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At least 235 records · Page 13

A simulation of remote sensor systems and data processing algorithms for spectral feature classification

A computational model of the deterministic and stochastic processes involved in multispectral remote sensing was designed to evaluate the performance of sensor systems and data processing algorithms for spectral feature classification. Accuracy in distinguishing between categories of surfaces or between specific types is developed as a means to compare sensor systems and data processing algorithms. The model allows studies to be made of the effects of variability of the atmosphere and of surface reflectance, as well as the effects of channel selection and sensor noise. Examples of these effects are shown.

Arduini, R. F.↗

Structural considerations for a software life cycle dynamic simulation model

This paper presents the results of a preliminary study into the prospects for simulating the software implementation and maintenance life cycle process, with the aim of producing a computerized tool for use by management and software engineering personnel in project planning, tradeoff studies involving product, environmental, situational, and technological factors, and training. The approach taken is the modular application of a 'flow of resource' concept to the systems dynamics simulation modeling technique. The software life cycle process is represented as a number of stochastic, time-varying, interacting work tasks that each achieves one of the project milestones. Each task is characterized by the item produced, the personnel applied, and the budgetary profile.

Tausworthe, R. C.↗

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 acceleration in the transrelativistic region and pion production in solar flares

The stochastic Fermi acceleration spectrum in the transrelativistic region obtained from a Monte-Carlo simulation for an energy-independent alpha(T) is much harder than the extension of the nonrelativistic analytic spectrum to this energy range for the same alpha(T). The latter, with alpha(T) = 0.043, was used to model the pion and nuclear line emissions for the impulsive phase of the 3 Jun. 1982 flare, as well as the 2.223 MeV emission from this flare. We find that the ratios of these three emissions for the Monte-Carlo spectrum with alpha(T) = 0.028 are essentially the same as those for the analytical spectrum with alpha(T) = 0.043. We also find that the acceleration time from approximately 30 MeV to approximately 1 GeV is less than or approximately = 10 s, consistent with the observations of the 3 Jun. 1982 flare.

Miller, James A.↗

Particle acceleration in cosmic plasmas; Proceedings of the Workshop, Bartol Research Inst., Newark, DE, Dec. 4-6, 1991

The present volume on particle acceleration in cosmic plasmas discusses transport theory, particle acceleration in the sun, heliosphere, and galaxy, particle acceleration at nonrelativistic shocks, and stochastic particle acceleration. Attention is given to particle acceleration in relativistic flows and shocks, simulations, composition and sources of high-energy cosmic rays, electron acceleration, and observation priorities and perspectives. Topics addressed include particle acceleration in the magnetosphere, particle transport from a turbulence perspective, numerical simulations of time-dependent cosmic ray mediated shocks, and solar flare plasma. Also discussed are relativistic shock waves and the excitation of plerions, ion acceleration at collisionless shock interactions, ultrahigh-energy cosmic rays from Fanaroff Riley, and constraints on electron acceleration in the Crab Nebula.

Zank, G. P.↗

Direct Numerical Simulation of Turbulent Condensation in Clouds

In this brief, we investigate the turbulent condensation of a population of droplets by means of a direct numerical simulation. To that end, a coupled Navier-Stokes/Lagrangian solver is used where each particle is tracked and its growth by water vapor condensation is monitored exactly. The main goals of the study are to find out whether turbulence broadens the droplet size distribution, as observed in in situ measurements. The second issue is to understand if and for how long a correlation between the droplet radius and the local supersaturation exists for the purpose of modeling sub-grid scale microphysics in cloud-resolving codes. This brief is organized as follows. In Section 2 the governing equations are presented, including the droplet condensation model. The implementation of the forcing procedure is described in Section 3. The simulation results are presented in Section 4 together with a sketch of a simple stochastic model for turbulent condensation. Conclusions and the main outcomes of the study are given in Section 5.

Shariff, K.↗

Tectonic-Climate Interactions in Action Orogenic Belts: Quantification of Dynamic Topography with SRTM data

