• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2A
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• pp.383-390
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• 2006

In this paper, a stochastic field that is compatible with Monte Carlo simulation is suggested for an expansion-based stochastic analysis scheme of weighted integral method. Through investigation on the way of affection of stochastic field function on the displacement vector in the series expansion scheme, it is noticed that the stochastic field adopted in the weighted integral method is not compatible with that appears in the Monte Carlo simulation. As generally recognized in the field of stochastic mechanics, the response variability is not a linear function of the coefficient of variation of stochastic field but a nonlinear function with increasing variability as the intensity of uncertainty is increased. Employing the stochastic field suggested in this study, the response variability evaluated by means of the weighted integral scheme is reproduced with high precision even for uncertain fields with moderately large coefficient of variation. Besides, despite the fact that only the first-order expansion is employed, an outstanding agreement between the results of expansion-based weighted integral method and Monte Carlo simulation is achieved.

• Bulletin of the Korean Mathematical Society
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• v.54 no.1
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• pp.17-28
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• 2017

In this paper, we deal with a class of mean-field backward stochastic differential equations (BSDEs) related to finite state, continuous time Markov chains. We obtain the existence and uniqueness theorem and a comparison theorem for solutions of one-dimensional mean-field BSDEs under Lipschitz condition.

• Structural Engineering and Mechanics
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• v.63 no.6
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• pp.837-846
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• 2017

An accurate calculation of the stochastic wind field is the foundation for analyzing wind-induced structure response and reliability. In this research, the spatial correlation of structural wind field was considered based on the time domain method. A method for calculating the stochastic wind field based on cross stochastic Fourier spectrum was proposed. A flowchart of the proposed methodology is also presented in this study to represent the algorithm and workflow. Along with the analysis of regional wind speed distribution, the wind speed time history sample was calculated, and the efficiency can therefore be verified. Results show that the proposed method and programs could provide an efficient simulation for the wind-induced structure response analysis, and help determine the related parameters easily.

• Proceedings of the KIEE Conference
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• 1985.07a
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• pp.127-130
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• 1985

A stochastic model to predict radio interference field as caused by corona discharges on high voltage transmission lines has been developed. This model is based on corona discharge distributed randomly in time and space. A stochastic model for the corona current induced by corona discharges on power lines is proposed. On the basis of the proposed corona current model, a rigorous analysis is presented to evaluate the radio interference (RI) field caused by corona discharges on a single conductor using the stochastic method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.6
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• pp.89-96
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• 1989

An improved method on texture coding, which is a part of the region growing based image coding, is presented in this paper. An image is segmented into stochastic regions which can be described as a stochastic random field, and non-stochastic ones in order to efficiently represent texture. In the texture coding and reconstruction, an autoregressive model is used for the stochastic regions, while a two-dimensional polynomial approximation is used for the non-stochastic ones. This proposed method leads to a better subjective quality, relatively higher compression ratio and shorter processing time for coding and reconstructing than the conventional method which uses only two-dimensional polynomial approximation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.12
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• pp.1138-1145
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• 2011

The internal broadband noise of a centrifugal fan in a household refrigerator is predicted using hybrid CAA techniques based on stochastic turbulent synthetic model. First, the unsteady flow field around the centrifugal fan is predicted using computational fluid dynamics(CFD) method. Then, the turbulent flow field is synthesized by applying the stochastic turbulent synthetic technique to the predicted flow field. The aerodynamic noise sources of the centrifugal fan are modeled on a basis of the synthesized turbulent field. Finally, the internal broadband noise of the centrifugal fan is predicted using the boundary element method(BEM) and the modeled sources. The predicted noise spectrum is compared with the experimental data. It is found that the predicted result closely follows the experimental data. The proposed method can be used as an effective tool for designing low-noise fans without expensive computational cost required generally for the LES and DNS simulations to resolve the turbulence flow field responsible for the broadband noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2011.10a
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• pp.627-632
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• 2011

The internal broadband noise of a centrifugal fan in a household refrigerator is predicted by using hybrid CAA technique based on stochastic turbulent synthetic model. First, the unsteady flow field around the centrifugal fan is predicted using Computational Fluid Dynamics (CFD) method. Then, the turbulent flow field is synthesized by applying the stochastic turbulent synthetic technique to the predicted flow field. The aerodynamic noise sources of the centrifugal fan are modeled on a basis of the synthesized turbulent field. Finally, the broadband noise of the centrifugal fan is predicted using Boundary Element Method (BEM) and the modeled sources. The predicted result is compared with the experimental data. It is found that the predicted result closely follows the experimental data. The proposed method can be used as an effective tool for designing low-noise fans without expensive computational cost required generally for the LES and DNS simulations to resolve the turbulence flow field responsible for the broadband noise.

• Journal of Korean Society of Transportation
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• v.9 no.1
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• pp.47-56
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• 1991

With respect to stochastic delays at linked signals the solid quantitative information has not been available as yet. On the basis of field data the values of "I" (variance-mean ration of flow) were related with the rate of flow. The stochastic delays with specific "I" values were obtained from the distribution of overflow queue, which were calculated by the use of Markov chains. This examination of the results led to the derivation of a simple method for calculating stochastic dclays through the introduction of "I" into Miller's model. The good agreement was shown between the model and the field. The relationships between the cycle lengths and delays were examinated in a large number of conditions with regard to degree of saturation. signal split and link length. Within the practical range of cycle length uniform delays were dominant and no critical point was found in terms of minimum, delay. In highly saturated conditions however the weight of stochastic delay is noticeable.

• Journal of the military operations research society of Korea
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• v.31 no.2
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• pp.28-44
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• 2005

The previous studies approach the field artillery fire scheduling problem as deterministic and do not explicitly include information on the potential scenario changes. Unfortunately, the effort used to optimize fire sequences and reduce the total time of engagement is often inefficient as the collected military intelligence changes. Instead of modeling the fire sequencing problem as deterministic model, we consider a stochastic artillery fire scheduling model and devise a solution methodology to integrate possible enemy attack scenarios in the evaluation of artillery fire sequences. The goal is to use that information to find robust solutions that withstand disruptions in a better way, Such an approach is important because we can proactively consider the effects of certain unique scheduling decisions. By identifying more robust schedules, cascading delay effects will be minimized. In this paper we describe our stochastic model for the field artillery fire sequencing problem and offer revised robust stochastic model which considers worst scenario first. The robust stochastic model makes the solution more stable than the general two-stage stochastic model and also reduces the computational cost dramatically. We present computational results demonstrating the effectiveness of our proposed method by EVPI, VSS, and Variances.

• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.