• Title/Summary/Keyword: Linear stochastic differential equations

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Monte Carlo analysis of earthquake resistant R-C 3D shear wall-frame structures

  • Taskin, Beyza;Hasgur, Zeki
    • Structural Engineering and Mechanics
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    • v.22 no.3
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    • pp.371-399
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    • 2006
  • The theoretical background and capabilities of the developed program, SAR-CWF, for stochastic analysis of 3D reinforced-concrete shear wall-frame structures subject to seismic excitations is presented. Incremental stiffness and strength properties of system members are modeled by extended Roufaiel-Meyer hysteretic relation for bending while shear deformations for walls by Origin-Oriented hysteretic model. For the critical height of shear-walls, division to sub-elements is performed. Different yield capacities with respect to positive and negative bending, finite extensions of plastic hinges and P-${\delta}$ effects are considered while strength deterioration is controlled by accumulated hysteretic energy. Simulated strong motions are obtained from a Gaussian white-noise filtered through Kanai-Tajimi filter. Dynamic equations of motion for the system are formed according to constitutive and compatibility relations and then inserted into equivalent It$\hat{o}$-Stratonovich stochastic differential equations. A system reduction scheme based on the series expansion of eigen-modes of the undamaged structure is implemented. Time histories of seismic response statistics are obtained by utilizing the computer programs developed for different types of structures.

Average performance of risk-sensitive controlled orbiting satellite and three-degree-of-freedom structure

  • Won, Chang-Hee
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.444-447
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    • 1995
  • The satellite in a circular orbit about a planet with disturbances and a three-degree-of-freedom (3DOF) structure under seismic excitations are modeled by the linear stochastic differential equations. Then the risk-sensitive optimal control method is applied to those equations. The mean and the variance of the cost function varies with respect to the risk-sensitivity parameter, .gamma.$_{RS}$ . For a particular risk-sensitivity parameter value, risk-sensitive control reduces to LQG control. Furthermore, the derivation of the mean square value of the state and control action are given for a finite-horizon full-state-feedback risk-sensitive control system. The risk-sensitive controller outperforms a classical LQG controller in the mean square sense of the state and the control action.

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Tracking Filter Design for a Maneuvering target Using Jump Processes

  • Lim, Sang-Seok
    • Journal of Electrical Engineering and information Science
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    • v.3 no.3
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    • pp.373-384
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    • 1998
  • This paper presents a maneuvering target model with the maneuver dynamics modeled as a jump process of Poisson-type. The jump process represents the deterministic maneuver(or pilot commands) and is described by a stochastic differential equation driven by a Poisson process taking values a set of discrete states. Employing the new maneuver model along with the noisy observations described by linear difference equations, the author has developed a new linear, recursive, unbiased minimum variance filter, which is structurally simple, computationally efficient, and hence real-time implementable. Futhermore, the proposed filter does not involve a computationally burdensome technique to compute the filter gains and corresponding covariance matrices and still be able to track effectively a fast maneuvering target. The performance of the proposed filter is assessed through the numerical results generated from the Monte-Carlo simulation.

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Phase Transitions and Phase Diagram of the Island Model with Migration

  • Park, Jeong-Man
    • Journal of the Korean Physical Society
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    • v.73 no.9
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    • pp.1219-1224
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    • 2018
  • We investigate the evolutionary dynamics and the phase transitions of the island model which consists of subdivided populations of individuals confined to two islands. In the island model, the population is subdivided so that migration acts to determine the evolutionary dynamics along with selection and genetic drift. The individuals are assumed to be haploid and to be one of two species, X or Y. They reproduce according to their fitness values, die at random, and migrate between the islands. The evolutionary dynamics of an individual based model is formulated in terms of a master equation and is approximated by using the diffusion method as the multidimensional Fokker-Planck equation (FPE) and the coupled non-linear stochastic differential equations (SDEs) with multiplicative noise. We analyze the infinite population limit to find the phase transitions from the monomorphic state of one type to the polymorphic state to the monomorphic state of the other type as we vary the ratio of the fitness values in two islands and complete the phase diagram of our island model.

Passive control of seismically excited structures by the liquid column vibration absorber

  • Konar, Tanmoy;Ghosh, Aparna Dey
    • Structural Engineering and Mechanics
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    • v.36 no.5
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    • pp.561-573
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    • 2010
  • The potential of the liquid column vibration absorber (LCVA) as a seismic vibration control device for structures has been explored in this paper. In this work, the structure has been modeled as a linear, viscously damped single-degree-of-freedom (SDOF) system. The governing differential equations of motion for the damper liquid and for the coupled structure-LCVA system have been derived from dynamic equilibrium. The nonlinear orifice damping in the LCVA has been linearized by a stochastic equivalent linearization technique. A transfer function formulation for the structure-LCVA system has been presented. The design parameters of the LCVA have been identified and by applying the transfer function formulation the optimum combination of these parameters has been determined to obtain the most efficient control performance of the LCVA in terms of the reduction in the root-mean-square (r.m.s.) displacement response of the structure. The study has been carried out for an example structure subjected to base input characterized by a white noise power spectral density function (PSDF). The sensitivity of the performance of the LCVA to the coefficient of head loss and to the tuning ratio have also been examined and compared with that of the liquid column damper (LCD). Finally, a simulation study has been carried out with a recorded accelerogram, to demonstrate the effectiveness of the LCVA.

Effects of Phenotypic Variation on Evolutionary Dynamics

  • Kang, Yung-Gyung;Park, Jeong-Man
    • Journal of the Korean Physical Society
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    • v.73 no.11
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    • pp.1774-1786
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    • 2018
  • Phenotypic variation among clones (individuals with identical genes, i.e. isogenic individuals) has been recognized both theoretically and experimentally. We investigate the effects of phenotypic variation on evolutionary dynamics of a population. In a population, the individuals are assumed to be haploid with two genotypes : one genotype shows phenotypic variation and the other does not. We use an individual-based Moran model in which the individuals reproduce according to their fitness values and die at random. The evolutionary dynamics of an individual-based model is formulated in terms of a master equation and is approximated as the Fokker-Planck equation (FPE) and the coupled non-linear stochastic differential equations (SDEs) with multiplicative noise. We first analyze the deterministic part of the SDEs to obtain the fixed points and determine the stability of each fixed point. We find that there is a discrete phase transition in the population distribution when the probability of reproducing the fitter individual is equal to the critical value determined by the stability of the fixed points. Next, we take demographic stochasticity into account and analyze the FPE by eliminating the fast variable to reduce the coupled two-variable FPE to the single-variable FPE. We derive a quasi-stationary distribution of the reduced FPE and predict the fixation probabilities and the mean fixation times to absorbing states. We also carry out numerical simulations in the form of the Gillespie algorithm and find that the results of simulations are consistent with the analytic predictions.