• Proceedings of the KSR Conference
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• 2003.10a
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• pp.210-215
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• 2003

Korean High Speed Train (KHST) has been tested on high speed line in JungBu site since it was developed in 2002. The KHST figured 7 cars was modeled for dynamic simulation with Vampire program. and the data acquisition system was used to test successfully the on-line test for proving the dynamic performance of KHST. The comparison between test and simulation results for dynamic behavior of KHST was tried in this paper and it was very difficult because the environmental conditions and running conditions have an effect on the test results and these conditions are unable to be modeled for dynamic analysis. Also the parameters for data acquisition system for test are usually not same to simulation conditions. Therefor, in this paper the acceleration data after filtering with low pass filter below 1Hz were used to compare between test and simulation results because the low frequency range is useful to evaluate the dynamic performance for railway vehicle system, so as steady state curving acceleration. The results show that both are similar in low frequency range.

• Journal of the Korea Society for Simulation
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• v.12 no.4
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• pp.95-102
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• 2003

Stream servers are for supplying multimedia stream data to users through the internet such as movies and music without discontinuation. A typical stream server is designed roughly by considering the characteristics of stream services and by employing processors, memory, PCI bus, Ethernet, TOE and disks. This study focuses on deciding the priority for using resources such as PCI bus, buffer memory and TOE buffer, which have limited capacities in a typical stream server. When the priorities for using limited resources are not given properly, the stream servers may not even function as originally designed. The simulation study shows that the top priority for using PCI bus for normal streaming services should be given to the operation that sends data from buffer memory to TOE buffer. Giving priority for using PCI bus to other operation such as sending data from disks to memory results in a deadlock phenomenon.

• Journal of the Korea Society for Simulation
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• v.1 no.1
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• pp.87-102
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• 1992

This paper presents the development of event-driven system level simulation tool SMPLE(Smpl Extende, an extention fo smpl) and its application to the performance analysis of multiprocessor computer systems. Because of its data structure, it is very difficult to change, expand or add new functions to simulation language smpl implemented by MacDougall. In SMPLE, we change data structure with structure and pointer, add new functions, and enable dynamic memory management. Using new data structure, facilities, and functions added in SMPLE, we simulate job processing of a shared bus multiprocessor system with autonomous hierarchical I/O subsystem. We set system performance contribution of subsystems and units. The impact of disk I/O on system performance is evaluated under vairous conditions of number of processors, processing power, memory access time and disk seek time.

• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.67-74
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• 2003

Stream servers are for supplying multimedia stream data to users through the internet such as movies and musics without discontinuation. A typical stream server is designed roughly by considering the characteristics of stream services and by employing processors, memory, PCI bus, Ethernet, TOE and disks. This study focuses on deciding the priority for using resources such as PCI bus, buffer memory and TOE buffer, which have limited capacities in a typical stream server. The simulation study shows that the top priority for using PCI bus for normal streaming services should be given to the operation that sends data from buffer memory to TOE buffer Giving priority for using PCI bus to other operation such as sending data from disks to memory results in deadlock Phenomenon.

• Journal of ILASS-Korea
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• v.29 no.1
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• pp.1-6
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• 2024

This paper is a numerical analysis study for evaluating the energy efficiency of electric vehicles. Currently, the methods for testing and evaluating the energy consumption efficiency of electric vehicles have limitations such as resources and time. Therefore, there is a need for research on developing models to predict the energy consumption efficiency of electric vehicles. In this study, a numerical analysis research is conducted to predict the energy efficiency of electric vehicles using a vehicle dynamics numerical analysis model. To validate the accuracy of the simulation model, it is compared the results of dynamometer tests with the simulation results and used the Unified Diagnostic Services (UDS) protocol to acquire internal data from the electric vehicle. It is ensured the reliability of the simulation model by comparing data such as motor speed, battery voltage, current, state of charge (SOC), regenerative braking power generation, and total driving distance of the test vehicle with dynamometer test data and simulation model results.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1825-1834
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• 2022

