• Title, Summary, Keyword: simulation model

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A study for production simulation model generation system based on data model at a shipyard

  • Back, Myung-Gi;Lee, Dong-Kun;Shin, Jong-Gye;Woo, Jong-Hoon
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.8 no.5
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    • pp.496-510
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    • 2016
  • Simulation technology is a type of shipbuilding product lifecycle management solution used to support production planning or decision-making. Normally, most shipbuilding processes are consisted of job shop production, and the modeling and simulation require professional skills and experience on shipbuilding. For these reasons, many shipbuilding companies have difficulties adapting simulation systems, regardless of the necessity for the technology. In this paper, the data model for shipyard production simulation model generation was defined by analyzing the iterative simulation modeling procedure. The shipyard production simulation data model defined in this study contains the information necessary for the conventional simulation modeling procedure and can serve as a basis for simulation model generation. The efficacy of the developed system was validated by applying it to the simulation model generation of the panel block production line. By implementing the initial simulation model generation process, which was performed in the past with a simulation modeler, the proposed system substantially reduced the modeling time. In addition, by reducing the difficulties posed by different modeler-dependent generation methods, the proposed system makes the standardization of the simulation model quality possible.

Submarine Diving Simulation Using a DEVS-HLA Interface based on the Combined Discrete Event and Discrete Time Simulation Model Architecture (이산 사건/이산 시간 혼합형 시뮬레이션 모델 구조 기반 DEVS-HLA 인터페이스를 이용한 잠수함의 잠항 시뮬레이션)

  • Cha, Ju-Hwan;Ha, Sol;Roh, Myung-Il;Lee, Kyu-Yeul
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.4
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    • pp.279-288
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    • 2010
  • In this paper, a DEVS(Discrete EVent Systems Specification)-HLA(High Level Architecture) interface was developed in order to perform the simulation using the combined discrete event and discrete time simulation model architecture in a distributed environment. The developed interface connects the combined simulation model with the HLA/RTI(Run-Time Infrastructure) which is an international standard middleware for distributed simulation. The interface consists of an interface model, a model interpreter, and a distributed environment interpreter. The interface model was defined by using the combined simulation architecture in order to easily connect the existing combined simulation model without modification with the HLA/RTI. The model interpreter takes charge of data transmission between the interface model and the combined simulation model. The distributed environment interpreter takes charge of data transmission between the interface model and the HLA/RTI. To evaluate the applicability of the developed interface, it was applied to the diving simulation of a submarine in a distributed environment. The result shows that a simulation result in a distributed environment using the interface is the same to the result in a single computing environment.

유선 시뮬레이션 기법과 준해석해를 이용한 용질 거동 분석

  • 정대인;최종근;박광원
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • pp.57-62
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    • 2004
  • Streamline simulation researches have been extensively accomplished due to the swiftness of computation and the reduction of numerical dispersion. In this study, we developed a streamline simulation model using a semianalytical solution of ID transport equation. To validate accuracy of the developed model, we compared simulation results of contaminant transport, which were acquired by streamline simulation models using an analytical solution, a numerical solution, and a semianalytical solution. The developed model using the semianalytical solution matched well with the model using an analytical solution. However, streamline simulation model using a numerical solution showed numerical dispersion. For an advection-dominant flow, there was little difference in the simulation results between the developed model and tile analytical model, but the differences between the analytical model and the numerical model were cleary shown. From the comparison of computing time we know that the streamline simulation using the semianalytical solution is 2-60 times as fast as the streamline simulation using the numerical solution.

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SIMULATION EFFICIENCY FOR MULTI-PRODUCTION MODEL

  • Kwon, Chi-Myung
    • Proceedings of the Korea Society for Simulation Conference
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    • pp.8-8
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    • 1992
  • Through a simulation experiment, often an experimenter is concerned with estimating the system parameters of the linear model consisting of m design points from the outputs oft the simulation model. To improve the estimation of the system parameters and reliability of these estimators, appropriate simulation techniques have been developed. For the first order linear model, Schruben and Margolin (1978) exploited the random number assignment rules which uses a combination of common random numbers and antithetic streams in a simulation experiment designed to estimate the system parameters when the design matrix of simulation model admits orthogonal blocking into two blocks. Nozari, Arnold and Pegden (1984) developed a method for appliying the method of control variates to the situation of the linear model having multiple design points. This talk deals with a different way of utilizing controls under the correlation induction strategy of Schruben and Margolin's to improve the simulation efficiency, and presents a procedure for obtaining the estimators of the system parameters analytically. Simulation results on a selected simulation model indicate a promising evidence that a proposed method may yield better results than Schruben and Margolin's method.

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PORT EXPANSION SIMULATION MODEL

  • 노용덕
    • Proceedings of the Korea Society for Simulation Conference
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    • pp.1-1
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    • 1992
  • This paper presents a user-oriented port expansion simulation model that determines the future economic port capacity to meet the projected demand. The model consists of two parts; a physical impact simulation, and an economic impact simulation. The first part of the model simulates the effects caused by the port capacity expansion. The second part evaluates the port economics due to changes in the port capacity. The model was validated by applying it to the actual port expansion followed at the Port of Mobile, Alabama. A case study is then presented to demonstrate the capacity of the model with a coal handling port, the McDuffie Terminals at the Port of Mobile.

