• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.380-386
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• 2001

In considering the issue of safely during emergency building evacuations, it is important to be able to make accurate predictions about evacuation conditions and to be able to assess safety levels. Simulation techniques are often used to make predictions regarding evacuation conditions. The two main types of prediction models are crowd flow models and discrete models. We have developed an evacuation simulation system based on the discrete model which attempts to address the implementation problems of existing evacuation models. Our model incorporates characteristics such as evacuee profiles and spatial considerations, and is capable of dynamically predicting the behavior of individual evacuees. The simulation system is primarily designed for buildings in which many people are incapacitated and require helpers in order to evacuate, such as hospitals and facilities fur the elderly. We show the results that the evacuation simulation system was used to perform two trial simulations.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.74-79
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• 1996

This paper describes a methodology for the development of models of discrete event system(DES). The methodology is based on transformation of continuous state space into discrete one to homomorphically represent dynamics of continuous processes in discrete events. This paper proposes a formal structure which can couple DES models within a framework. The structure employs the DEVS formalism for the DES models. The proposed formal structure has been applied to develop a DEVS model for the human cardiovascular system. For this, the cardiac cycle is partitioned into a set of phases based on events identified through VisSim simulation in the CS of the electrical analog model. VisSim is the simulation tool of visual environment for developing continuous, discrete, and hybrid system models and performing dynamic simulation. For each phase, a CS of the electrical analog model for the cardiovascular system has been simulated by VisSim 2.0. To validate this model, first develop the DEVS model, then simulate the model in the DEVSIM++ environment. It has same simulation results for the data obtained from the CS simulation using VisSim. The comparison shows that the DEVS model represents dynamics of the human heart system at each phase of cardiac cycle.

• Journal of the Society of Naval Architects of Korea
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• v.47 no.2
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• pp.248-257
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• 2010

In this study, a discrete event and dynamic-based discrete time combined simulation modeling architecture, which can be used to calculate equations of motions among discrete events, is developed. This is composed of a command model, which is in charge of discrete event simulation, a numerical integration model, which finds motions by numerically integrating equations of motions, and an external force and control force model, which calculates the force and transmits it to the equations. Using this architecture, we can develop dynamic-based simulation by simply connecting and combining models, and handle simultaneously discrete event and discrete time simulation. To verify the efficiency of the architecture, it is applied to the submarine diving and surfacing simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.939-943
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• 2001

PLC(programmable Logic Controller)s essential components of modern automation systems encompassing almost every industry. Ladder Diagrams (LD) have been widely used in the design of such PLC since the LD is suitable for the modeling of the sequential control system. However, the synthesis of LD itself mainly depends on the experience of the industrial engineer, which may results in unstructured or inflexible design. Hence, in this paper, we propose a ladder diagram conversion algorithm which systematically produces LDs for PLCs based on discrete event models to enhance the structured and flexible design mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1041-1044
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• 1988

This paper considers the design problem of adaptive filters based an the state-space models for linear discrete-time stationary stochastic signal processes. The adaptive state estimator consists of both the predictor and the sequential prediction error estimator. The discrete Chandrasakhar filter developed by author is employed as the predictor and the nonlinear least-squares estimator is used as the sequential prediction error estimator. Two models are presented for calculating the parameter sensitivity functions in the adaptive filter. One is the exact model called the linear innovations model and the other is the simplified model obtained by neglecting the sensitivities of the Chandrasekhar X and Y functions with respect to the unknown parameters in the exact model.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.399-404
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• 2000

Functionally graded materials(FGMs) involve dual-phase graded layers in which two different constituents are mixed continuously and functionally according to a given volume fraction. For the analysis of their thermo-mechanical response, conventional homogenized methods have been widely employed in order to estimate equivalent material properties of the graded layer. However, such overall estimations are insufficient to accurately predict the local behavior. In this paper, we compare the thermo-elastic behaviors predicted by several overall material-property estimation techniques with those obtained by discrete analysis models utilizing the finite element method, for various volume fractions and loading conditions.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.55-64
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• 2024

In this study, we consider the sample size determination problem for clustered count data with many zeros. In general, zero-inflated Poisson and binomial models are commonly used for zero-inflated data; however, in real data the assumptions that should be satisfied when using each model might be violated. We calculate the required sample size based on a discrete Weibull regression model that can handle both underdispersed and overdispersed data types. We use the Monte Carlo simulation to compute the required sample size. With our proposed method, a unified model with a low failure risk can be used to cope with the dispersed data type and handle data with many zeros, which appear in groups or clusters sharing a common variation source. A simulation study shows that our proposed method provides accurate results, revealing that the sample size is affected by the distribution skewness, covariance structure of covariates, and amount of zeros. We apply our method to the pancreas disorder length of the stay data collected from Western Australia.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.5
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• pp.27-37
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• 2020

Structural optimization problems with discrete design variables require more function calculations (or finite element analyses) than those in the continuous design space. In this study, a method to find an optimal solution in the discrete design of the truss structure is presented, reducing the number of function calculations. Because a continuous optimal solution is the Karush-Kuhn-Tucker point that satisfies the optimality condition, it is assumed that the discrete optimal solution is around the continuous optimum. Then, response values such as weight, displacement, and stress are predicted using approximate models-referred to as hybrid metamodels-within specified design ranges. The discrete design method using the hybrid metamodels is used as a post-process of the continuous optimization process. Standard truss design problems of 10-bar, 25-bar, 15-bar, and 52-bar are solved to show the usefulness of this method. The results are compared with those of existing methods.

• Journal of Korea Multimedia Society
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• v.20 no.7
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• pp.1090-1101
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• 2017

This study analyzes spatial density and integration of Space Syntax and Discrete Event Simulation (DEVS) of complex system theory and analyzes spatial structure by property, type and depth. The aim of this study is to secure the validity of the theoretical application. The study evaluated the correlation between spatial density and integration by setting up eight types of analysis models. In addition, analyzed the correlation of structural characteristics and approached the application of discrete event simulation of spatial syntax theory. It is confirmed that the concept of integration of spatial syntax theory and analysis using discrete event simulation are valid as new spatial analysis methodology. Also expect that realistic and concrete predictions will be possible if discrete event simulation evolves into research for space allocation and space efficiency optimization.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.146-153
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• 2004

This paper presents a discrete analysis approach to investigate the performance of dual mass flywheel (DMF). In the discrete analysis, arcspring installed between the flywheels is modeled as N- discrete elements. Each element consists of mass, spring and nonlinear friction element. LuGre friction model is used to describe nonlinear friction characteristic. Based on the dynamic models of the DMF, clutch, engine, manual transmission and vehicle, a DMF performance simulator is developed using MATLAB Simulink. Simulation results of the engine speed, driveshaft torque and vehicle velocity are compared with test results. It is found that the discrete DMF model describes the vehicle behavior closely, especially during the clutch actuation period.