• 한국화재소방학회논문지
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• 제23권5호
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• pp.143-152
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• 2009

초고층건물의 수직통로에서 발생하는 연돌효과의 기체역학적 특성과 관련된 차압과 중성대의 위치 계산 및 연돌효과 발생의 가시화를 위하여 3가지 형태의 개구부를 갖는 단일 단순수직통로에 대하여 CFD 모델을 사용하여 수치해석을 하였다. 연돌효과의 차압은 이론식 계산 결과와 비교 시 수직통로의 높이가 높아질수록 차이가 커진다. 중성대 위치는 연돌효과 초기(t = 10s)에 Type A의 경우 수직통로의 높이가 30m 미만인, Type B의 경우 30m 이상인 모델에서 이론식 계산 결과와의 편차가 5% 미만으로 잘 일치한다. 따라서 수직통로 높이가 30m 이상인 다중개구부 수직통로(Type B)의 경우 CFD 모델을 사용하여 중성대 위치를 계산하는 것이 가능하다. 연돌효과의 가시화를 통하여 연돌효과의 공기 유동 현상을 쉽게 이해할 수 있다.

• Journal of Information Processing Systems
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• 제8권1호
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• pp.55-66
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• 2012

This paper presents a dual modeling method that simulates the graphic and haptic behavior of a volumetric deformable object and conveys the behavior to a human operator. Although conventional modeling methods (a mass-spring model and a finite element method) are suitable for the real-time computation of an object's deformation, it is not easy to compute the haptic behavior of a volumetric deformable object with the conventional modeling method in real-time (within a 1kHz) due to a computational burden. Previously, we proposed a fast volume haptic rendering method based on the S-chain model that can compute the deformation of a volumetric non-rigid object and its haptic feedback in real-time. When the S-chain model represents the object, the haptic feeling is realistic, whereas the graphical results of the deformed shape look linear. In order to improve the graphic and haptic behavior at the same time, we propose a dual modeling framework in which a volumetric haptic model and a surface graphical model coexist. In order to inspect the graphic and haptic behavior of objects represented by the proposed dual model, experiments are conducted with volumetric objects consisting of about 20,000 nodes at a haptic update rate of 1000Hz and a graphic update rate of 30Hz. We also conduct human factor studies to show that the haptic and graphic behavior from our model is realistic. Our experiments verify that our model provides a realistic haptic and graphic feeling to users in real-time.

• 한국가시화정보학회지
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• 제19권2호
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• pp.56-62
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• 2021

Solid oxide fuel cells (SOFCs) is the high efficiency fuel cell operating at high temperatures ranging from 700-1000℃. Design of the flow paths of the fuel and air in SOFCs is important to improve cell performance and prevent cell degradation. However, the uneven distribution of current density in the traditional type having one inlet and outlet causes cell degradation. In this regard, the parallel flow path with two inlet and outlets was designed and compared to the traditional type based on computational fluid dynamics (CFD) simulation. To check the cell performance, hydrogen distribution, velocity distribution and current density distribution were monitored. The results validated that the parallel designs with two inlets and outlets have a higher cell performance compared to the traditional design with one inlet and outlet due to a larger reaction area. In case of uniform-type paths, more uniform current density distribution was observed with less cross-sectional variation in flow paths. In case of contracted and expanded inflow paths, significant improvement of performance and uniform current density was not observed compared to uniform parallel path. Considering SOFC cell with uniform current density can prevent cell degradation, more suitable design of SOFC cell with less cross-sectional variation in the flow path should be developed. This work can be helpful to understand the role of flow distribution in the SOFC performance.

• Journal of Korean Neurosurgical Society
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• 제65권5호
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• pp.697-709
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• 2022

Objective : The present study aimed to identify the function of ischemic stroke (IS) patients' peripheral blood and its role in IS, explore the pathogenesis, and provide direction for clinical research progress by comprehensive bioinformatics analysis. Methods : Two datasets, including GSE58294 and GSE22255, were downloaded from Gene Expression Omnibus database. GEO2R was utilized to obtain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed using the database annotation, visualization and integrated discovery database. The protein-protein interaction (PPI) network of DEGs was constructed by search tool of searching interactive gene and visualized by Cytoscape software, and then the Hub gene was identified by degree analysis. The microRNA (miRNA) and miRNA target genes closely related to the onset of stroke were obtained through the miRNA gene regulatory network. Results : In total, 36 DEGs, containing 27 up-regulated and nine down-regulated DEGs, were identified. GO functional analysis showed that these DEGs were involved in regulation of apoptotic process, cytoplasm, protein binding and other biological processes. KEGG enrichment analysis showed that these DEGs mediated signaling pathways, including human T-cell lymphotropic virus (HTLV)-I infection and microRNAs in cancer. The results of PPI network and cytohubba showed that there was a relationship between DEGs, and five hub genes related to stroke were obtained : SOCS3, KRAS, PTGS2, EGR1, and DUSP1. Combined with the visualization of DEG-miRNAs, hsa-mir-16-5p, hsa-mir-181a-5p and hsa-mir-124-3p were predicted to be the key miRNAs in stroke, and three miRNAs were related to hub gene. Conclusion : Thirty-six DEGs, five Hub genes, and three miRNA were obtained from bioinformatics analysis of IS microarray data, which might provide potential targets for diagnosis and treatment of IS.

