• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.1
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• pp.116-127
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• 1994

A reliability analysis model for the frame structure which grafts the discretized ideal plastic method to the stochastic finite element method is introduced. The proposed method simmulates realistically the sequencial occurrence of plastic hinges and yields the probability of failure directly from the geometrical and material properties of a frame structure. The presented method can also take into account the uncertainties inherent in loads and resisten- ces through the stochastic finite element technique. The analysis results are compared with those of the Monte Carlo Simmulation, the Bound Theory, and the fs-unzipping method, and show good agreement.

• Computational Structural Engineering
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• v.8 no.1
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• pp.127-136
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• 1995

In this paper the stochastic FE analysis considering the material and geometrical property of the plate structure is performed by the weighted integral method. To consider the stochasity of the material and geometrical property, the stochastic field is assumed respectively. The mean value of the stochastic field is 0 and the value of variance is assumed as 0.1. The characteristics of the assumed stochastic field is represented by auto-correlation function. This auto-correlation function is used in evaluating the response variability of the plate structure. In this study a new auto-correlation function is derived to concern the uncertainty of the plate thickness. The newly derived auto-correlation function is a function of auto-correlation function and coefficient of variation of the assumed stochastic field. The two results, obtained by proposed Weighted Integral method and Monte Carlo Simulation method, are coincided with each other and these results are almost equal to the theoretical result that is derived in this study. In the case of considering the variability of plate thickness, the obtained result is well coincide with those of Lawrence and Monte Carlo simulation.

• Structural Engineering and Mechanics
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• v.28 no.2
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• pp.129-152
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• 2008

This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.

• Journal of Korea Water Resources Association
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• v.35 no.4 s.129
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• pp.385-395
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• 2002

A stochastic model using FOEA(First-Order Error-Analysis) and Monte Carlo Method is developed to predict water quality variation in a river. A sensitivity analysis using influential matrix is performed to determine the significant reaction coefficients. Also the BFGS (Broyden-Fletcher-Goldfarb-Shanno) optimization method is applied to estimate the optimal values of the major reaction coefficients. The developed stochastic model is applied to the real study reach and the results are agreed well with those of deterministic analysis. The process for analyzing the uncertainties of the discharge, water quality and reaction coefficients of headwater and tributaries is included in the model to estimate the influence on the water quality variation at downstream. The extents of contribution of the uncertainties influencing on the total uncertainty can be evaluated from the results of the model.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.21-33
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• 2006

The reliability analysis can be conducted more effectively by formulating the stochastic finite element method suitable for the reliability theory about the cable stayed bridge. After conducting the initial equilibrium analysis of the cable stayed bridge, the program which can conduct the linear and nonlinear stochastic finite element analysis using the perturbation method and the reliability analysis considered to the correlation of the random variable is developed. Using the results of this program about the cable stayed bridge, the characteristic of the node displacement, element force and cable tension according to the correlation of the random variable is investigated quantitatively. Also the reliability index and the failure probability are examined by the compounding the correlation of the random variable.

• Structural Engineering and Mechanics
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• v.25 no.3
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• pp.275-289
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• 2007

In this paper a brief overview of methods to assess the reliability of mechanical systems and structures is presented. A selection of computational procedures, stochastic structural dynamics, stochastic fatigue crack growth and reliability based optimization are discussed. It is shown that reliability based methods may form the basis for a rational decision making.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.390-392
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• 2010

Mobile grid system supports the integration mobile devices as grid resources. Availability of mobile resources changes dynamically in mobile grid system. Stochastic reward nets (SRN) is an extension of stochastic Petri nets and provides compact modeling facilities for system analysis. We build the SRN model to represent availability of mobile resources with disconnected operation service.

• Korean Journal of Mathematics
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• v.14 no.2
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• pp.185-202
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• 2006

In this paper, using the Black-Scholes analysis, we will derive the partial differential equation of convertible bonds with both non-stochastic and stochastic interest rate. We also find numerical solutions of convertible bonds equation with known interest rate using the finite element method.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.38-49
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• 2012

In this study, we analyze statistical characteristics of influent water quality in Daejeon waste water treatment plant and apply a stochastic model for data generation. In the analysis, the influent water quality data from year 2003 to 2008, except for year 2006, are used. Among water quality variables, we find strong correlations between BOD and T-N; T-N and T-P; BOD and T-P; $COD_{Mn}$ and T-P; and BOD and $COD_{Mn}$. We also find that different water quality variables follow different theoretical probability distribution functions, which also depends on whether the seasonal cycle is removed. Finally, we generate the influent water quality data using the multi-season 1st Markov model (Thomas-Fiering model). With model parameters calibrated for the period 2003~2005, the generated data for 2007~2008 are well compared with observed data showing good agreement in general. BOD and T-N are underestimated by the stochastic model. This is mainly due to the statistical difference in observed data itself between two periods of 2003~2005 and 2007~2008. Therefore, we expect the stochastic model can be applied with more confidence in the case that the data follows stationary pattern.

• Tunnel and Underground Space
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• v.11 no.2
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• pp.156-166
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• 2001

A stochastic continuum(SC) modeling technique was developed to simulate the groundwater flow pathway in fractured rocks. This model was developed to overcome the disadvantageous points of discrete fracture network(DFN) modes which has the limitation of fracture numbers. Besides, SC model is able to perform probabilistic analysis and to simulate the conductive groundwater pathway as discrete fracture network model. The SC model was formulated based on the discrete fracture network(DFN) model. The spatial distribution of permeability in the stochastic continuum model was defined by the probability distribution and variogram functions defined from the permeabilities of subdivided smaller blocks of the DFN model. The analysis of groundwater travel time was performed to show the consistency between DFN and SC models by the numerical experiment. It was found that the stochastic continuum modes was an appropriate way to provide the probability density distribution of groundwater velocity which is required for the probabilistic safety assessment of a radioactive waste disposal facility.