This project was undertaken to examine the approach to steady state in collisional mountain belts. Although the primary thrust of this grant was to look at larger collisional mountain belts, such as the Himalaya, the Tien Shan, and Southern Alps, we began by looking at smaller structures represented by growing and propagating folds. Like ranges that are evolving toward a topographic steady state, these folds undergo a series of morphologic changes as they are progressively uplifted and eroded. We wanted to document the nature of these changes and to try to discern some of the underlying controls on them. We initially focused on the Wheeler Ridge anticline in southern California. Subsequently, we progressed to looking at the topographic development and the effects of differential uplift and glaciation on the Kyrgyz Range in the northern Tien Shan. This range is unusual inasmuch as it is transformed along its length from a simple uplift with a largely preserved Mesozoic erosion surface arching across it to a highly dissected and heavily glaciated uplift in the region where uplift has been sustained at higher rates over longer intervals. In efforts to understand the distribution of erosion rates at 10(exp 3) - 10(exp 5) year time scales, cosmogenic radionuclide (CRN) concentrations have been gaining increasingly widespread usage (Brown et al., 1995; Riebe et al., 2004; Riebe et al., 2001; Vance et al., 2003). Most studies to date, however, have been conducted in slowly eroding ranges. In rapidly eroding mountains where landslides deliver most of the sediments to the rivers, we hypothesized that CRN concentrations could be highly perturbed by the stochastic processes of landsliding. Therefore, we undertook the development of a numerical model that simulated the effects of both landsliding and grain-by-grain attrition within fluvial catchments. This modeling effort has shown the effects of catchment size and erosion rate on CRN concentrations and allows a prediction of where to sample to obtain the optimal erosion rate estimates using CRN techniques. Finally, we developed computational techniques to operate on DEMs to extract useful information that would enable quantification of climate-erosion interactions. In particular, we worked on rapid techniques to define catchments of any given range of sizes, to extract channel gradients, to combine precipitation information to calculate discharge, and to utilize various stream-power models to determine the erosional energy within any given catchment within a transect. We briefly describe results from Wheeler Ridge, the Kyrgyz Range, the Nepal Himalaya, and our numerical modeling.

Burbank, Douglas W.↗

Quantum Decision-Maker

A quantum device simulating human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and a classical neural nets describing evolution of probabilities of these processes which represent the mental dynamics.

quantum↗

Simulation of rotor blade element turbulence

A piloted, motion-based simulation of Sikorsky's Black Hawk helicopter was used as a platform for the investigation of rotorcraft responses to vertical turbulence. By using an innovative temporal and geometrical distribution algorithm that preserved the statistical characteristics of the turbulence over the rotor disc, stochastic velocity components were applied at each of twenty blade-element stations. This model was implemented on NASA Ames' Vertical Motion Simulator (VMS), and ten test pilots were used to establish that the model created realistic cues. The objectives of this research included the establishment of a simulation-technology basis for future investigation into real-time turbulence modeling. This goal was achieved; our extensive additions to the rotor model added less than a 10 percent computational overhead. Using a VAX 9000 computer the entire simulation required a cycle time of less than 12 msec. Pilot opinion during this simulation was generally quite favorable. For low speed flight the consensus was that SORBET (acronym for title) was better than the conventional body-fixed model, which was used for comparison purposes, and was determined to be too violent (like a washboard). For high speed flight the pilots could not identify differences between these models. These opinions were something of a surprise because only the vertical turbulence component on the rotor system was implemented in SORBET. Because of the finite-element distribution of the inputs, induced outputs were observed in all translational and rotational axes. Extensive post-simulation spectral analyses of the SORBET model suggest that proper rotorcraft turbulence modeling requires that vertical atmospheric disturbances not be superimposed at the vehicle center of gravity but, rather, be input into the rotor system, where the rotor-to-body transfer function severely attenuates high frequency rotorcraft responses.

Mcfarland, R. E.↗

Evolutionary Design of a Phased Array Antenna Element

We present an evolved S-band phased array antenna element design that meets the requirements of NASA's TDRS-C communications satellite scheduled for launch early next decade. The original specification called for two types of elements, one for receive only and one for transmit/receive. We were able to evolve a single element design that meets both specifications thereby simplifying the antenna and reducing testing and integration costs. The highest performance antenna found using a genetic algorithm and stochastic hill-climbing has been fabricated and tested. Laboratory results are largely consistent with simulation. Researchers have been investigating evolutionary antenna design and optimization since the early 1990s, and the field has grown in recent years its computer speed has increased and electromagnetic simulators have improved. Many antenna types have been investigated, including wire antennas, antenna arrays and quadrifilar helical antennas. In particular, our laboratory evolved a wire antenna design for NASA's Space Technology 5 (ST5) spacecraft. This antenna has been fabricated, tested, and is scheduled for launch on the three spacecraft in 2006.

Globus, Al↗

Quantum Decision Maker Theory and Simulation

A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which represent the motor dynamics, and of classical neural nets describing the evolution of probabilities of these processes which represent the mental dynamics.

Quantum↗

GERMcode: A Stochastic Model for Space Radiation Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and high charge and energy (HZE) particles that have been studied at the NASA Space Radiation Laboratory (NSRL) for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of HZE particles in tissue and shielding materials is made with a stochastic approach that includes both particle track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections. For NSRL applications, the GERMcode evaluates a set of biophysical properties, such as the Poisson distribution of particles or delta-ray hits for a given cellular area and particle dose, the radial dose on tissue, and the frequency distribution of energy deposition in a DNA volume. By utilizing the ProE/Fishbowl ray-tracing analysis, the GERMcode will be used as a bi-directional radiation transport model for future spacecraft shielding analysis in support of Mars mission risk assessments. Recent radiobiological experiments suggest the need for new approaches to risk assessment that include time-dependent biological events due to the signaling times for activation and relaxation of biological processes in cells and tissue. Thus, the tracking of the temporal and spatial distribution of events in tissue is a major goal of the GERMcode in support of the simulation of biological processes important in GCR risk assessments. In order to validate our approach, basic radiobiological responses such as cell survival curves, mutation, chromosomal aberrations, and representative mouse tumor induction curves are implemented into the GERMcode. Extension of these descriptions to other endpoints related to non-targeted effects and biochemical pathway responses will be discussed.