Performing high-fidelity computational fluid dynamics (HF-CFD) to predict the flow and heat transfer state of the coolant in the reactor core is expensive, especially in scenarios that require extensive parameter search, such as uncertainty analysis and design optimization. This work investigated the performance of utilizing a multi-fidelity reduced-order model (MF-ROM) in PWR rod bundles simulation. Firstly, basis vectors and basis vector coefficients of high-fidelity and low-fidelity CFD results are extracted separately by the proper orthogonal decomposition (POD) approach. Secondly, a surrogate model is trained to map the relationship between the extracted coefficients from different fidelity results. In the prediction stage, the coefficients of the low-fidelity data under the new operating conditions are extracted by using the obtained POD basis vectors. Then, the trained surrogate model uses the low-fidelity coefficients to regress the high-fidelity coefficients. The predicted high-fidelity data is reconstructed from the product of extracted basis vectors and the regression coefficients. The effectiveness of the MF-ROM is evaluated on a flow and heat transfer problem in PWR fuel rod bundles. Two data-driven algorithms, the Kriging and artificial neural network (ANN), are trained as surrogate models for the MF-ROM to reconstruct the complex flow and heat transfer field downstream of the mixing vanes. The results show good agreements between the data reconstructed with the trained MF-ROM and the high-fidelity CFD simulation result, while the former only requires to taken the computational burden of low-fidelity simulation. The results also show that the performance of the ANN model is slightly better than the Kriging model when using a high number of POD basis vectors for regression. Moreover, the result presented in this paper demonstrates the suitability of the proposed MF-ROM for high-fidelity fixed value initialization to accelerate complex simulation.

• Journal of information and communication convergence engineering
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• v.1 no.4
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• pp.169-173
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• 2003

The performance of modern mainframe computers keeps increasing due to the advances in the semiconductor technology. However, the quest for the faster computer has never been satisfied. To overcome the discrepancy in the supply and demand, we studied a high performance computer architecture utilizing a three-dimensional Holographic Data Storage Systems (HDSS) as a secondary storage system. The HDSS can achieve a high storage density by utilizing the third dimension. Furthermore, the HDSS can exploit the parallelism by processing the two-dimensional data in a single step. To compare the performance of the HDSS with the conventional hard disk based storage system, we modeled the HDSS using the DiskSim simulation engine and performed the simulation study. Results showed that the HDSS can improve the access time by 1.7 times.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.231-233
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• 2010

Many algorithms for processing LIDAR data are being developed for diverse applications not limited to patch segmentation, bare-earth filtering and building extraction. However, since we cannot exactly know the true locations of LIDAR points, it is difficult to assess the performance of a LIDAR data processing algorithm. In this paper, we thus attempted the performance assessment of the segmentation algorithm developed by Lee (2006) using the LIDAR data generated through simulation based on sensor modelling. Consequently, based on simulation, we can perform the performance assessment of a LIDAR processing algorithm more objectively and quantitatively with an automatic procedure.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.107-114
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• 2016

Web system helps high-performance processing for big-data analysis and practical use to make various information using IT resources. The government have started the RPS system in 2012. The system invigorates the electricity production as using renewable energy equipment. The government operates system gathered big-data with various related information system data and the system users are distributed geographically. The companies have to fulfill the system, are available to purchase the REC to other electricity generation company sellers to procure REC for their duty volumes. The REC market operates single auction methods with users a competitive price. But the price have the large variation with various user trading strategy and sellers situations. This papler proposed RPS system modeling and simulation in web environment that is modeled in geographically distributed computing environment for web user with DEVS W/S. Web simulation system base on web service helps to analysis correlation and variables that act on trading price and volume within RPS big-data and the analysis can be forecast REC price.

• KIEAE Journal
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• v.17 no.5
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• pp.77-86
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• 2017

Purpose: Because of the growing concern over fossil fuel use and increasing demand for greenhouse gas emission reduction since the 1990s, the building energy analysis field has produced various types of methods, which are being applied more often and broadly than ever. A lot of research products have been actively proposed in the area of the building energy simulation for over 50 years around the world. However, in the last 20 years, there have been only a few research cases where the trend of building energy analysis is examined, estimated or compared. This research aims to investigate a trend of the building energy analysis by focusing on methodology and characteristics of each method. Method: The research papers addressing the building energy analysis are classified into two types of method: engineering analysis and algorithm estimation. Especially, EPG(Energy Performance Gap), which is the limit both for the existing engineering method and the single algorithm-based estimation method, results from comparing data of two different levels- in other words, real time data and simulation data. Result: When one or more ensemble algorithms are used, more accurate estimations of energy consumption and performance are produced, and thereby improving the problem of energy performance gap.