

Merhav, S. J.↗

Stochastic robustness

To carry out stochastic robustness analysis, an expected probability distribution is assigned to each uncertain parameter in the system. The Monte Carlo analysis proceeds by repeatedly assigning shaped random values to each plant parameter, evaluating the stability of performance metric, and performing the binary classification (stable/unstable, etc.). If the system is stable, the state response to a unit disturbance impulse can be propagated to establish whether the response would violate settling time envelopes and whether peak actuator use would violate predetermined maximums. The final estimates of the probability of each form of unacceptable behavior are found by dividing the number of cases in which the overall system had that form of unacceptability by the number of cases run. Stability robustness can be portrayed graphically using the stochastic root locus and by using histograms of parameter values found in the unacceptable cases.

Marrison, C.↗

Technical notes and correspondence: Stochastic robustness of linear time-invariant control systems

A simple numerical procedure for estimating the stochastic robustness of a linear time-invariant system is described. Monte Carlo evaluations of the system's eigenvalues allows the probability of instability and the related stochastic root locus to be estimated. This analysis approach treats not only Gaussian parameter uncertainties but non-Gaussian cases, including uncertain-but-bounded variation. Confidence intervals for the scalar probability of instability address computational issues inherent in Monte Carlo simulation. Trivial extensions of the procedure admit consideration of alternate discriminants; thus, the probabilities that stipulated degrees of instability will be exceeded or that closed-loop roots will leave desirable regions can also be estimated. Results are particularly amenable to graphical presentation.

Stengel, Robert F.↗

Ion pickup, scattering, and stochastic acceleration in the cometary environment of P/Giacobini-Zinner

Observations and theory related to the scattering and acceleration of cometary pickup ions are reviewed with emphasis on Comet P/Giacobini-Zinner. A comparison of the regions upstream and downstream of the bow shock is made to assess the relative merits of each as a site for stochastic acceleration of ions above the pickup energy through interaction with low-frequency MHD waves. In the far upstream region the data are most consistent with a model where pickup ions generate a low level of MHD waves but remain relatively scatter-free. In the downstream region intense magnetic fluctuations gives rise to rapid isotropization of the ions and a second-order stochastic acceleration. The properties of the MHD power spectrum are related to the energetic ion spectrum in the framework of a leaky box model where the bulk of the acceleration occurs downstream of the shock throughout the cometosheath. Good agreement of the observations with theory is evident for both P/Giacobini-Zinner and P/Halley.

Barbosa, D. D.↗

Identification of linear stochastic systems through projection filters

A novel method is presented for identifying a state-space model and a state estimator for linear stochastic systems from input and output data. The method is primarily based on the relationship between the state-space model and the finite-difference model of linear stochastic systems derived through projection filters. It is proved that least-squares identification of a finite difference model converges to the model derived from the projection filters. System pulse response samples are computed from the coefficients of the finite difference model.

Chen, Chung-Wen↗

Determining design gust loads for nonlinear aircraft similarity between methods based on matched filter theory and on stochastic simulation

This is a work-in-progress paper. It explores the similarity between the results from two different analysis methods - one deterministic, the other stochastic - for computing maximized and time-correlated gust loads for nonlinear aircraft. To date, numerical studies have been performed using two different nonlinear aircraft configurations. These studies demonstrate that results from the deterministic analysis method are realizable in the stochastic analysis method.

Scott, Robert C.↗

Stochastic modeling of crack initiation and short-crack growth under creep and creep-fatigue conditions

A simplified stochastic model is proposed for crack initiation and short-crack growth under creep and creep-fatigue conditions. Material inhomogeneity provides the random nature of crack initiation and early growth. In the model, the influence of microstructure is introduced by the variability of: (1) damage accumulation along grain boundaries, (2) critical damage required for crack initiation or growth, and (3) the grain-boundary length. The probabilities of crack initiation and growth are derived by using convolution integrals. The model is calibrated and used to predict the crack density and crack-growth rate of short cracks of 304 stainless steel under creep and creep-fatigue conditions. The mean-crack initiation lives are predicted to be within an average deviation of about 10 percent from the experimental results. The predicted comulative distributions of crack-growth rate follow the experimental data closely. The applicability of the simplified stochastic model is discussed and the future research direction is outlined.

Kitamura, Takayuki↗