Kim, Myung-Hee Y.↗

A Fast Monte Carlo Method for Model-Based Prognostics Based on Stochastic Calculus

This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.

stochastic calculus↗

A coordination theory for intelligent machines

A formal model for the coordination level of intelligent machines is established. The framework of the coordination level investigated consists of one dispatcher and a number of coordinators. The model called coordination structure has been used to describe analytically the information structure and information flow for the coordination activities in the coordination level. Specifically, the coordination structure offers a formalism to (1) describe the task translation of the dispatcher and coordinators; (2) represent the individual process within the dispatcher and coordinators; (3) specify the cooperation and connection among the dispatcher and coordinators; (4) perform the process analysis and evaluation; and (5) provide a control and communication mechanism for the real-time monitor or simulation of the coordination process. A simple procedure for the task scheduling in the coordination structure is presented. The task translation is achieved by a stochastic learning algorithm. The learning process is measured with entropy and its convergence is guaranteed. Finally, a case study of the coordination structure with three coordinators and one dispatcher for a simple intelligent manipulator system illustrates the proposed model and the simulation of the task processes performed on the model verifies the soundness of the theory.

Wang, Fei-Yue↗

Dynamical Signatures of Living Systems

One of the main challenges in modeling living systems is to distinguish a random walk of physical origin (for instance, Brownian motions) from those of biological origin and that will constitute the starting point of the proposed approach. As conjectured, the biological random walk must be nonlinear. Indeed, any stochastic Markov process can be described by linear Fokker-Planck equation (or its discretized version), only that type of process has been observed in the inanimate world. However, all such processes always converge to a stable (ergodic or periodic) state, i.e., to the states of a lower complexity and high entropy. At the same time, the evolution of living systems directed toward a higher level of complexity if complexity is associated with a number of structural variations. The simplest way to mimic such a tendency is to incorporate a nonlinearity into the random walk; then the probability evolution will attain the features of diffusion equation: the formation and dissipation of shock waves initiated by small shallow wave disturbances. As a result, the evolution never "dies:" it produces new different configurations which are accompanied by an increase or decrease of entropy (the decrease takes place during formation of shock waves, the increase-during their dissipation). In other words, the evolution can be directed "against the second law of thermodynamics" by forming patterns outside of equilibrium in the probability space. Due to that, a specie is not locked up in a certain pattern of behavior: it still can perform a variety of motions, and only the statistics of these motions is constrained by this pattern. It should be emphasized that such a "twist" is based upon the concept of reflection, i.e., the existence of the self-image (adopted from psychology). The model consists of a generator of stochastic processes which represents the motor dynamics in the form of nonlinear random walks, and a simulator of the nonlinear version of the diffusion equation which represents the mental dynamics. It has been demonstrated that coupled mental-motor dynamics can simulate emerging self-organization, prey-predator games, collaboration and competition, "collective brain," etc.

Zak, M.↗

Unsupervised Detection of Planetary Craters by a Marked Point Process

With the launch of several planetary missions in the last decade, a large amount of planetary images is being acquired. Preferably, automatic and robust processing techniques need to be used for data analysis because of the huge amount of the acquired data. Here, the aim is to achieve a robust and general methodology for crater detection. A novel technique based on a marked point process is proposed. First, the contours in the image are extracted. The object boundaries are modeled as a configuration of an unknown number of random ellipses, i.e., the contour image is considered as a realization of a marked point process. Then, an energy function is defined, containing both an a priori energy and a likelihood term. The global minimum of this function is estimated by using reversible jump Monte-Carlo Markov chain dynamics and a simulated annealing scheme. The main idea behind marked point processes is to model objects within a stochastic framework: Marked point processes represent a very promising current approach in the stochastic image modeling and provide a powerful and methodologically rigorous framework to efficiently map and detect objects and structures in an image with an excellent robustness to noise. The proposed method for crater detection has several feasible applications. One such application area is image registration by matching the extracted features.

Troglio, G.↗

A Stochastic Model of Space Radiation Transport as a Tool in the Development of Time-Dependent Risk Assessment

A new computer model, the GCR Event-based Risk Model code (GERMcode), was developed to describe biophysical events from high-energy protons and heavy ions that have been studied at the NASA Space Radiation Laboratory (NSRL) [1] for the purpose of simulating space radiation biological effects. In the GERMcode, the biophysical description of the passage of heavy ions in tissue and shielding materials is made with a stochastic approach that includes both ion track structure and nuclear interactions. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model [2]. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections

Kim, Myung-Hee Y.↗