• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.3
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• pp.697-704
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• 1995

The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents the stochastic model of a nonlinear dynamic system with uncertain parameters under nonstationary stochastic inputs. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method and the second moment equation is numerically evaluated by stochastic process closure method, 4th cumulant neglect closure method and Runge-Kutta method. But the first and the second moment equations are coupled each other, so this equations are approximately evaluated by a iterative method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

• 한국연소학회:학술대회논문집
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• 2001.11a
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• pp.35-41
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• 2001

A second-order conditional moment closure(CMC) model is applied to the prediction of local extinction in a turbulent hydrocarbon diffusion flame and compared with direct numerical simulation(DNS) results for the flame. Combustion of a hydrocarbon fuel is described by a simple two-step mechanism. A second-order correction for conditional mean reaction rate terms is made by the assumed pdf method. The results show that the second-order closure is necessary for accurate prediction of intermediate species, while first-order CMC gives good predictions for fuel, oxidant, product and temperature. Conditional variances and covariances are well predicted during an extinction process while they are overpredicted during a reignition process.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.4
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• pp.127-134
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• 1995

The dynamic characteristics of a system can be critically influenced by system uncertainty, so the dynamic system must be analyzed stochastically in consideration of system uncertainty. This study presents a generalized stochastic model of dynamic system subjected to bot external and parametric nonstationary stochastic input. And this stochastic system is analyzed by a new stochastic process closure method and moment equation method. The first moment equation is numerically evaluated by Runge-Kutta method. But the second moment equation is founded to constitute an infinite coupled set of differential equations, so this equations are numerically evaluated by cumulant neglect closure method and Runge-Kutta method. Finally the accuracy of the present method is verified by Monte Carlo simulation.

• 한국연소학회:학술대회논문집
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• 2000.05a
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• pp.122-132
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• 2000

Computational fluid dynamic simulation is performed for the floating turbulent premixed flames stabilized in stagnation flows of Cho et al. [1] and Cheng and Shepherd [2]. They are both in the wrinkled flamelet regime far from the extinction limit with $u'/S^{0}_{L}$ less than unity. The turbulent flux is given in the first moment closure as a sum of the classical gradient flux due to turbulent motions and the countergradient flux due to thermal expansion. The parameter $N_{B}'s$ are greater than unity with the countergradient flux dominant over the gradient flux. The countergradient flux is assumed to be zero in $\bar{c}<0.05$. The flame surface density is modeled as a symmetric parabolic function with respect to $\bar{c}$. The product of the maximum flame surface density and the mean stretch factor is considered as a tuning constant to match the flame location. Good agreement is achieved with the measured $\tilde{w}$ and $\bar{c}$ profiles along the axis in both flames.

• 한국연소학회:학술대회논문집
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• 2002.11a
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• pp.11-17
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• 2002

The first-order conditional moment closure (CMC) model is applied to $CH_4$/Air turbulent jet diffusion flames(Sandia Flame D, E and F). The flow and mixing fields are calculated by fast chemistry assumption and a beta function pdf for mixture fraction. Reacting scalar fields are calculated by elliptic CMC formulation. The results for Flame D show reasonable agreement with the measured conditional mean temperature and mass fractions of major species, although with discrepancy on the fuel rich side. The discrepancy tends to increase as the level of local extinction increases. Second-order CMC may be needed for better prediction of these near-extinction flames.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.1
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• pp.43-51
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• 2000

The response statistics of a hinged-clamped beam under broad-band random excitation is investigated. The random excitation is applied at the nodal point of the second mode. By using Galerkin's method the governing equation is reduced to a system of nonautonomous nonlinear ordinary differential equations. A method based upon the Markov vector approach is used to generate a general first-order differential equation in the dynamic moment of response coordinates. By means of the Gaussian and non-Gaussian closure methods the dynamic moment equations for the random responses of the system are reduced to a system of autonomous ordinary differential equations. The case of two mode interaction is considered in order to compare it with the case of three mode interaction. The analytical results for two and three mode interactions are also compared with results obtained by Monte Carlo simulation.

• Journal of the Korean Society of Industry Convergence
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• v.3 no.2
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• pp.141-147
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• 2000

The nonlinear response statistics of an autoparameteric system under broad-band random excitation is investigated. The specific system examined is a vibration absorber system with internal resonance, which is known to be a good model for a variety of engineering systems, including ship motions with nonlinear coupling between pitching and rolling motions. The Fokker-Planck equations is used to generate a general first-order differential equation in the dynamic moment of response coordinates. By means of the Gaussian closure method the dynamic moment equations for the random responses of the system are reduced to a system of autonomous ordinary differential equations. The jump phenomenon was found by Gaussian closure method under random excitation.

• Journal of KSNVE
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• v.8 no.4
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• pp.715-722
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• 1998

An investigation into the stochastic bifurcation and response statistics of an autoparameteric system under broad-band random excitation is made. The specific system examined is a spring-pendulum system with internal resonance, which is known to be a good model for a variety of engineering systems, including ship motions with nonlinear coupling between pitching and rolling motions. The Fokker-Planck equations is used to genrage a general first-order differential equation in the dynamic moment of response coordinates. By means of the Gaussian and non-Gaussian closure methods the dynamic moment equations for the random responses of the system are reduced to a system of autonomous ordinanary differential equations. In view of equilibrium solutions of this system and their stability we examine the stochastic bifurcation and response statistics. The analytical results are compared with results obtained by Monte Carlo simulation.

• Journal of the Korean Society of Industry Convergence
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• v.4 no.2
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• pp.133-139
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• 2001

The nonlinear response statistics of an spring-pendulum system with internal resonance under narrow band random excitation is investigated analytically- The center frequency of the filtered excitation is selected to be close to natural frequency of directly excited spring mode. The Fokker-Planck equations is used to generate a general first-order differential equation in the dynamic moment of response coordinates. By means of the Gaussian closure method the dynamic moment equations for the random responses of the system are reduced to a system of autonomous ordinary differential equations. The nonlinear phenomena, such as jump and multiple solutions, under narrow band random excitation were found by Gaussian closure method.

• Structural Engineering and Mechanics
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• v.23 no.6
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• pp.599-613
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• 2006

A method for the dynamical analysis of FE discretized uncertain linear and nonlinear structures is presented. This method is based on the moment equation approach, for which the differential equations governing the response first and second-order statistical moments must be solved. It is shown that they require the cross-moments between the response and the random variables characterizing the structural uncertainties, whose governing equations determine an infinite hierarchy. As a consequence, a closure scheme must be applied even if the structure is linear. In this sense the proposed approach is approximated even for the linear system. For nonlinear systems the closure schemes are also necessary in order to treat the nonlinearities. The complete set of equations obtained by this procedure is shown to be linear if the structure is linear. The application of this procedure to some simple examples has shown its high level of accuracy, if compared with other classical approaches, such as the perturbation method, even for low levels of closures.