• Earthquakes and Structures
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• v.19 no.6
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• pp.445-457
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• 2020

An ultra-high voltage (UHV) transmission system has the advantages of low circuitry loss, high bulk capacity and long-distance transmission capabilities over conventional transmission systems, but it is easier for this system to cross fault rupture zones and become damaged during earthquakes. This paper experimentally and numerically investigates the seismic responses and collapse failure of a UHV transmission tower-line system crossing a fault. A 1:25 reduced-scale model is constructed and tested by using shaking tables to evaluate the influence of the forward-directivity and fling-step effects on the responses of suspension-type towers. Furthermore, the collapse failure tests of the system under specific cross-fault scenarios are carried out. The corresponding finite element (FE) model is established in ABAQUS software and verified based on the Tian-Ma-Qu material model. The results reveal that the seismic responses of the transmission system under the cross-fault scenario are larger than those under the near-fault scenario, and the permanent ground displacements in the fling-step ground motions tend to magnify the seismic responses of the fault-crossing transmission system. The critical collapse peak ground acceleration (PGA), failure mode and weak position determined by the model experiment and numerical simulation are in relatively good agreement. The sequential failure of the members in Segments 4 and 5 leads to the collapse of the entire model, whereas other segments basically remain in the intact state.

• Journal of Korean Society of Disaster and Security
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• v.14 no.1
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• pp.9-21
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• 2021

Recently, the importance of eco-friendly power generation facility using renewable energy has newly appeared. Hydropower plant is a very important source of electricity generation and supply which is very important to secure safety because it is commonly connected with multi facility and operated on a large scale. In this study, a scenario-based analysis method was suggested to assess vulnerability of a penstock system caused by water hammer commonly occurred in the operation of hydropower plants. A hypothetical hydropower plant was used to demonstrate the applicability of a transient analysis model. In order to verify reliability of the model, the prediction of pressure behaviors were compared with the results of commercial model (SIMSEN) and measured data, then a real hydroelectric power plant was applied to develop all potential water hammer scenarios during the actual operation. The scenario-based simulation and vulnerability assessment for water hammer in the penstock system were performed with internal and external load conditions. The simulation results indicated that the vulnerability of a penstock system was varied with the operating conditions of hydropower facilities and significantly affected by load combination consisting of different load scenarios. The proposed numerical method could be an useful tool for the vulnerabilityty assessment of the hydropower plants due to water hammer.

• Journal of the Korea Society for Simulation
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• v.22 no.4
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• pp.67-82
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• 2013

This paper presents multi-fidelity modeling and simulation (M&S) methodology to enhance simulation performance of engineering-level defense models. In this approach, a set of models with varying degrees of fidelity is exercised to reduce computational expense maintaining a similar level of system effectiveness. For multi-fidelity M&S principles, this paper defines model fidelity from two perspectives (i.e., model behavior and execution), and suggests the Fidelity Change Point (FCP) to specify the fidelity conversion. With these concepts, this paper centers on three ideas: 1) two models' structure which are the Behavioral-Fidelity Interchangeable Model (B-FIM) and the Executional-Fidelity Interchangeable Model (E-FIM), 2) modeling formalism, and 3) a simulation algorithm to support them. From an abstract case study regarding a target tracking scenario with the utilization of the proposed method, we can gain interesting experimental results regarding the enhancement of simulation performance. Finally, we expect that this work will serve various M&S-based analysis areas for enhancing simulation performance.

• 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 Safety Management & Science
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• v.11 no.2
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• pp.137-144
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• 2009

EPCIS(EPC Information Services) system is a core component of EPCglobal Architecture Framework offering information of the freights, the time of awareness and the location of awareness on the EPCglobal Network. The role of EPCIS is to exchange information based on EPC. There are four kinds of event data which are object event data, aggregation event data, quantity event data, and transaction event data. These EPCIS events data are stored and managed in EPCIS repository. This study suggest the quantitative modeling about total number of EPCIS event data under the assumption to aware the RFID tags of items, cases(boxes), vehicles(carriers, forklifts, auto guided vehicles, rolltainers) at a time on the reading points. We also estimate the number of created EPCIS event data by the suggested quantitative modeling under scenario of process in the integrated logistics center based on RFID system And this study compare the TO-BE model with the AS-IS model about the total sizes of created EPCIS event data using the simulation, in which we suggested the TO-BE model as the development of the repository by skipping the overlapped records.

