• Bulletin of the Korean Mathematical Society
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• v.42 no.2
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• pp.231-244
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• 2005

We derive a comparison theorem for solutions of the following stochastic partial differential equations in a Hilbert space H. $$Lu^i=\alpha(u^i)M(t,\; x)+\beta^i(u^i),\;for\;i=1,\;2,$$ $where\;Lu^i=\;\frac{\partial u^i}{\partial t}\;-\;Au^{i}$, A is a linear closed operator on Hand M(t, x) is a spatially homogeneous Gaussian noise with covariance of a certain form. We are going to show that if $\beta^1\leq\beta^2\;then\;u^1{\leq}u^2$ under some conditions.

• 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.

• Clean Technology
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• v.7 no.2
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• pp.119-126
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• 2001

The prediction of ozone formation was studied using the neural network and the stochastic method. Parameter estimation method and artificial neural network(ANN) method were employed in the stochastic scheme. In the parameter estimation method, extended least squares(ELS) method and recursive maximum likelihood(RML) were used to achieve the real time parameter estimation. Autoregressive moving average model with external input(ARMAX) was used as the ozone formation model for the parameter estimation method. ANN with 3 layers was also tested to predict the ozone formation. To demonstrate the performance of the ozone formation prediction schemes used in this work, the prediction results of ozone formation were compared with the real data. From the comparison it was found that the prediction schemes based on the parameter estimation method and ANN method show an acceptable accuracy with limited prediction horizon.

• 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.

• Health Policy and Management
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• v.31 no.4
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• pp.491-507
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• 2021

Background: This study aims to measure regional healthcare differences in Korea, and define relatively underserved areas. Methods: We employed position value for relative comparison index (PARC) to measure the healthcare status of 250 areas using 137 indicators in five following domains: healthcare demand, supply, accessibility, service utilization, and outcome. We performed a sensitivity analysis using t-SNE (t-distributed stochastic neighboring embedding). Results: Based on PARC values, 83 areas were defined as relatively underserved areas, 49 of which were categorized as moderate and 34 as severe. The provincial regions with the most underserved areas were Gyeongbuk (16 areas), Gangwon (13), Jeonnam (13), and Gyeongnam (12). Conclusion: This study suggests a relative comparison approach to define relatively underserved areas in healthcare. Further studies incorporating various perspectives and methods are required for policy implications.

• Magazine of the Korean Society of Agricultural Engineers
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• v.32 no.E
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• pp.59-66
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• 1990

Abstract The formulation of the probabilistic finite element method was briefly reviewed. The method was implemented into a computer program for frame analysis which has the same analogy as finite element analysis. Another program for Monte Carlo simulation of finite element analysis was written. Two sample structures were assumed and analized. The characteristics of the second moment statistics obtained by the probabilistic finite element method was examined through numerical studies. The applicability and limitation of the method were also evaluated in comparison with the data generated by Monte Carlo simulation.

• Computational Structural Engineering
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• v.5 no.1
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• pp.97-108
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• 1992

This paper is an attempt to account for the uncertainty of the residual strength in the reliability analysis of structural systems. For this purpose the stochastic finite element method(SFEM) is linked to the system reliability analysis procedure. The stochastic finite element is known to be able to a more explicitly consider the effect of uncerainties of material and geometric variables on those of load effects in structural analysis procedure. The method has been applied to system as well as component reliability analysis of a plane structure. Comparison of the results by the present approach is made with the method in which the residual strength of failed component is treated as deterministic variable. Several case studies have been carried to show the effect of uncertainty in residual strength of a member after failure. Is has been conformed that reidual strength very much affect the system reliability level. It can be, hence, concluded that the uncertainties in the post-ultirnate behaviour may have to be taken into account in the system reliability analysis for a better a ssessment of the system reliability especially for a structure of which member behaviour is modelled as asemi-brittle model. And then the stochastic finite element method can efficiently evaluate the system reliability.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.637-648
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• 2007

This paper presents a sensor fusion method based on indirect Kalman filter(IKF) for error compensation of low-cost inertial sensors and its application to the determination of attitude and position of small flying robots. First, the analysis of the measurement error characteristics to zero input is performed, focusing on the bias due to the temperature variation, to derive a simple nonlinear bias model of low-cost inertial sensors. Moreover, from the experimental results that the coefficients of this bias model possess non-deterministic (stochastic) uncertainties, the bias of low-cost inertial sensors is characterized as consisting of both deterministic and stochastic bias terms. Then, IKF is derived to improve long term stability dominated by the stochastic bias error, fusing low-cost inertial sensor measurements compensated by the deterministic bias model with non-inertial sensor measurement. In addition, in case of using intermittent non-inertial sensor measurements due to the unreliable data link, the upper and lower bounds of the state estimation error covariance matrix of discrete-time IKF are analyzed by solving stochastic algebraic Riccati equation and it is shown that they are dependant on the throughput of the data link and sampling period. To evaluate the performance of proposed method, experimental results of IKF for the attitude determination of a small flying robot are presented in comparison with that of extended Kaman filter which compensates only deterministic bias error model.

• IE interfaces
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• v.13 no.3
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• pp.424-430
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• 2000

Supply chain management (SCM) is an area that has recently received a great deal of attention in the business community. While SCM is relatively new, the idea of coordinated planning is not. During the last decades, many researchers have investigated multi-stage inventory problems. However, only a few papers address the problem of cost-optimal coordination of multi-stage inventory control with respect to service measures. Even published approaches have a shortcoming in dealing with a delivery lead time consisted of a shipping time and a waiting time. Assumed that there is no waiting time, or that the delivery lead time is implicitly compounded of a shipping time and a waiting time, the problem is often simplified into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem at all installations. This paper presents a simulation-based heuristic algorithm and a comparison with others for the problem that cannot be decomposed into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem because the waiting time ties together all stages. The comparison shows that the simulation-based heuristic algorithm performs better than other approaches in saving average inventory cost for both Poisson and Normal demands.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.3
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• pp.117-129
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• 1993

This study was conducted to get reasonable and abundant hydrological time series of monthly flows simulated by a best fitting stochastic simulation model for the establishment of rational design and the rationalization of management for agricultural hydraulic structures including reservoirs. Comparative analysis carried out for both statistical characteristics and synthetic monthly flows simulated by the multi-season first order Markov model based on Gamma distribution which is confirmed as good one in the first report of this study and by Harmonic synthetic model analyzed in this report for the six watersheds of Yeong San and Seom Jin river systems. 1.Arithmetic mean values of synthetic monthly flows simulated by Gamma distribution are much closer to the results of the observed data than those of Harmonic synthetic model in the applied watersheds. 2.In comparison with the coefficients of variation, index of fluctuation for monthly flows simulated by two kinds of synthetic models, those based on Gamma distribution are appeared closer to the observed data than those of Harmonic synthetic model both in Yeong San and Seom Jin river systems. 3.It was found that synthetic monthly flows based on Gamma distribution are considered to give better results than those of Harmonic synthetic model in the applied watersheds. 4.Continuation studies by comparison with other simulation techniques are to be desired for getting reasonable generation technique of synthetic monthly flows for the various river systems in Korea.