• Journal of the Korea Society for Simulation
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• v.8 no.4
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• pp.137-154
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• 1999

In this paper, we propose a software design method that will track the effects of modifications in a component to the rest of the components in the design phase. The prediction of the effects due to the design modifications before coding can be a valuable aid for the complex and large software development. Within the method, the target system is represented by the structured I/O system level specification which is one of the system representation level defined by the system theory. Then it is abstracted to the I/O system level. The DEVS (Discrete Event System Specification) model is constructed based on tile I/O system level specification. Finally, the DEVS model is simulated to generate the behavior of the software by the abstract simulator in DEVS simulation environment. As an application, the graphic user interface system of a metal grating production scheduling system is presented.

• Journal of the Korean housing association
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• v.1 no.1
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• pp.37-48
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• 1990

The objective of this study is to suggest a housing life cycle of Korean families which adds to the establishment of reasonable housing standards and to the prediction of fufure-oriented family housing behavior by reviewing published papers. Following model is suggested as a housing life cycle suitable to assess the family housing behavior in Korea. 1st stage : period of house searching 2nd stage : period of house changing 3rd stage : period of house stabilizing \circled1 size enlargement phase \circled2 quality improvement phase \circled3 stable settlement phase 4th siage : period of house contracting 5th stage : period of house depending Since the proposed model is hypothetical, it must be tested and modified by the extensive social survey research on the real housing event history.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.73-79
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• 2005

This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

• Information and Communications Magazine
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• v.31 no.3
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• pp.103-116
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• 2014

This paper proposes the design of Vehicular Cyber-Physical Systems (called VCPS) based on vehicular cloud for smart road networks. Our VCPS realizes mobile cloud computing services where vehicles themselves or mobile devices (e.g., smartphones and tablets of drivers or passengers in vehicles) play a role of both cloud server and cloud client in the vehicular cloud. First, this paper describes the architecture of vehicular networks for VCPS and the delay modeling for the event prediction and data delivery, such as a mobile node's travel delay along its navigation path and the packet delivery delay in vehicular networks. Second, the paper explains two VCPS applications as smart road services for the driving efficiency and safety through the vehicular cloud, such as interactive navigation and pedestrian protection. Last, the paper discusses further research issues for VCPS for smart road networks.

• Corrosion Science and Technology
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• v.15 no.1
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• pp.6-12
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• 2016

Flow-Accelerated Corrosion (FAC) is a well-known degradation mechanism that attacks the secondary piping in nuclear power plants. Since the Surry Unit 2 event in 1986, most nuclear power plants have implemented management programs to deal with damages in carbon and low-alloy steel piping. Despite the utmost efforts, damage induced by FAC still occurs in power plants around the world. In order to predict FAC wear, some computer programs were developed such as CHECWORKS, CICERO, and COMSY. Various data need to be input to these programs; the chemical composition of secondary piping, flow operating conditions and piping geometries. CHECWORKS, developed by the Electric Power Research Institute (EPRI), uses a geometry code to calculate geometry effects. Such a relatively simple geometry code is limited in acquiring the accuracy of FAC prediction. Recently, EPRI revisited the geometry code with the intention of updating it. In this study, numerical simulations were performed for two adjacent $90^{\circ}$ elbows and the results were analysed in terms of the proximity effect between the two adjacent elbows.

• The Journal of Bigdata
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• v.3 no.1
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• pp.47-54
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• 2018

Previous studies of business process analysis have analyzed various factors such as task, customer service, operator convenience, and execution time prediction. To accurately analyze these factors, it is effective to utilize actual historical data recorded in information systems. Process mining is a technique for analyzing various elements of a business process from event log data. In this case study, process mining was applied to the transaction data of a purchase agency to analyze the business process of their procurement process, the execution time, and the operators.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.4 no.1
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• pp.7-24
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• 1996

A methodology has been developed for predicting aircraft reliability incorporating both C.C.F.s(Common-Cause Failures), and phased missions. Failure behaviour of an aircraft, or it's systems are predicted. Both independent failures, and C.C.F.s, are modelled by the Markov process, and simulated using Monte Carlo sampling with the robust variance reduction method. Prediction of safety and reliability is made through discrete-event simulation of aircraft operations. A case study is described for investigating the safety and reliability of the propulsion system of two-, three- and four-engined aircraft. This is particularly important for the design of ETOPS(Extended Range of Two-Engined Aircraft Operations) and results are presented for the cases with, and without the effect of C.C.F.s.

• Wind and Structures
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• v.24 no.6
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• pp.529-564
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• 2017

The Santa Ana winds occur in Southern California during the September-May time frame, bringing low humidities across the area and strong winds at favored locations, which include some mountain gaps and on particular slopes. The exceptionally strong event of late October 2007, which sparked and/or spread numerous fires across the region, is compared to more recent events using a numerical model verified against a very dense, limited-area network (mesonet) that has been recently deployed in San Diego County. The focus is placed on the spatial and temporal structure of the winds within the lowest two kilometers above the ground within the mesonet, along with an attempt to gauge winds and gusts occurring during and after the onset of October 2007's Witch fire, which became one of the largest wildfires in California history.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.296-302
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• 1996

The Loss of a Main Feedwater Pump test at 100% Power for YGN 4 was simulated in order to verify and validate the KSNPA. The comparison of the test data with the KSNPA prediction results showed reasonable agreement in the trends of the major plant parameters. All plant control systems including NSSS and T/G control systems are properly actuated and stabilized the plant conditions to a new steady state conditions in the KSNPA. From the comparison results, the KSNPA showed its capability to simulate the LOMFP event for the Korean Standard Nuclear Power Plant.

• Earthquakes and Structures
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• v.22 no.4
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• pp.401-419
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• 2022

A novel hybrid extreme machine learning-multiverse optimizer (ELM-MVO) framework is proposed to predict the liquefaction phenomenon in seismically excited tunnel lining inside the sand lens. The MVO is applied to optimize the input weights and biases of the ELM algorithm to improve its efficiency. The tunnel located inside the liquefied sand lens is also evaluated under various near- and far-field earthquakes. The results demonstrate the superiority of the proposed method to predict the liquefaction event against the conventional extreme machine learning (ELM) and artificial neural network (ANN) algorithms. The outcomes also indicate that the possibility of liquefaction in sand lenses under far-field seismic excitations is much less than the near-field excitations, even with a small magnitude. Hence, tunnels designed in geographical areas where seismic excitations are more likely to be generated in the near area should be specially prepared. The sand lens around the tunnel also has larger settlements due to liquefaction.