• Journal of the Korean Society for Railway
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• v.6 no.2
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• pp.100-107
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• 2003

This paper presents development of train performance simulation(TPS) program to analyze traction performance, braking performance and energy consumption for Korea high speed railway system. The conventional TPS program have some inconveniences such as DOS-based platform, user interface and limited function. The simulation technique model using scenario menu, various analysis function and object-oriented design/programming is presented. This simulation result have been compared with Alstom's for the Seoul-Pusan High Speed Rail Project.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.77-86
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• 2012

This study was aim to predict future land-cover changes and to analyze regional land-cover changes in irrigation areas and agricultural reservoir watersheds under climate change scenario. To simulate the future land-cover under climate change scenario - A1B of the SRES (Special Report on Emissions Scenarios), Dyna-CLUE (Conversion of Land Use Change and its Effects) was applied for modeling of competition among land-use types in relation to socioeconomic and biophysical driving factors. For the study areas, 8 agricultural reservoirs were selected from 8 different provinces covering all around nation. The simulation results from 2010 to 2100 suggested future land-cover changes under the scenario conditions. For Madun reservoir in Gyeonggi-do, total decrease amount of paddy area was a similar amount of 'Base demand scenario' of Water Vision 2020 published by MLTMA (Ministry of Land, Transport and Maritime Affairs), while the decrease amounts of paddy areas in other sites were less than the amount of 'High demand scenario' of Water Vision 2020. Under A1B scenario, all the land-cover results showed only slight changes in irrigation areas of agricultural reservoirs and most of agricultural reservoir watersheds will be increased continuously for forest areas. This approach could be useful for evaluating and simulating agricultural water demand in relation to land-use changes.

• IE interfaces
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• v.17 no.1
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• pp.1-12
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• 2004

In a modern semiconductor device manufacturing industry, statistical bin limits on wafer level test bin data are used for minimizing value added to defective product as well as protecting end customers from potential quality and reliability excursion. Most wafer level test bin data show skewed distributions. By Monte Carlo simulation, this paper evaluates methods and sample size effect regarding determination of statistical bin limits. In the simulation, it is assumed that wafer level test bin data follow the Poisson distribution. Hence, typical shapes of the data distribution can be specified in terms of the distribution's parameter. This study examines three different methods; 1) percentile based methodology; 2) data transformation; and 3) Poisson model fitting. The mean square error is adopted as a performance measure for each simulation scenario. Then, a case study is presented. Results show that the percentile and transformation based methods give more stable statistical bin limits associated with the real dataset. However, with highly skewed distributions, the transformation based method should be used with caution in determining statistical bin limits. When the data are well fitted to a certain probability distribution, the model fitting approach can be used in the determination. As for the sample size effect, the mean square error seems to reduce exponentially according to the sample size.

• Journal of The Korean Society of Agricultural Engineers
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• v.50 no.4
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• pp.17-24
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• 2008

Exposure risk assessment of pesticide molinate using the RICEWQ model in a rice paddy plot was performed to observe the effects of various water and pesticide management scenarios. Several scenarios were developed to represent the specific water and pesticide management practices of rice cultivation in Korea. The results of the scenario analysis using the RICEWQ model simulation from the previous studies were analysed. The molinate risk for aquatic organisms is evaluated by the ratio of the predicted environmental concentration(PEC) and the predicted no-effect concentration(PNEC). The results showed that the no-effect periods for aquatic organisms for the deep, shallow and very shallow irrigation conditions were 33.3, 28.9 and 25.6 DATs for the lable rate application and 36.4, 33.7 and 30.8 DATs for the double lable rate application, respectively. The higher application rate showed greater exposure risk to the aquatic organisms. Based on this study, the withholding period of molinate practiced in Korea, that is 3 to 4 DATs, must be much longer. The results of this study can be used for the non-point source pollution control and environmental policy making regarding pesticides.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.93-108
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• 2023

In manufacturing productivity analysis, understanding the intricate interplay among factors like facility performance, layout design, and workforce allocation within the production line is imperative. This paper introduces a simulation-based methodology tailored to food manufacturing, progressively expanding scenarios to analyze production enhancement. The target system is a food processing plant, encompassing production processes, including warehousing, processing, subdivision, packaging, inspection, loading, and storage. First, we analyze the target system and design a simulation model according to the actual layout arrangement of equipment and workers. Then, we validate the developed model reflecting the real data obtained from the target system, such as the workers' working time and the equipment's processing time. The proposed model aims to identify optimal factor values for productivity gains through incremental scenario comparisons. To this end, three stages of simulation experiments were conducted by extending the equipment and worker models of the subdivision and packaging processes. The simulation experiments have shown that productivity depends on the placement of skilled workers and the performance of the packaging machine. The proposed method in this study will offer combinations of factors for the specific production requirements and support optimal decision-making in the real-world field.