• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.5
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• pp.136-145
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• 2004

In companion paper, the composition and structure of the traffic environment is derived. Rules to regulate agent behaviors and the frameworks to communicate between the agents are proposed. In this paper, the model of a driver agent which controls a vehicle agent is constructed. The driver agent is capable of having different driving styles. That is, each driver agent has individual behavior settings of the yielding index and the passing index. The yielding index can be defined as how often the agent yields in case of lane changes, and the passing index can be defined as how often the agent passes ahead. According to these indices, the agents overtake or make their lanes for other vehicles. Similarly, the vehicle agents can have various vehicle dynamic models. According to their dynamic characteristics, the vehicle agent shows its own behavior. The vehicle model of the vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted flow model. The result has shown that it is possible to express the characteristics of each vehicle and its driver in a traffic flow, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed in this paper shows the effectiveness and the practical usefulness of the traffic simulation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.11
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• pp.1523-1534
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• 2000

The performance of a number of existing dynamic subgrid-scale(SGS) models is evaluated in large-eddy simulations(LES) of two prototype transitional and turbulent shear flows, a planar jet and a channel flow. The dynamic SGS models applied include the dynamic Smagorinsky model(DSM);Germano et al. 1991, Lully 1992), the dynamic tow-component model(DTM; Akhavan et al. 2000), the dynamic mixed model(DMM;Zang et al, 1993). and the dynamic two-parameter model(DTPM; Salvetti & Banerjee 1995). The results are compared with those for DNS for their evaluation. The LES results demonstrate the superior performance of DTM with use of a sharp cutoff filter and DMM with use of a box filter, as compared to their respect counterpart DSM, in predicting the mean statistics, spectra and large-scale structure of the flow, Such features of DTM and DMM derive from the construction of the models in which tow separate terms are included to represent the SGS interactions; a Smagorinsky edd-viscosity term to account for the non-local interactions, and a local-interaction term to account for the nonlinear dynamics between the resolved and subgrid scales in the vicinity of the LES cutoff. As well, overall the SGS models using a sharp cutoff filter are more successful than those using a box filter in capturing the statistics and structure of the flow. Finally, DTPM is found to be compatible or inferior to DMM.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.67-95
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• 1998

This research addresses flow time prediction in the dynamic unbalanced job shop scheduling environment. The specific purpose of the research is to develop the job flow time prediction model in the dynamic unbalance djob shop. Such factors as job characteristics, job shop status, characteristics of the shop workload, shop dispatching rules, shop structure, etc, are considered in the prediction model. The regression prediction approach is analyzed within a dynamic, make-to-order job shop simulation model. Mean Absolute Lateness (MAL) and Mean Relative Error (MRE) are used to compare and evaluate alternative regression models devloped in this research.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.110-118
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• 2004

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of ‘NARMAX’ form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.25-32
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• 2018

This paper presents an efficient software reliability testing method for the model based auto-generated code and reify a dynamic test procedure. The benefits of executing the model-based each static/dynamic reliability test before the code-based static/dynamic reliability test are described. Also, The correlations of code/model based reliability test are demonstrated by using model testing tool, Model Advisor and Verification and Validation, and the code testing tool, PolySpace and LDRA. The result of reliability test is indicated in this paper.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.163-172
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• 2004

Nowadays, to analyze the dynamic characteristics of the automotive driving system, the computer simulation linked up with VR(Virtual Reality) technology is treated as the useful method with the improvement of computing ability. In this paper, the VR simulation system has been developed to investigate the driving characteristics of the ASV(Advanced Safety Vehicle) equipped with an ACC(Adaptive Cruise Control) system. For the purpose, VR environment which generates 3D graphic and sound information of the vehicle, the road, the facilities, and the terrain has been organized for the driving reality. Mathematical models of vehicle dynamic analysis including the ACC model have been constructed for computer simulation. The ACC modulates the throttle and brake functions to regulate the vehicle speed so that vehicles could keep proper spacing. Also, the real-time simulation algorithm synchronizes vehicle dynamic simulation with the graphic rendering. With the developed VR simulation system, simple scenarios are applied to analyze the dynamic characteristics. It is shown that the VR simulation system could be useful to evaluate the adaptive cruise controlled vehicle on various driving conditions.

