• Journal of the Korean Society of Combustion
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• v.15 no.4
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• pp.15-21
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• 2010

The transported probability density function(PDF) model has been applied to simulate the turbulent nonpremixed piloted jet flame. To realistically account for the mixture fraction PDF informations on the turbulent non-premixed jet flame, the present Lagrangian PDF transport approach is based on the joint velocity-composition-turbulence frequency PDF formulation. The fluctuating velocity of stochastic fields is modeled by simplified Langevin model(SLM), turbulence frequency of stochastic fields is modeled by Jayesh-Pope model and effects of molecular diffusion are represented by the interaction by exchange with the mean (IEM) mixing model. To validate the present approach, the numerical results obtained by the joint velocity-composition-turbulence frequency PDF model are compared with experimental data in terms of the unconditional and conditional means of mixture fraction, temperature and species and PDFs.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.41-46
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• 1998

In this paper, a stochastic approach based on a Monte Carlo simulation method for the design of a guidance and control (G & C) system of an automatic landing flight experiment (ALFLEX) vehicle is presented. The aim of this study is to design a G & C system robust against uncertainties in the vehicular dynamics. In this study, uncertain parameters and disturbances are treated as random variables in the Monte Carlo simulation. Then, some controller gains in the G & C system are tuned to satisfy conditions concerning the states at touchdown. The proposed method was applied to the ALFLEX vehicle. The simulation results shored the effectiveness of the present approach.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.91-100
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• 2016

In this research, emergency vehicle dispatching problems faced with in the wake of massive natural disasters are considered. Here, the emergency vehicle dispatching problems can be regarded as a single machine stochastic scheduling problems, where the processing times are independently and identically distributed random variables, are considered. The objective of minimizing the expected number of tardy jobs, with distinct job due dates that are independently and arbitrarily distributed random variables, is dealt with. For these problems, optimal static-list policies can be found by solving corresponding assignment problems. However, for the special cases where due dates are exponentially distributed random variables, using a proposed dynamic programming approach is found to be relatively faster than solving the corresponding assignment problems. This so-called Pivot Dynamic Programming approach exploits necessary optimality conditions derived for ordering the jobs partially.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.554-565
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• 2012

In this paper, we study a cross-layer and end-to-end optimization problem for the integrated wireless and wireline network that consists of one wireline core network and multiple wireless access networks. We consider joint end-to-end flow control/distribution at the transport and network layers and opportunistic scheduling at the data link and physical layers. We formulate a single stochastic optimization problem and solve it by using a dual approach and a stochastic sub-gradient algorithm. The developed algorithm can be implemented in a distributed way, vertically among communication layers and horizontally among all entities in the network, clearly showing what should be done at each layer and each entity and what parameters should be exchanged between layers and between entities. Numerical results show that our cross-layer and end-to-end optimization approach provides more efficient resource allocation than the conventional layered and separated optimization approach.

• Journal of Korea Water Resources Association
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• v.30 no.6
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• pp.699-708
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• 1997

The effective unsaturated hydraulic conductivity in stratified soils is evaluated using a three-dimensional stochastic approach. Because of the disparity of the correlation scales in a stratified soil, the general stochastic equations are simplified. This allows analytical evaluation of generic expressions for the effective hydraulic conductivities. Simple asymptotic expressions, valid at particular ranges(wetting front, drying condition, wetting condition) of the mean flow characteristics, are also derived. An example of applying the derived theoretical result to a imaginaryl clay soil is presented. It reveals found that the effective unsaturated hydraulic conductivity showed large-scale hysteresis. Such large-scale hysteresis was produced by the spatial variability of hydraulic soil properties rather than hysteresis of the local parameters. In addition the results show that the effective hydraulic conductivities were larger in the case of accommodating heterogeneity of soil preperties rather than neglecting heterogeneity of soil properties.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2828-2835
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• 2015

In this paper, we analyse the effect of redundancy types and non-stop forwarding scheme on network service availability. We use stochastic reward net models as enabling modeling approach for the analytical evaluation. We first design stochastic reward nets for redundancy models with or without non-stop forwarding and then evaluate their availability using Stochastic Petri Net Package.

• Journal of Korean Society of Transportation
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• v.12 no.1
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• pp.43-54
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• 1994

The major concern of this paper is to investigate the properties of a stochastic equilibrium for each model system in terms of a consumer welfare measure. The primary assumption for this study is that a trip-maker would choose the trip from his origin zone which maximizes his personal welfare. This assumption, finally, leads to a singly constrained gravity model. The consumer welfare measure is derived from the concept of expected welfare of randomly sampled trip-makers. Each of the four different models considered in this paper is differentiated depending on the complexity of its model or the definition of its travel function. In this study, three different regions are chosen for the purpose of taking into account the effects of different zone-systems on the properties of a stochastic equilibrium : (i) Archerville region (5 zone) ; (ii) San Francisco Bay regions (30 zones) ; (iii) Houston, TX region (199 zones). It is concluded that almost identical, "global" consumer welfare values can be obtained in some cases of the gravity-type trip distribution models based on a stochastic equilibrium.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.450-453
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• 1998

Investigation is performed on the characteristics and new control technique for general form of dynamic system under the randomly disturbance. Also, a controller design method in stochastic domain in studied, which is preliminary result in the course of research on the control of stochastic system. The governing equation is derived via F-P-K approach in stochastic sense. A controller is designed in term of auto power density and cross power density.

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.71-94
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• 2009

In this paper a procedure for Monte Carlo simulation of univariate stationary stochastic processes with the aid of neural networks is presented. Neural networks operate model-free and, thus, circumvent the need of specifying a priori statistical properties of the process, as needed traditionally. This is particularly advantageous when only limited data are available. A neural network can capture the "pattern" of a short observed time series. Afterwards, it can directly generate stochastic process realizations which capture the properties of the underlying data. In the present study a simple feed-forward network with focused time-memory is utilized. The proposed procedure is demonstrated by examples of Monte Carlo simulation, by synthesis of future values of an initially short single process record.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.113-127
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• 2014

The stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum utility defined in terms of mean and variance by managing the constraint set and the objective function in an iterative manner. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.