• Nuclear Engineering and Technology
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• v.52 no.8
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• pp.1834-1846
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• 2020

The SMART (System-integrated Modular Advanced ReacTor) is an integral-type small modular reactor developed by KAERI (Korea Atomic Energy Research Institute). This paper discusses the development of a dynamic equivalent model of the SMART control rod drive mechanism that can be efficiently utilized for complicated analysis during the design of the SMART. A semi-empirical approach is used to develop the equivalent model; that is, the equivalent model is defined analytically and verified empirically. Two types of tests, dynamic characteristics tests and seismic loading tests, are conducted for the development and verification of the dynamic equivalent model, respectively. Acceleration response spectra from the seismic analysis based on the developed equivalent model show good agreement with those from the seismic loading tests.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.05a
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• pp.703-707
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• 2000

Machine tool errors have to be characterized and predicted to improve machine tool accuracy. A real-time error compensation system has been developed based on volumetric error synthesis model which is composed of machine tool errors. This paper deals with new algorithm about verification of machine tool errors. This new algorithm uses a simplified volumetric error synthesis model. This simplified model is constructed with only main components among the error components of the machines. This main error components are analyzed by three-dimensional helical ball bar test. By substituting result of helical ball bar test fer simplified model, we could find that obtained error components are closed to real error components.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.1
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• pp.52-59
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• 1991

An effective and accurate delay time model is the key problem in the simulation and timing verification of CMOS logic circuits. We propose a semi-analytic CMOW delay time model taking into account the configuration ratio, the input waveform slope and the load capacitance. This model is based on the Schichman Hodges's DC equations and derived on the optimally weighted switching peak current. The parameters necessary for the model calculation are automatically determined from the program. The proposed model is computationally effective and the error is typically within 10% of the SPICEA results. Compared to the table RC model, the accuracy is inproved over two times in average.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.585-594
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• 2009

In this present study, to performed the model test and estimated the behavior characteristics of twin tunnel in accordance with the variation of the whole failure parameters which is the strength of the ground, distance of tunnel, angle of the joint, installation of tension bolts and the blasting load. To carry out the numerical analysis for verification of model test results and analyze the sensitivity on failure parameters using model test and numerical analysis results. Based on sensitivity analysis results, to propose the most habitually failure parameters in tunnel scale model test.

• KIEAE Journal
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• v.8 no.5
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• pp.11-16
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• 2008

This research has established CFD model on pit's cool-tube system through heat and air movement simulations, of which data was based on experimental and verification. This research work verified the effectiveness of the cool-tube system by analysing temperature, humidity and air current of the actually installed case. Also, we analysed heat transfer through air current simulation and the results are as followings. Firstly, we experiment on temperature, humidity and speed of air currents of the cool tube system with pit space during the month of May (spring). The average exterior temperature was $16.1^{\circ}C$, and $18.2^{\circ}C$ for the pit, $24.7^{\circ}C$ for the compressor room. Secondly, based on measured data of real case, we have analysed heat transfer through air current simulation and verified our proposed model. The actual measurement of average temperature of exhaust air of the pit's area is $19.7^{\circ}C$ with tolerance of $-0.33^{\circ}C{\sim}-0.6^{\circ}C$ compared to above simulations. Thirdly, having verified air current simulation model with formation of 260,000 and 1,000,000 cells, we could get reasonable near values with 260,000 cells. Lastly, the next step of research would be focused on proposing the best possible pit's cool-tube system after analysis of heat transfer of the air current simulation based on verified CFD model.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.8
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• pp.689-696
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• 2001