• International Journal of Aeronautical and Space Sciences
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• v.16 no.3
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• pp.394-406
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• 2015

In this work, an efficient aircraft landing simulation strategy is proposed to develop an efficient and reliable hard-landing monitoring procedure. Landing stage is the most dangerous moment during operation cycle of aircraft and it may cause structural damage when hard-landing occurs. Therefore, the occurrence of hard-landing should be reported accurately to guarantee the structural integrity of aircraft. In order to accurately determine whether hard-landing occurs or not from given landing conditions, full nonlinear structural dynamic simulation can be performed, but this approach is highly time-consuming. Thus, a more efficient approach for aircraft landing simulation which uses a hierarchical aircraft landing model and an extended inertia relief technique is proposed. The proposed aircraft landing model is composed of a multi-body dynamics model equipped with landing gear and tire models to extract the impact force and inertia force at touch-down and a linear dynamic structural model with an extended inertia relief method to analyze the structural response subject to the prescribed rigid body motion and the forces extracted from the multi-body dynamics model. The numerical examples show the efficiency and practical advantages of the proposed landing model as an essential component of aircraft hard-landing monitoring procedure.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.3
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• pp.263-269
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• 2009

This paper describes comparative analysis results about the dynamic interaction of interconnected wind power system using the actual-size hardware simulator and the simulation model with PSCAD/EMTDC. The hardware simulator, which is composed of 2.0MVA induction motor with drive system and 1.5MW doubly-fed induction generator, was built and tested in Go-Chang Test Site of KEPCO for analyzing the dynamic interaction with the interconnected distribution system. The operation of hardware simulator was verified through comparative analysis between experimental results and simulation results obtained by simulation model with PSCAD/EMTDC. The developed hardware simulator and simulation model could be effectively used for analyzing the dynamic interaction, which has various phenomena depending on the wind variation and the network state of interconnected power system.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.43 no.2
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• pp.159-168
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• 2010

This paper presents a mathematical model and simulation method for investigating the performance of set net systems and fish cage systems influenced by currents and waves. Both systems consist of netting, mooring ropes, a floating collar and sinkers. The netting and ropes were considered flexible structures and the floating collar was considered an elastic structure. Both were modeled on a mass-spring model. The structures were divided into finite elements and mass points were placed at the mid-point of each element, and the mass points were connected by mass-less springs. Each mass point was subjected to external and internal forces and the total force was calculated at every integration step. An implicit integration scheme was used to solve the nonlinear dynamic system. The computation method was applied to dynamic simulation of actual systems simultaneously influenced by currents and waves in order to evaluate their practicality. The simulation results improved our understanding of the behavior of the structure and provided valuable information concerning the optimized design of set net and fish cage systems exposed to an open ocean environment.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.115-120
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• 1997

System identification is the task of inferring a mathematical description of a dynamic system from a series of measurements of the system. There are several motives for establishing mathematical descriptions of dynamic systems. Typical applications encompass simulation, prediction, fault diagnostics, and control system design. The paper demonstrates that neural networks can be used effective for the identification of nonlinear dynamical systems. The content of this paper concerns dynamic neural network models, where not all inputs to and outputs from the networks are measurable. Only one model type is treated, the well-known Innovation State Space model(Kalman Predictor). The identification is based only on input/output measurements, so in fact a non-linear Extended Kalman Filter problem is solved. Even for linear models this is a non-linear problem without any assurance of convergence, and in spite of this fact an attempt is made to apply the principles from linear models, an extend them to non-linear models. Computer simulation results reveal that the identification scheme suggested are practically feasible.