• 한국분무공학회지
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• 제28권1호
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• pp.1-9
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• 2023

In the cylinder of gasoline direct injection engines, the spray targeting from injectors is of great significance for fuel consumption and pollutant emissions. The automotive industry is putting a lot of effort into improving injector targeting accuracy. To improve the targeting accuracy of injectors, it is necessary to develop models that can predict the spray targeting positions. When developing spray targeting models, the most used technique is computational fluid dynamics (CFD). Recently, due to the superiority of machine learning in prediction accuracy, the application of machine learning in this field is also receiving constant attention. The purpose of this study is to build a machine learning model that can accurately predict spray targeting based on the design parameters of injectors. To achieve this goal, this study firstly used laser sheet beam visualization equipment to obtain many spray cross-sectional images of injectors with different parameters at different injection pressures and measurement planes. The spray images were processed by MATLAB code to get the targeting coordinates of sprays. A total of four models were used for the prediction of spray targeting coordinates, namely ANN, LSTM, Conv1D and Conv1D & LSTM. Features fed into the machine learning model include injector design parameters, injection conditions, and measurement planes. Labels to be output from the model are spray targeting coordinates. In addition, the spray data of 7 injectors were used for model training, and the spray data of the remaining one injector were used for model performance verification. Finally, the prediction performance of the model was evaluated by R² and RMSE. It is found that the Conv1D&LSTM model has the highest accuracy in predicting the spray targeting coordinates, which can reach 98%. In addition, the prediction bias of the model becomes larger as the distance from the injector tip increases.

• 한국가시화정보학회지
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• 제21권1호
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• pp.80-93
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• 2023

We performed numerical simulations of blood flow in an arterial cerebral artery aneurysm to investigate the hemodynamic behavior after coil embolization. A patient-specific model was created based on CTA data. We also conducted the coil embolization simulation to obtain the coil placement within the aneurysm. Blood was assumed to be an incompressible Newtonian fluid, and both the vessel and coil were considered rigid walls. The pulsatile boundary condition was applied at the inlet, and the outflow boundary conditions were used at the outlets. Our findings demonstrated that the coil embolization significantly reduces the blood volume flowrate entering the aneurysm by effectively blocking the inflow jet, leading to a decrease in both TAWSS and WSS, especially at the systolic peak in the impingement zone. While several high OSI regions disappeared over the aneurysm surface, we observed high OSI regions with a relatively small area where the coil did not completely occlude the aneurysm. Overall, these results quantitatively analyzed the effectiveness of coil embolization by focusing on hemodynamic indicators, potentially preventing aneurysm rupture. The present work could contribute to the development of patient-specific coil embolization.

• 한국산학기술학회논문지
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• 제18권2호
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• pp.254-260
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• 2017

사회기반시설물은 적절한 수명관리를 통해 경제적이고 안전한 구조성능을 유지한다. 일반적으로 최적화 기법을 적용하여, 유지보수의 시점과 방법을 결정하게 되는데, 이 적용에 있어서 단일 목적함수만을 고려하기 보다는 다수의 목적함수를 동시에 고려하는 것이 보다 합리적인 의사결정을 유도한다. 최근까지 수명관리에 관련한 연구는 생애주기 비용 최소화 또는 구조성능 최대화와 관련한 목적함수를 적용하여 왔으며, 새로운 확률론적 구조성능 및 안전성 평가 기법을 이용하여 다양한 형태의 목적함수를 개발/적용하고 있다. 이러한 다수의 목적함수를 동시에 고려하는 다목적 최적화 기반 사회기반시설물 수명관리가 최근 국내외에서 많이 적용되고 있다. 하지만, 수명관리 최적화를 위한 목적함수의 개수가 증가함에 따라 신뢰성있는 결과를 얻기 위해서는 많은 계산시간이 소요되며, 특히 확률론적 계산을 위한 시뮬레이션 기법이 적용되는 목적함수의 경우 계산시간은 더욱 증가하게 된다. 또한, 목적함수의 개수 증가에 따라 계산결과의 차수가 증가하기 때문에 이를 시각화하고 나아가 의사결정에 어려움이 발생한다. 따라서, 본 논문에서는 다목적 최적화 문제의 계산된 결과를 바탕으로 한 의사결정의 효율성 향상을 위해 최소 필수 목적함수를 구별하는 목적감소 기법을 적용하여 콘크리트 교량 상판의 수명관리에 대한 연구를 수행하였으며, 최초 4개의 목적함수가 2개까지 감소되는 결과를 보여준다.

