• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.224-224
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• 2019

국제기상기구의 Global Framework for Climate Services (GFCS)의 관점에서 살펴보면 국내의 기상 기후 정보는 기상청을 중심으로 관측 자료와 중장기 예측 및 기후변화 시나리오 정보 등의 다양한 시간규모로 생산되고 있다. 하지만 사용자가 직접적으로 다양한 기후정보를 상세화하여 활용하기 위해서는 기후정보의 구축 및 전처리를 수행해야하는 어려움이 있다. 따라서 APEC Climate Center (APCC)에서 다학제 융합 기반 기후정보 서비스를 중심으로 사용자 인터페이스 플랫폼 (User Interface Platform: UIP)의 기술적 플랫폼으로 APCC Integrated Modeling Solution (AIMS)를 개발하였다. AIMS는 사용자의 관점으로 상세화를 수행할 수 있고, 다양한 응용 분야에 적용하기 쉽게 데이터를 생성하여 연구에 도움을 주고 있다. 본 연구는 AIMS에서 제공하고 있는 기존의 국가별로 제공하는 제 5차 결합 기후모델 비교사업 (The $5^{th}$ phase of the coupled model intercomparision project, CMIP5)에서 해석한 전구기후모델 (General Circulation Model, GCM)의 통계적 상세화 방법인 Simple Quantile Mapping (SQM)과 Spatial Disaggregation Quantile Delta Mapping (SDQDM)를 포함하여 AIMS에 새롭게 추가 된 통계적 상세화 방법인 Bias Correction and Stochastic Analog (BCSA) 방법을 소개하고자 한다. 또한 60개의 종관기상관측 (Automated Surface Observing System, ASOS)자료를 중심으로 생성한 세 가지 통계적 상세화방법의 과거재현성과 RCP4.5, RCP8.5 시나리오를 활용한 미래 불확실성 평가 결과를 이용하여 연구자들의 맞춤형 자료를 생산하고 평가하는데 도움을 줌으로써 다양한 기후자료의 효과적인 활용이 가능할 것으로 기대된다.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1109-1114
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• 2022

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 feasibility and applicability of a 3D-based equivalent model using dynamic condensation method for seismic analysis of a SMART control rod drive mechanism. The equivalent model is utilized for complicated seismic analysis during the design of the SMART. While the 1D-based beam-mass equivalent model is widely used in the nuclear industry for its calculation efficiency, the 3D-based equivalent model is suggested for the seismic analysis of SMART to enhance the analysis accuracy of the 1D-based equivalent model while maintaining its analysis efficiency. To verify the suggested model, acceleration response spectra from seismic analysis based on the 3D-based equivalent model are compared to those from the 1D-based beam-mass equivalent model and experiments. The accuracy and efficiency of the dynamic condensation method are investigated by comparison to analysis results based on the conventional modeling methodology used for seismic analysis.

• Advances in Computational Design
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• v.7 no.4
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• pp.345-369
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• 2022

Infectious disease emergency hospitals are usually temporarily built during the pneumonia epidemic with higher requirements regarding diagnosis and treatment efficiency, hygiene and safety, and infection control.This study aims to identify how the Building Information Modeling (BIM) + Industrialized Building System (IBS) approach could rapidly deliver an infectious disease hospital and develop site epidemic spreading algorithms. Coronavirus-19 pneumonia construction site spreading algorithm model mind map and block diagram of the construction site epidemic spreading algorithm model were developed. BIM+IBS approach could maximize the repetition of reinforced components and reduce the number of particular components. Huoshenshan Hospital adopted IBS and BIM in the construction, which reduced the workload of on-site operations and avoided later rectification. BIM+IBS integrated information on building materials, building planning, building participants, and construction machinery, and realized construction visualization control and parametric design. The delivery of Huoshenshan Hospital was during the most critical period of the Coronavirus-19 pneumonia epidemic. The development of a construction site epidemic spreading algorithm provided theoretical and numerical support for prevention. The agent-based analysis on hospital evacuation observed "arched" congestion formed at the evacuation exit, indicating behavioral blindness caused by fear in emergencies.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.81-91
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• 2023

As abnormal weather conditions escalate, water disasters such as droughts and floods occur more frequently. These natural disasters are fatal to agricultural reservoirs, where the operation techniques vary greatly depending on the season and weather conditions, and response through intake works is limited. In response, governments like the Korea Rural Community Corporation have researched efficient water supply methods through irrigation channels. Therefore, previous studies analyzed the irrigation process using numerical models to determine an efficient irrigation system. However, SWMM and EPANET used in previous studies are limited in quantitative agricultural irrigation process analysis. Therefore, this study developed AIRISS to simulate and analyze agricultural irrigation. Specifically, we simulated the irrigation process in the Ssangbong area of South Korea and simulated the irrigation process to verify the performance of the numerical model. AIRISS, developed in this study, is specialized in simulating the agricultural irrigation process. It can check the supply to each paddy and the condition of each paddy.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.5
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• pp.465-477
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• 2023

In proton exchange membrane fuel cell (PEMFC), proper thermal management of the stack and moisture generation by electrochemical reactions significantly affect fuel cell performance. In this study, the PEMFC dynamic characteristic model was developed through Simcenter AMESim, a development program. In addition, the developed model aims to understand the thermal resin balance of the stack and performance characteristics for input loads. The developed model applies the thermal management model of the stack and the moisture content and permeability model to simulate voltage loss and stack thermal behavior precisely. This study extended the C based AMESet (adaptive modeling environment submodeling tool) to simulate electrochemical reactions inside the stack. Fuel cell model of AMESet was liberalized with AMESim and then integrated with the balance of plant (BOP) model and analyzed. And It is intended to be used in component design through BOP analysis. The resistance loss of the stack and thermal behavior characteristics were predicted, and the impact of stack performance and efficiency was evaluated.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.281-293
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• 2023

