• 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.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.6
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• pp.447-454
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• 2017

A three-dimensional two-phase large eddy simulation(LES) has been conducted to investigate the breakup and atomization of liquid jets such as a diesel jet in parallel flow and water jet in cross flow. Gas-liquid two-phase flow was solved by a combined model of Eulerian for gas flow and Lagrangian for a liquid jet. Two stochastic breakup models were implemented to simulate the liquid column and droplet breakup process. The penetration depth and SMD(Sauter Mean Diameter) were analyzed, which was comparable with the experimental data.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.49-57
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• 2018

In a previous article, for analyzing a stochastic activity network, Cho proposed a method for estimating the moments (mean, variance, skewness, kurtosis) of the project completion time under the assumption that the durations of activities are independently and normally distributed. Developed in the present article is a method for estimating those moments for stochastic activity networks which allow any type of distributions for activity durations. The proposed method uses the moment matching approach to discretize the distribution function of activity duration, and then a discrete inverse-transform method to determine activity durations to be used for calculating the project completion time. The proposed method can be easily applied to large-sized activity networks, and computationally more efficient than Monte Carlo simulation, and its accuracy is comparable to that of Monte Carlo simulation.

• Nuclear Engineering and Technology
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• v.54 no.7
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• pp.2529-2539
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• 2022

Stochastic and an empirical Green's function (EGF) methods are preliminarily applied to simulate strong ground motions (SGMs) at seismic stations within nuclear power plant (NPP) sites in South Korea by an assumed large earthquake with M_W6.5 (scenario earthquake) on the causative fault of the 2016 Gyeongju earthquake with M_W5.5 (mainshock). In the stochastic method, a ratio of spectral amplitudes of observed and simulated waveforms for the mainshock is assumed to be an adjustment factor. In the EGF method, SGMs by the mainshock are simulated assuming SGMs by the 2016 Gyeongju earthquake with M_W5.0 (foreshock) as the EGF. To simulate SGMs by the scenario earthquake, a ratio of fault length to width is assumed to be 2:1 in the stochastic method, and SGMs by the mainshock are assumed to be EGF in the EGF method. The results are similar based on a bias of the simulated response spectra by the two methods, and the simulated response spectra by the two methods exceeded commonly standard design response spectra anchored at 0.3 g of NPP sites slightly at a frequency band above 4 Hz, but considerable attention to interpretation is required since it is an indirect comparison.

• 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.

• Earthquakes and Structures
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• v.3 no.5
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• pp.719-747
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• 2012

In this paper a novel approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. The appealing feature of the approach is that it is non-iterative and "one-step". This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various "two-step" approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (K-T) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra, given in a polynomial form, associated with the first passage problem for UHS compatible K-T and C-P uniformly modulated stochastic processes. Hopefully, the herein derived stochastic processes and median peak factor spectra can be used to facilitate the aseismic design of structures regulated by contemporary code provisions in a Monte Carlo simulation-based or stochastic dynamics-based context of analysis.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.581-609
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• 2012

In this paper a novel non-iterative approach is proposed to address the problem of deriving non-stationary stochastic processes which are compatible in the mean sense with a given (target) response (uniform hazard) spectrum (UHS) as commonly desired in the aseismic structural design regulated by contemporary codes of practice. This is accomplished by solving a standard over-determined minimization problem in conjunction with appropriate median peak factors. These factors are determined by a plethora of reported new Monte Carlo studies which on their own possess considerable stochastic dynamics merit. In the proposed approach, generation and treatment of samples of the processes individually on a deterministic basis is not required as is the case with the various approaches found in the literature addressing the herein considered task. The applicability and usefulness of the approach is demonstrated by furnishing extensive numerical data associated with the elastic design UHS of the current European (EC8) and the Chinese (GB 50011) aseismic code provisions. Purposely, simple and thus attractive from a practical viewpoint, uniformly modulated processes assuming either the Kanai-Tajimi (K-T) or the Clough-Penzien (C-P) spectral form are employed. The Monte Carlo studies yield damping and duration dependent median peak factor spectra, given in a polynomial form, associated with the first passage problem for UHS compatible K-T and C-P uniformly modulated stochastic processes. Hopefully, the herein derived stochastic processes and median peak factor spectra can be used to facilitate the aseismic design of structures regulated by contemporary code provisions in a Monte Carlo simulation-based or stochastic dynamics-based context of analysis.

• Korean Journal of Construction Engineering and Management
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• v.6 no.4 s.26
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• pp.80-90
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• 2005

Activity durations retain probabilistic and stochastic natures due to diverse factors causing the delay or acceleration of activity completion. These natures make the final project duration to be a random variable. These factors are the major source of financial risk. Extending the Stochastic Project Scheduling Simulation system (SPSS) developed in previous research; this research presents a method to estimate how the final project duration behaves when activity durations change randomly. The final project cost is estimated by considering the fluctuation of indirect cost, which occurs due to the delay or acceleration of activity completion, along with direct cost assigned to an activity. The final project cost is estimated by considering how indirect cost behaves when activity duration change. The method quantifies the amount of contingency to cover the expected delay of project delivery. It is based on the quantitative analysis to obtain the descriptive statistics from the simulation outputs (final project durations). Existing deterministic scheduling method apply an arbitrary figures to the amount of delay contingency with uncertainty. However, the stochastic method developed in this research allows computing the amount of delay contingency with certainty and certain degree of confidence. An example project is used to illustrate the quantitative analysis method using simulation. When the statistical location and shape of probability distribution functions defining activity durations change, how the final project duration and cost behave are ascertained using automated sensitivity analysis method

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2001.10a
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• pp.232-237
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• 2001

The evaluation of specimen thickness effect of fatigue crack growth life by the simulation of probabilistic fatigue crack growth is presented. In this paper, the material resistance to fatigue crack growth is treated as a spatial stochastic process, which varies randomly on the crack surface. Using the previous experimental data, the non-Gaussian(eventually Weibull, in this report) random fields simulation method is applied. This method is useful to estimate the probability distribution of fatigue crack growth life and the variability due to specimen thickness by simulating material resistance to fatigue crack growth along a crack path.

• Journal of Korean Institute of Industrial Engineers
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• v.2 no.1
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• pp.79-83
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• 1976

This paper deals with a computer simulation for the stochastic inventory system in which the decision rules are associated with the problem of forecasting uncertain demand, lead time, and amount of shortages. The model consists of mainly three parts; part I$\cdots$the model calculates the expected demand during lead time through the built-in subrou tine program for random number generator and the probability distribution of the demand, part II$\cdots$the model calculates all the possible expected shortages per lead time period, part III$\cdots$finally the model calculates all the possible total inventory cost over the simulation period. These total inventory costs are compared for searching the optimal inventory cost with the best ordering quantity and reorder point. An application example of the simulation program is given.