• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.82-92
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• 2024

Purpose: The purpose of this study is to find a solution to the massive data construction that occurs when fire simulation data is linked to augmented reality and the resulting data overload problem. Method: An experiment was conducted to set the interval between appropriate input data to improve the reliability and computational complexity of Linear Interpolation, a data estimation technology. In addition, a validity verification was conducted to confirm whether Linear Interpolation well reflected the dynamic changes of fire. Result: As a result of application to the underground common area, which is the study target building, it showed high satisfaction in improving the reliability of Interpolation and the operation processing speed of simulation when data was input at intervals of 10 m. In addition, it was verified through evaluation using MAE and R-Squared that the estimation method of fire simulation data using the Interpolation technique had high explanatory power and reliability. Conclusion: This study solved the data overload problem caused by applying digital twin technology to fire simulation through Interpolation techniques, and confirmed that fire information prediction and visualization were of great help in real-time fire prevention.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.23-34
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• 2004

Regenerative simulation (RS) is a method of stochastic steady-state simulation in which output data are collected and analysed within regenerative cycles (RCs). Since data collected during consecutive RCs are independent and identically distributed, there is no problem with the initial transient period in simulated processes, which is a perennial issue of concern in all other types of steady-state simulation. In this paper, we address the issue of experimental analysis of the quality of sequential regenerative simulation in the sense of the coverage of the final confidence intervals of mean values. The ultimate purpose of this study is to determine the best version of RS to be implemented in Akaroa2 [1], a fully automated controller of distributed stochastic simulation in LAN environments.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.2
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• pp.85-89
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• 1997

The development of the algorithm and the computer aided marking data generation system based on it should precede the automation system for plate forming by line heating method. This paper places emphasis on the yard simulation for a real surface model to justify the algorithm and the computer aided marking data generation system which have been already developed. The yard simulation has been carried out according to the generated marking data and the heating condition produced by the developed computer aided system. The practical applicability of the developed computer aided system has been conformed by comparing the results of the computer simulation to the results of the yard simulation. This paper ends with the extension of the developed marking data generation system.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.6
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• pp.510-520
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• 2014

Unlike other mass production in small variety, shipbuilding process is a project-based method in single variety, which causes unpredictable volatility in the planning system. In shipyards, series of manufacturing processes from fabrication to erection is sequentially carried out. In order to predict unfavorable changes such as overload or low load of working volume, computerized simulation has been being gradually adopted. The data used in the simulation are processed from the database of the main scheduling and planning system. Thus the quality of those data is very crucial for the meaningful results. Unfortunately, research on the verification of data quality is very rare and hardly known to the authors. In this work, using the database of scheduling and product information system of a large domestic shipyard, the data required for the simulation are qualitatively analyzed and verified.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.274-277
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• 2008

To evaluate high-resolution wind resources for local and coastal area with complex terrain was attemped to combine the prognostic MM5 mesoscale model with CALMET diagnostic modeling this study. Firstly, MM5 was simulated for 1km resolution, nested fine domain, with FDDA using QuikSCAT seawinds data was employed to improve initial meteorological fields. Wind field and other meteorological variables from MM5 with all vertical levels used as initial guess field for CALMET. And 5 surface and 1 radio sonde observation data is performed objective analysis whole domain cells. Initial and boundary condition are given by 3 hourly RDAPS data of KMA in prognostic MM5 simulation. Geophysical data was used high-resolution terrain elevation and land cover(30 seconds) data from USGS with MM5 simulation. On the other hand SRTM 90m resolution and EGIS 30m landuse was adopted for CALMET diagnostic simulation. The simulation was performed on whole year for 2007. Vertical wind field a hour from CALMET and latest results of MM5 simulation was comparison with wind profiler(KEOP-2007 campaign) data at HAENAM site.

• Korean System Dynamics Review
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• v.13 no.2
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• pp.47-71
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• 2012

The purpose of this research is the examination of validity of data as well as simulation model, i.e. to simulate the real data in the SD model with the least error using the adjustments for the faithful reflection of real data to the simulation. In general, SD programs (e.g. VENSIM) utilize the Euler or Runge-Kutta method as an algorithm. It is possible to reflect the trend of real data via these two estimation methods however can cause the validity problem in case of the simulation requiring the accuracy as they have endogenous errors. In this article, the future population estimated by the Korea National Statistical Office (KNSO) to 2050 is simulated by the aging chain model, dividing the population into three cohorts, 0-14, 15-64, 65 and over cohorts by age and offering the adjustments to them. Adjustments are calculated by optimization with three different methods, optimization in EXCEL, manual optimization with iterative calculation, and optimization in VENSIM DSS, the results are compared, and at last the optimal adjustment set with the least error are found among them. The simulation results with the pre-determined optimal adjustment set are validated by methods proposed by Barlas (1996) and other alternative methods. It is concluded that the result of simulation model in this research has no significant difference from the real data and reflects the real trend faithfully.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.173-178
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• 2014

Smart devices linked to high speed networks enable us to obtain location dependent data at anywhere and anytime. In this environment, a wireless data broadcast system can deal with enormous data request from a great number of clients effectively. In order to set up an efficient wireless data broadcast system, various data scheduling and indexing schemes have been proposed. However, a simulation framework to evaluate the schemes is not reported yet. In this paper, we design and develop a simulation framework for a wireless data broadcast system. The developed simulation framework can evaluate quickly a wireless data broadcast system and has scalability to adopt various data scheduling and indexing schemes for wireless data broadcasting.

• Journal of Digital Contents Society
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• v.10 no.4
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• pp.649-657
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• 2009

Usually, The data transmission processing efficiency of the distributed system running on high speed networks depends on the system architecture and the data transmission processing system. In order to secure the real-time rate and the system reliability, the real-time distributed simulation system on the distributed environment has tried to satisfy the performance required by the data transmission processing system. However, the client/server-based data transmission processing system in the real-time simulation system has been difficult to satisfy the system stability, extensibility and maintenability, especially when system changes. So, it is natural to study another improved data transmission processing system to solve the problems at the existing real-time simulation system. After analyzing the existing real-time simulation system, this paper will propose the improved real-time data transmission system by using Software Design Pattern, which enhances extensibility, interoperability, reusability and maintenability of the system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.708-710
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• 2013

Web based simulation service is utilized to computationally analyze various phenomena in real world according to the progress of network and computing technology. To provide suitable simulation service, web based simulation service will be improved by analyzing execution data. Especially, an API for data retrieval is designed, because every analyst needs different data. In this paper, we design the retrieval API for a user to analyze the web based simulation execution data, which is used on CFD (Cumputational Fluid Dynamics) and Chemistry. The designed retrieval API provides an simulation execution data depending on an user requirement such as a user type, an execution period, and an affiliation, which is based on the core information such as an user, a simulation program, and a cyberlab. Besides, a developer can provides a suitable information for a user to execute a simulation well such as a simulation statistics, an execution trend, and a frequent error.