Large-scale Multi-disciplinary Systems(LMS) such as transportation, aerospace, defense etc. are complex systems in which there are many subsystems, interfaces, functions and demanding performance requirements. Because many contractors participate in the development, it is necessary to apply methods of sharing common objectives and communicating design status effectively among all of the stakeholders. The processes and methods of systems engineering which includes system requirement analysis; functional analysis; architecting; system analysis; interface control; and system specification development provide a success-oriented disciplined approach to the project. This paper shows not only the methodology and the results of model-based systems engineering to Automated Guided Transit(AGT) system as one of LMS systems, but also propose the extension of the model-based tool to help manage a project by linking WBS (Work Breakdown Structure), work organization, and PBS (Product Breakdown Structure). In performing the model-based functional analysis, the focus was on the operation concept of an example rail system at the top-level and the propulsion/braking function, a key function of the modern automated rail system. The model-based behavior analysis approach that applies a discrete-event simulation method facilitates the system functional definition and the test and verification activities. The first application of computer-aided tool, RDD-100, in the railway industry demonstrates the capability to model product design knowledge and decisions concerning key issues such as the rationale for architecting the top-level system. The model-based product design knowledge will be essential in integrating the follow-on life-cycle phase activities. production through operation and support, over the life of the AGT system. Additionally, when a new generation train system is required, the reuse of the model-based database can increase the system design productivity and effectiveness significantly.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.721-738
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• 2018

The purpose of this study is to create landslide vulnerability using frequency ratio (FR) and evidential belief functions (EBF) model which are two methods of probability model and to select appropriate model for each region through comparison of results in Sacheon-myeon and Jumunjin-eup of Gangneung. 762 locations in Sacheon-myeon and 548 landscapes in Jeonju-eup were constructed based on the interpretation of aerial photographs. Half of each landslide point was randomly selected for modeling and remaining landslides were used for verification purposes. Twenty landslide-inducing factors classified into five categories such as topographic elements, hydrological elements, soil maps (1:5,000), forest maps (1:5,000), and geological maps (1:25,000) were considered for the preparation of landslide vulnerability in the study. The relationship between landslide occurrence and landslide inducing factors was analyzed using FR and EBF models. The two models were then verified using the AUC (curve under area) method. According to the results of verification, the FR model (AUC = 81.2%) was more accurate than the EBF model (AUC = 78.9%) at Jeonjun-eup. In the Sacheon-myeon, the EBF model (AUC = 83.6%) was more accurate than the FR model (AUC = 81.6%). Verification results show that FR model and EBF model have high accuracy with accuracy of around 80%.

• Journal of the Korean Society of Systems Engineering
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• v.13 no.1
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• pp.15-23
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• 2017

This paper describes verification of APR1400 reactor vessel by applying the system engineering approach, in which the design re-engineering method is used to check the design parameters of APR1400 RV (reactor vessel). The RV is classified as safety class 1 and therefore must adhere strictly to the rules of ASME BPVC section III, subsection NB and seismic category I. This study explores designing the RV by following the ASME guidelines and making a comparative study with the current design. To meet this objective we apply system engineering methodologies to structure the process and allow for verification and validation of the major RV design parameters such as thickness of RV. The structural thicknesses of various part of RV are determined as well as reinforcements on the RV major nozzles. A 3D virtual reality model was created based on the design parameters using CATIA V5 and animation using Dassault Composer V2016. A comparison of re-engineered ARP1400 RV and standard APR1400 RV was done to show which design parameters were taken more conservative approach.

• Korean Journal of Computational Design and Engineering
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• v.16 no.5
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• pp.351-360
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• 2011

Product systems are quickly and frequently changed because Product Life Cycle is continuously reduced and adopting new product is steadily fast. Thus, various studies are progressed using simulation which is one of digital manufacturing. The research that is concerning simulation of control verification for shorten the commissioning which has a lot of trial and error is in progress. Also, simulation of control verification has strength that it can catch the errors in advance. However, a control program in simulation needs virtual factory for representation of control information. For this reason, excessive time and energy is put into controlling the virtual factory. So, in this paper, we construct library which is using exist data, in order to overcome limitation of these problems. Furthermore, we suggest methodology which can model and verify the process more speedy using library. Especially, we give body to the BB/BR Line process which has many altering equipment and need high technology effectively using physical and logical modeling. We can set up a control simulation environment very rapidly, as well as cut process time down using our suggestion.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.