This study addresses the optimal design methodology for switching between active electronically scanned array (AESA) radar operating modes to easily select the necessary information to reduce pilots' cognitive load and physical workload in situations where diverse and complex information is continuously provided. This study presents a procedure for defining a hidden Markov chain model (HMM) for modeling operating mode changes based on time series data on the operating modes of the AESA radar used by pilots while performing mission scenarios with inherent uncertainty. Furthermore, based on a transition probability matrix (TPM) of the HMM, this study presents a mathematical programming model for proposing the optimal structural design of AESA radar operating modes considering the manipulation method of a hands on throttle-and-stick (HOTAS). Fighter pilots select and activate the menu key for an AESA radar operation mode by manipulating the HOTAS's rotary and toggle controllers. Therefore, this study presents an optimization problem to propose the optimal structural design of the menu keys so that the pilot can easily change the menu keys to suit the operational environment.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.241-241
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• 2012

Semiconductor industry has been taking the advantage of improvements in process technology in order to maintain reduced device geometries and stringent performance specifications. This results in semiconductor manufacturing processes became hundreds in sequence, it is continuously expected to be increased. This may in turn reduce the yield. With a large amount of investment at stake, this motivates tighter process control and fault diagnosis. The continuous improvement in semiconductor industry demands advancements in process control and monitoring to the same degree. Any fault in the process must be detected and classified with a high degree of precision, and it is desired to be diagnosed if possible. The detected abnormality in the system is then classified to locate the source of the variation. The performance of a fault detection system is directly reflected in the yield. Therefore a highly capable fault detection system is always desirable. In this research, time series modeling of the data from an etch equipment has been investigated for the ultimate purpose of fault diagnosis. The tool data consisted of number of different parameters each being recorded at fixed time points. As the data had been collected for a number of runs, it was not synchronized due to variable delays and offsets in data acquisition system and networks. The data was then synchronized using a variant of Dynamic Time Warping (DTW) algorithm. The AutoRegressive Integrated Moving Average (ARIMA) model was then applied on the synchronized data. The ARIMA model combines both the Autoregressive model and the Moving Average model to relate the present value of the time series to its past values. As the new values of parameters are received from the equipment, the model uses them and the previous ones to provide predictions of one step ahead for each parameter. The statistical comparison of these predictions with the actual values, gives us the each parameter's probability of fault, at each time point and (once a run gets finished) for each run. This work will be extended by applying a suitable probability generating function and combining the probabilities of different parameters using Dempster-Shafer Theory (DST). DST provides a way to combine evidence that is available from different sources and gives a joint degree of belief in a hypothesis. This will give us a combined belief of fault in the process with a high precision.

• Korean Journal of Remote Sensing
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• v.24 no.2
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• pp.99-106
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• 2008

A synthetic aperture radar (SAR) system is of great interest in many fields of civil and military applications because of all-weather and luminance free imaging capability. SAR image quality parameters such as spatial resolution, peak to sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) can be normally estimated by modeling of impulse response function (IRF) which is obtained from various system design parameters such as altitude, operational frequency, PRF, etc. In modeling of IRF, however, background clutter environment surrounding the IRF is generally neglected. In this paper, analysis method for SAR mage quality is proposed in the real background clutter environment. First of all, SAR raw data of a point scatterer is generated based on various system parameters. Secondly, the generated raw data can be focused to ideal IRF by range Doppler algorithm (RDA). Finally, background clutter obtained from image of currently operating SAR system is applied to IRF. In addition, image quality is precisely analyzed by zooming and interpolation method for effective extraction of IRF, and then the effect of proposed methodology is presented with several simulation results under the assumption of estimation error of Doppler rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.3
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• pp.73-82
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• 2019

In order to build a smart factory, building a CPPS (Cyber Physical Product System) is an important system that must be accompanied. Through the CPPS, it is the reality of smart factories to move physical factories to a digital-based cyber world and to intelligently and autonomously monitor and control them. But The existing CPPS architectures present only an abstract modeling architecture, and the research that applied the OPC UA Framework (Open Platform Communication Unified Architecture), an international standard for data exchange in the smart factory, as the basic system of CPPS It was insufficient. Therefore, it is possible to implement CPPS that can include both cloud and IoT by collecting field data distributed by CPPS architecture applicable to actual factories and concentrating data processing in a centralized In this study, we implemented CPPS architecture through central OPC UA Server based on OPC UA conforming to central processing OPC UA Framework, and how CPPS logical process and data processing process are automatically generated through OPC UA modeling processing We have proposed the CPPS architecture including the model factory and implemented the model factory to study its performance and usability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.1-9
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• 2009

Bus information system(BIS), as a part of the intelligent transportation system(ITS), is one of the most advanced public transportation systems which provide the real-time bus traffic information for the users waiting the buses at the bus stop. However, correct bus information data, such as the present bus location, the user waiting time, the bus arrival time, etc. are not provided for the bus users because the proper bus arrival time predictive models are not used yet in most of the cities operating the bus information system, including the metropolitan City of Ulsan. Thus, the purpose in this study is to investigate real-time bus traffic characteristic data for identifying the bus operation characteristics on the arterial under the study in the metropolitan City of Ulsan, analyze real-time bus traffic characteristic data on the ID locations of the arterial under the study, construct the optimal unit segment models for the unit segments which are the bus stop, node and travel section using the exponential smoothing, weighted smoothing and Kalman Filter methods, respectively, and finally suggest the optimal integrated model for predicting the real-time bus arrival time at the bus stop of the arterial under the study.