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Simulator Output Knowledge Analysis Using Neural network Approach : A Broadand Network Desing Example

  • Kim, Gil-Jo;Park, Sung-Joo
    • Proceedings of the Korea Society for Simulation Conference
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    • pp.12-12
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    • 1994
  • Simulation output knowledge analysis is one of problem-solving and/or knowledge adquistion process by investgating the system behavior under study through simulation . This paper describes an approach to simulation outputknowldege analysis using fuzzy neural network model. A fuzzy neral network model is designed with fuzzy setsand membership functions for variables of simulation model. The relationship between input parameters and output performances of simulation model is captured as system behavior knowlege in a fuzzy neural networkmodel by training examples form simulation exepreiments. Backpropagation learning algorithms is used to encode the knowledge. The knowledge is utilized to solve problem through simulation such as system performance prodiction and goal-directed analysis. For explicit knowledge acquisition, production rules are extracted from the implicit neural network knowledge. These rules may assit in explaining the simulation results and providing knowledge base for an expert system. This approach thus enablesboth symbolic and numeric reasoning to solve problem througth simulation . We applied this approach to the design problem of broadband communication network.

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System Level Network Simulation of Adaptive Array with Dynamic Handoff and Power Control (동적 핸드오프와 전력제어를 고려한 적응배열 시스템의 네트워크 시뮬레이션)

  • Yeong-Jee Chung;Jeffrey H. Reed
    • Journal of the Korea Society for Simulation
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    • v.8 no.4
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    • pp.33-51
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    • 1999
  • In this study, the system level network simulation is considered with adaptive array antenna in CDMA mobile communication system. A network simulation framework is implemented based on IS-95A/B system to consider dynamic handoff, system level network behavior, and deploying strategy into the overall CDMA mobile communication network under adaptive array algorithm. Its simulation model, such as vector channel model, adaptive beam forming antenna model, handoff model, and power control model, are described in detail with simulation block. In order to maximize SINR of received signal at antenna, Maximin algorithm is particularly considered, and it is computed at each simulation snap shot with SINR based power control and handoff algorithm. Graphic user interface in this system level network simulator is also implemented to define the simulation environments and to represent simulation results on real mapping system. This paper also shows some features of simulation framework and simulation results.

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A Simulation Model for Master Production Schedule (MPS) Evaluation System (기준생산계획 평가 시스템을 위한 시뮬레이션 모델)

  • 최성훈
    • Proceedings of the Korea Society for Simulation Conference
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    • pp.106-110
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    • 1998
  • Some successful scheduling systems are based on simulation technique. However, they are relatively expensive. A cost-effective solution is to apply general-purpose simulation software to the scheduling system. This paper is concerned with developing a simulation model for MPS(Master Production Schedule) evaluation system. The target system of the model is PC production system. AIM (Analyzer for Improving Manufacturing system), a well-known manufacturing oriented simulation software, is used for modeling tool. Eventually, the model can be included into an MPS evaluation system as simulation module and a scheduler can use the system to verify the MPS in advance.

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A Simulation Modeling Methodology by Integrating Distributed Simulation Objects on the Web (웹상에 분산되어 있는 시뮬레이션 객체들의 통합에 의한 시뮬레이션 모델링 방법론)

  • 심원보;이영해
    • Proceedings of the Korea Society for Simulation Conference
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    • pp.325-330
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    • 1999
  • Web-based simulation is one of the most interesting field of simulation research today. Among many research area of web-based simulation, we concern about what a effective way of building simulation model is since creating comprehensive simulation models can be expensive and time consuming. So this paper discusses how to integrate distributed simulation sub-models as objects for constructing the required simulation model which is more large and complex. We introduce two web-oriented methodologies (such as JIDL, CORBA) and the concepts of agent for assisting modelers to integrate simulation models scattered over the web. SINDBAD, which we designed, is a simulation environment which makes it possible constructing a simulation model with distributed model objects on the web and performing the parallel simulation in a distributed way. It is organized according to design patterns in the object oriented concept. Actually we are on the premise that all the distributed objects are originally composed in a CORBA-compatible way to start with our prototype of SINDBAD.

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System Level Simulation of CDMA Network with Adaptive Array

  • Chung, Yeong-Jee;Lee, Jae-Woo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.4
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    • pp.755-764
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    • 1999
  • In this study, the system level network simulation is considered with adaptive array antenna in CDMA mobile communication system. A network simulation framework is implemented based on IS-95A/B system to consider dynamic handoff, system level network behavior, and deploying strategy into the overall CDMA mobile communication network under adaptive array algorithm. Its simulation model, such as vector channel model, adaptive beam forming antenna model, handoff model, and power control model, are described in detail with simulation block. In order to maximize SINR of received signal at antenna, maximin algorithm is particularly considered, and it is computed at each simulation snap shot with SINR based power control and handoff algorithm. Graphic user interface in this system level network simulator is also implemented to define the simulation environments and to represent simulation results on real mapping system. This paper also shows some features of simulation framework and simulation results.

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