• 생명과학회지
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• 제18권4호
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• pp.565-571
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• 2008

생물정보학의 발전으로 다양한 형태의 생물정보가 컴퓨터 프로그램에 의해 양산되고 있다. 단순한 서열간의 비교나 작은 규모의 자료를 처리하기 보다는 다각화된 정보와 대규모의 생물정보를 취급하고 있다. 그 중에서 시각화와 annotation를 위한 도구개발은 지난 10년간 많은 연구가 되고 있는 분야이다. 그럼에도 일반화된 도구 개발은 생물정보의 다양성과 사용자 요구의 다양화로 인해 매우 어렵다. 본 논문에서는 유전체간 알려진 정보와 다중 관계 그래프를 이용하여 이를 annotation하고 시각화하는 GenoVA 시스템을 제안한다. 다중 정렬을 위한 몇 개의 프로그램이 존재하지만 그 방법들이 서열내의 복잡성 때문에 많은 정보가 누락된다. 따라서 제안된 방법에서는 pairwise alignment를 확장하여 모든 유전체간 비교를 통해 연관성 도출한다. 유전체간 보존되는 영역의 빈도수와 BLAST 점수가 높은 것을 블록노드라 하고 이들 간의 연관관계를 다중 관계 그래프로 표현하였다. 또한 GenoVA는 알려진 정보, COG, 유전자를 시각화하고 다중 관계 그래프의 한 영역을 중심으로 클러스터링된 경로를 계층적으로 보여주었다. 이때 누락되거나 알려지지 않은 유전자나 다른 annotation정보 추출할 수 있다. 본 논문의 실험을 위해 열 개의 박테리아 유전체가 사용되었고 시각화와 annotation을 위한 자료로 활용하였다. GenoVA는 새로운 유전체에 대한 개략적이고 전산적 annotation을 직관적이고 편리하게 제공한다.

• Journal of Computational Design and Engineering
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• 제1권3호
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• pp.173-186
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• 2014

The failure of a subsea production plant could induce fatal hazards and enormous loss to human lives, environments, and properties. Thus, for securing integrated design safety, core source technologies include subsea system integration that has high safety and reliability and a technique for the subsea flow assurance of subsea production plant and subsea pipeline network fluids. The evaluation of subsea flow assurance needs to be performed considering the performance of a subsea production plant, reservoir production characteristics, and the flow characteristics of multiphase fluids. A subsea production plant is installed in the deep sea, and thus is exposed to a high-pressure/ low-temperature environment. Accordingly, hydrates could be formed inside a subsea production plant or within a subsea pipeline network. These hydrates could induce serious damages by blocking the flow of subsea fluids. In this study, a simulation technology, which can visualize the system configuration of subsea production processes and can simulate stable flow of fluids, was introduced. Most existing subsea simulations have performed the analysis of dynamic behaviors for the installation of subsea facilities or the flow analysis of multiphase flow within pipes. The above studies occupy extensive research areas of the subsea field. In this study, with the goal of simulating the configuration of an entire deep sea production system compared to existing studies, a DES-based simulation technology, which can logically simulate oil production processes in the deep sea, was analyzed, and an implementation example of a simplified case was introduced.

• 한국전산구조공학회논문집
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• 제28권2호
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• pp.177-185
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• 2015

도시기반 라이프라인은 지진발생시 시설물의 붕괴뿐만 아니라 붕괴로 인한 도시기능 마비, 대형화재와 같은 2차 피해를 동반하여 막대한 사회 경제적 손실을 야기할 것으로 예측된다. 이에 대한 대비책으로 국내에서는 지진재해대응시스템을 운영 중이며, 지진재해대응시스템은 각 시설물별 지진취약도 모델을 통해서 시설물의 파괴확률을 산정하고, 지진재해 정도를 평가한다. 따라서 본 논문에서는 국내 지반특성을 고려하여 도시기반 라이프라인 시설물 중 매설가스배관의 시간이력 해석을 수행하였고, 확률론적인 해석방법인 최우도추정법을 이용하여 지진취약도 모델을 개발하였다. 해석모델은 국내 대표도시인 서울지역에 매설된 고압관과 중압관으로 선정하였으며, 지반의 모델링은 Winkler foundation 모델을 이용하였다. 또한 개발된 취약도 모델의 GIS 적용방안을 제시하였다.