• Proceedings of the Korean Nuclear Society Conference
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• 1997.05a
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• pp.409-414
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• 1997

Reflood model in RELAP5/MOD3.1 are modified to improve the unrealistic prediction results of the model. In the new method, the modified Zuber pool boiling critical heat flux (CHF) correlation is adopted. The reflood drop size is characterized by the use of We=1.5 and the minimum drop size of 0.0007 m for $p^{*}\;{\leq}\;0.025$. To describe the wall to vapor heat transfer at low pressure and low flow condition, the Webb-Chen correlation is utilized . The suggested method has been verified through the simulations of the Lehigh University rod bundle reflood tests. Through sensitivity study it is shown that the effect of drag coefficients is dominant in the reflood model. It is proved that the present modifications result in much more improved quench behavior and accurate wan and vapor temperature predictions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.355-358
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• 2004

In this study, the deformation characteristics of grain-size controlled rheology materials surfaces were investigated as a part of the research on the surface crack prediction in semi-solid formed automobile components. The microstructure of rheology Al-Si alloys consists of primary and eutectic regions. In eutectic regions the crack initiation begins with initial fracture of the eutectic silicon particles and inside other intermetallic phases. Nano-deformation characteristics in the eutectic and primary region of semi-solid aluminum alloys (356 alloy and 319 alloy) were investigated through the nanoindentation/scratch experiments and the AFM observation.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.71-78
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• 2003

The exit burrs in the micro-drilling of precision miniature holes are of interest, especially for ductile materials. As burrs from this process can be difficult to remove, it is important to acquire the way of predicting burr types as well as optimal cutting conditions which minimize the burrs. In this paper, an artificial neural network was used for the prediction of burr formation in micro-drilling. First, the influence of cutting conditions including cutting speed, feed and drill diameter on the exit burr characteristics, such as burr size and type, were observed and analyzed. Then. the burr types were classified by using the influential experimental data as input parameters to the neural nets.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.287-292
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• 2003

The large-scale direct tension tests of plain concrete were performed and then the complete load-CMOD(crack mouth opening displacement) curves with a stable postpeak descending part were presented. Two independently controlled actuators were used to ensure a homogeneous increasing of CMOD in both notches of a specimen and to avoid secondary flexural stresses. It was compared the fracture energies from the test results with them from a classical prediction equation by Bazant and Oh (983), The results are indicated that the fracture energies from these large-scale direct tensile tests are large as 1.5-2 times on average against them from the Bazants prediction equation. But the tensile strength for large-size specimens was about half of the values determined from the splitting tensile strength tests for 10 by 20mm cylindrical specimens due to size effect.

• Transactions of Materials Processing
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• v.9 no.1
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• pp.59-65
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• 2000

Most studies of failure analysis in ductile metals have been based on the classical plasticity theory using the local constitutive relations. These frequently yields a physically unrealistic solution, in which a numerical prediction of the onset of a deformation localization shows an inherent mesh-size sensitivity. A one way to remedy the spurious mesh sensitivity resulted in the unreasonable results is to incorporate the non-local plasticity into the simulation model, which introduce an internal (material) length-scale parameter into the classical constitutive relations. In this paper, a non-local version of the modified Gurson constitutive relation has been introduced into the finite element formulation of the simulation for plane strain compression of the visco elastic-plastic void material. By introducing the non-local constitutive relations we could successfully removed the inherent mesh-size sensitivity for the prediction of the deformation localization. The effects of non-local constitutive relation are discussed in terms of the load-stroke curve and the strain distributions accross the shear band.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.84-89
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• 2004

When the tube contacted to support, anti-vibration bar of the steam generator in nuclear power plant, the contact area is worn out by their relative displacement and contact force. Connors and Au-Yang found the relation between tube worn displacement and volume, or normal work rate at given gap size. The present analysis is obtained the relation between tube worn displacement and normal work rate at various gap size modifying Au-Yang's result. The results are compared with Connors and Yettisir and Pettigrew's results. The comparison shows that Yettisir and Pettigrew result is fairly good agreement with Connors and present results with gap clearance, 0.015in.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.12
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• pp.1341-1346
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• 2011

Currently, many researches are carried out for laser assisted machining, which is one of the important fields in materials difficult to process. However, a prediction of heat source is difficult because of moving heat source. In this paper, a thermal analysis of laser assisted machining of plate by change of heat source size is performed, and preheating temperature by adjusting the feed rate is controlled. It was recognized that the maximum preheating temperature increases according to the decrease in heat source size, and feed rate need to adjust as high speed. The results of this analysis can be used as a reference for preheating temperature prediction in laser assisted milling.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.11a
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• pp.160-162
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• 2018

본 논문에서는 압축 영역에서 열 영상을 이용한 딥러닝 기반의 객체 검출 방법을 제안한다. 비디오 압축 표준인 High Efficiency Video Coding(HEVC)를 이용하여 부보화된 비트스트림으로부터 Intra Prediction Mode(IPM), Prediction Unit Size(PUS), Transform Unit Size(TUS)를 추출하고 3 채널 영상으로 변환하고 객체 검출 네트워크인 YOLO 에 입력으로 넣어주어 최종적으로 객체의 위치 및 객체의 종류를 예측한다. 실험결과로써 복원된 열 영상과 검출된 결과를 주관적으로 보여줌으로써 압축영역에서 열영상을 이용한 객체 검출이 가능함을 보인다.

• Geomechanics and Engineering
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• v.36 no.1
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• pp.83-97
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• 2024

It is important to make reasonable prediction about the long-term deformation of high rockfill geostructures. However, the deformation is usually underestimated using the rockfill parameters obtained from laboratory tests due to different size effects, which make it necessary to identify parameters from in-situ monitoring data. This paper proposes a novel hybrid back-analysis method with a modified objective function defined for the time-dependent back-analysis problem. The method consists of two stages. In the first stage, an improved weighted average method is proposed to quickly narrow the search region; while in the second stage, an adaptive response surface method is proposed to iteratively search for the satisfactory solution, with a technique that can adaptively consider the translation, contraction or expansion of the exploration region. The accuracy and computational efficiency of the proposed hybrid back-analysis method is demonstrated by back-analyzing the long-term deformation of two high embankments constructed for airport runways, with the rockfills being modeled by a rheological model considering the influence of stress states on the creep behavior.

• Journal of IKEEE
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• v.23 no.4
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• pp.1430-1439
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• 2019

In Functional Mockup Interface(FMI)-based co-simulation, a bisectional algorithm can be used to find the zerocrossing point as a way to improve the accuracy of the simulation results. In this paper, the proposed master algorithm(MA) analyzes the repeated interval graph and predicts the next interval by applying the Markov Chain to the step size. In the simulation, we propose an algorithm to minimize the rollback by storing the step size that changes according to the graph type as an array and applying it to the next prediction interval when the rollback occurs in the simulation. Simulation results show that the proposed algorithm reduces the simulation time by more than 20% compared to the existing algorithm.