• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.689-696
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• 2001

Large-scale Multi-disciplinary Systems(LMS) such as transportation, aerospace, defense etc. are complex systems in which there are many subsystems, interfaces, functions and demanding performance requirements. Because many contractors participate in the development, it is necessary to apply methods of sharing common objectives and communicating design status effectively among all of the stakeholders. The processes and methods of systems engineering which includes system requirement analysis; functional analysis; architecting; system analysis; interface control; and system specification development provide a success-oriented disciplined approach to the project. This paper shows not only the methodology and the results of model-based systems engineering to Automated Guided Transit(AGT) system as one of LMS systems, but also propose the extension of the model-based tool to help manage a project by linking WBS (Work Breakdown Structure), work organization, and PBS (Product Breakdown Structure). In performing the model-based functional analysis, the focus was on the operation concept of an example rail system at the top-level and the propulsion/braking function, a key function of the modern automated rail system. The model-based behavior analysis approach that applies a discrete-event simulation method facilitates the system functional definition and the test and verification activities. The first application of computer-aided tool, RDD-100, in the railway industry demonstrates the capability to model product design knowledge and decisions concerning key issues such as the rationale for architecting the top-level system. The model-based product design knowledge will be essential in integrating the follow-on life-cycle phase activities. production through operation and support, over the life of the AGT system. Additionally, when a new generation train system is required, the reuse of the model-based database can increase the system design productivity and effectiveness significantly.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.211-220
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• 2017

The application of the theoretical model to real assembly lines has been one of the biggest challenges for researchers and industrial engineers. There should be some realistic approach to achieve the conflicting objectives on real systems. Therefore, in this paper, a model is developed to synchronize a real system (A discrete event simulation model) with a theoretical model (An optimization model). This synchronization will enable the realistic optimization of systems. A job assignment model of the assembly line is formulated for the evaluation of proposed realistic optimization to achieve multiple conflicting objectives. The objectives, fluctuation in cycle time, throughput, labor cost, energy cost, teamwork and deviation in the skill level of operators have been modeled mathematically. To solve the formulated mathematical model, a multi-objective simulation integrated hybrid genetic algorithm (MO-SHGA) is proposed. In MO-SHGA each individual in each population acts as an input scenario of simulation. Also, it is very difficult to assign weights to the objective function in the traditional multi-objective GA because of pareto fronts. Therefore, we have proposed a probabilistic based linearization and multi-objective to single objective conversion method at population evolution phase. The performance of MO-SHGA is evaluated with the standard multi-objective genetic algorithm (MO-GA) with both deterministic and stochastic data settings. A case study of the goalkeeping gloves assembly line is also presented as a numerical example which is solved using MO-SHGA and MO-GA. The proposed research is useful for the development of synchronized human based assembly lines for real time monitoring, optimization, and control.

• Journal of the Korea Society of Computer and Information
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• v.25 no.4
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• pp.97-103
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• 2020

Wireless sensor networks collect and analyze sensing data in a variety of environments without human intervention. The sensor network changes its lifetime depending on routing protocols initially installed. In addition, it is difficult to modify the routing path during operating the network because sensors must consume a lot of energy resource. It is important to measure the network performance through simulation before building the sensor network into the real field. This paper proposes a WSN model for a low-energy adaptive clustering hierarchy protocol using DEVS kernel models. The proposed model is implemented with the sub models (i.e. broadcast model and controlled model) of the kernel model. Experimental results indicate that the broadcast model based WSN model showed lower CPU resource usage and higher message delivery than the broadcast model.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.63-72
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• 2020

Tank, which is a representative ground weapon system, is one of the most important weapon systems in each country. For the cost-effective acquisition of a tank based on scientific analysis, the operational concept and effectiveness should be studied based on engagement simulation technology. Besides physical capabilities including maneuver and communication, logical models including decision-making of a tank commander should be developed systematically. This paper describes a method to model a tank for engagement simulation based on Base System Model(BSM), which is the standard architecture of the weapon system model in AddSIM, an integrated engagement simulation software. In particular, a method is proposed to develop logical models by hierarchical and modular approach based on human decision-making model. The proposed method applies a mathematical formalism called DEVS(Discrete EVent system Specification) formalism. It is expected that the proposed method is widely used to study the operational concept and analyze the effectiveness of tanks in the Korean military in the future.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.617-627
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• 2022

Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.94-117
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• 1998

This paper investigates the performance characteristics of the data link layer of the 1996 version of IEC/ISA fieldbus which is developed as internatioal standard of fieldbus. A discrete-event simulation model of the data link layer of IEC/ISA fieldbus is developed. Using the simulation model, this paper identifies the network parameters that influence the performance of prioritys scheme and real-time data transmission, and analyzes the delay performance of IEC/ISA fieldbus with respect to the change of network parameters. The simulation model also integrates continuous-time simulation model of a control system as application process. Using the integrated simulation model, this study investigates the effect of network-induced delay on the performance of control system. Since the simulation model developed in this study can predict the network performance, it will be effectively utilized in the design phase of control and automation systems that adopt the IEC/ISA fieldbus.

• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.1-9
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• 2013

Algal blooms in potable water supplies are becoming an increasingly prevalent and serious water quality problem around the world. In addition to precipitating taste and odor problems, blooms damage the environment, and some classes like cyanobacteria (blue-green algae) release toxins that can threaten human health, even causing death. There is a recognized need in the water industry for models that can accurately forecast in real-time algal bloom events for planning and mitigation purposes. In this study, using data for an interconnected system of rivers and reservoirs operated by a New Jersey water utility, various ANN models, including both discrete prediction and classification models, were developed and tested for forecasting counts of three different algal classes for one-week and two-weeks ahead periods. Predictor model inputs included physical, meteorological, chemical, and biological variables, and two different temporal schemes for processing inputs relative to the prediction event were used. Despite relatively limited historical data, the discrete prediction ANN models generally performed well during validation, achieving relatively high correlation coefficients, and often predicting the formation and dissipation of high algae count periods. The ANN classification models also performed well, with average classification percentages averaging 94 percent accuracy. Despite relatively limited data events, this study demonstrates that with adequate data collection, both in terms of the number of historical events and availability of important predictor variables, ANNs can provide accurate real-time forecasts of algal population counts, as well as foster increased understanding of important cause and effect relationships, which can be used to both improve monitoring programs and forecasting efforts.

• Journal of the Korea Society for Simulation
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• v.27 no.3
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• pp.13-21
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• 2018

The system of systems (SoS) based analysis method for the C3 system consisting of the communication system and the command and control (C2) system has the advantage that detailed analysis is possible, but it requires long execution time per one trial, which makes the analysis of various scenarios difficult. To solve this problem, this paper proposes a method for analysis of C3 SoS using a transformation of a federation into an integrated simulation. This transformation technique reduces the execution time while maintaining accuracy by abstracting the system other than the one to be analyzed, consisting of model hypothesis and function identification. The former can construct an abstracted model for the simulation through the proposed extended Discrete Event Systems Specification (DEVS) formalism and the latter can express the characteristics of the model influenced by other systems. From the case study on C and C2 analysis, the experimental results show that this method shortened the time considerably while maintaining the accuracy within an acceptable error range and we expect that this method will enable the exploratory analysis of the complex systems other than C3.

• Journal of the Korea Society for Simulation
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• v.18 no.1
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• pp.41-51
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• 2009

A discrete event simulation model is developed to evaluate the performances of three different revenue management methods for an air cargo network from Northeast China to North America and Europe. In the first method, a bid price model is applied only to the routes that pass through Incheon. In the second method, the bid price model is applied to all the routes. In third method, bid price and virtual nesting models are applied to the routes that pass through Incheon. The results show that the total revenue significantly increases with the employment of pricing and capacity control. The developed simulation model is a useful research tool to study marketing strategies for air cargo operations.

• Journal of the Korea Society for Simulation
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• v.29 no.4
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• pp.33-46
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• 2020

The purpose of Electronic warfare is to disturbe, neutralize, attack, and destroy the opponent's electronic warfare weapon system or equipment. Suppression of Enemy Air Defense (SEAD) mission is aimed at incapacitating, destroying, or temporarily deteriorating air defense networks such as enemy surface-to-air missiles (SAMs), which is a representative mission supported by electronic warfare. This paper develops a simulator for analyzing the effectiveness of SEAD missions under electronic warfare support using C++ language based on the DEVS (Discrete Event Systems Specification) model, the usefulness of which has been proved through case analysis with examples. The SEAD mission of the friendly forces is carried out in parallel with SSJ (Self Screening Jamming) electronic warfare under the support of SOJ (Stand Off Jamming) electronic warfare. The mission is assumed to be done after penetrating into the enemy area and firing HARM (High Speed Anti Radiation Missile). SAM response is assumed to comply mission under the degraded performance due to the electronic interference of the friendly SSJ and SOJ. The developed simulator allows various combinations of electronic warfare equipment specifications (parameters) and operational tactics (parameters or algorithms) to be input for the purpose of analysis of the effect of these combinations on the mission effectiveness.