• 지질공학
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• 제29권2호
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• pp.137-151
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• 2019

굴착공사 중 발생할 수 있는 지반함몰 사고를 방지하기 위해 굴착공사 주변 지층변화를 분석하고 모니터링하는 탐사기법과 기술이 필요함에 따라 다양한 탐사기술들을 적용, 보완함으로써 해석 기법을 향상시키는 것이 요구된다. 이 연구에서는 굴착공사 중 발생할 수 있는 지반침하 위험요소와 굴착, 지하수 등에 의한 이완영역을 탐지하기 위한 실규모 현장 실험을 실시하였다. 현장 실험을 수행하기 위해 실규모 굴착현장 테스트베드를 구축하고, 도심지 현장을 고려한 탐사법 중 전기비저항 탐사, 다중채널분석표면파탐사를 활용, 각 개별탐사의 적용 유효성 검토 및 모델링을 이용한 최적 탐사변수 도출과 설계, 탐사결과의 상호연관성을 비교 해석하였다. 이 연구 결과, 각 탐사별로 이완영역에 대한 영향을 확인할 수 있었으며, 특히 전기비저항탐사를 이용해 지하수면 위치를 확인하고 굴착에 대한 영향 파악할 수 있었다. 추후 지하수의 영향을 고려한, 즉 굴착면을 고려한 모델링에 대해 추가 연구가 필요할 것으로 보인다.

• Steel and Composite Structures
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• 제49권5호
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• pp.517-532
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• 2023

Tower structures have been widely used in communication and transmission engineering. The failure of joints is the leading cause of structure failure, which make it play a crucial role in tower structure engineering. In this study, the aluminum alloy three tube tower structure is taken as the prototype, and the middle joint of the tower was selected as the research object. Three different stainless steel-aluminum alloy composite joints (SACJs), denoted by TA, TB and TC, were designed. Finite element (FE) modeling analysis was used to compare and determine the TC joint as the best solution. Detail requirements of fasteners in the TC stainless steel-aluminum alloy composite joint (TC-SACJ) were designed and verified. In order to systematically and comprehensively study the mechanical properties of TC-SACJ under multi-directional loading conditions, the full-scale experiments and FE simulation models were all performed for mechanical response analysis. The failure modes, load-carrying capacities, and axial load versus displacement/stain testing curves of all full-scale specimens under tension/compression loading conditions were obtained. The results show that the maximum vertical displacement of aluminum alloy tube is 26.9mm, and the maximum lateral displacement of TC-SACJs is 1.0 mm. In general, the TC-SACJs are in an elastic state under the design load, which meet the design requirements and has a good safety reserve. This work can provide references for the design and engineering application of aluminum alloy tower structures.

• 한국지진공학회논문집
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• 제1권2호
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• pp.17-29
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• 1997

교량의 내진설계에 있어서 일반적인 중.소지간의 교량에 적용하도록 규정법 단일모드 스펙트럼 해석법은 비교적 작은 규모의 단순교량에 적용되는 있는 간단한 내진설계방법에며 국내외를 통틀어 가장 많이 사용되는 방법이다. 그러나 최근에 들어서부터 구조형상이 복잡해지고 지간이 길고 교각고가 높은, 규모가 큰 비정형 교량이 많이 시공되고 있으며 이러한 경우에는 교량의 안전과 경제적, 효율적인 설계를 위해서 반드시 다중모드 스펙트럼 해석법이나 입력지진파에 의한 시간이력해석에 의해서 검토되는 것이 바람직하다.다중모드 스펙트럼 해석법의 경우에는 교량의 형식, 경간의 수, 교각의 강성, 인접교각과의 상대적 강성 및 상부구조의 지지조건 등에 따라서 같은 유형의 교량이라 하더라도 진동응답은 각기 다르기 때문에 일률적인 규칙을 적용하는데에는 어려움이 있다. 따라서 본 연구에서는 도로교량에 대한 효율적인 내진설계가 이루어지기 위해서, 교량이 진동응답 및 특성을 파악할 수 있는 3차원 동적해석 프로그램을 작성하여 내진해석이 용이하게 이루어질 수 있도록 하였으며, 후처리 프로그램을 사용하므로써 동적해석프로그램에 의한 결과를 곧바로 내진설계에 반영할 수 있도록 하였으며, 후처리 프로그램을 사용하므로써 동적해석프로그램에 의한 결과를 곧바로 내진설계에 반영할 수 있도록 하였다. 또한 교량의 형식, 규모, 지지조건 등의 변화에 따른 동적 해석결과로부터 적절하고 효율적인 내진설계의 기준을 제시하였다.

• Nuclear Engineering and Technology
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• 제55권12호
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• pp.4357-4366
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• 2023

MARS-KS, a domestic regulatory confirmatory code of Republic of Korea, had been developed by integrating RELAP5/MOD2 and COBRA-TF. The integration of COBRA-TF allowed to extend the capability of MARS-KS, limited to one-dimensional analysis, to multi-dimensional analysis. The use of COBRA-TF was mainly focused on subchannel analyses for simulating multi-dimensional behavior within the reactor core. However, this feature has been remained as a legacy without ongoing maintenance. Meanwhile, MARS-KS also includes its own multidimensional component, namely MULTID, which is also feasible to simulate three-dimensional convection and diffusion. The MULTID is capable of modeling the turbulent diffusion using simple mixing length model. The implementation of the turbulent mixing is of importance for analyzing the reactor core where a disturbing cross-sectional structure of rod bundle makes the flow perturbation and corresponding mixing stronger. In addition, the presence of this turbulent behavior allows the secondary transports with net mass exchange between subchannels. However, a series of assessments performed in previous studies revealed that the turbulence model of the MULTID could not simulate the aforementioned effective mixing occurred in the subchannel-scale problems. This is obvious consequence since the physical models of the MULTID neglect the effect of mass transport and thereby, it cannot model the void drift effect and resulting phasic distribution within a bundle. Thus, in this study, the turbulence mixing model of the MULTID has been improved by means of the inter-channel mixing model, widely utilized in subchannel analysis, in order to extend the application of the MULTID to small-scale problems. A series of assessments has been performed against rod bundle experiments, namely GE 3X3 and PSBT, to evaluate the performance of the introduced mixing model. The assessment results revealed that the application of the inter-channel mixing model allowed to enhance the prediction of the MULTID in subchannel scale problems. In addition, it was indicated that the code could not predict appropriate phasic distribution in the rod bundle without the model. Considering that the proper prediction of the phasic distribution is important when considering pin-based and/or assembly-based expressions of the reactor core, the results of this study clearly indicate that the inter-channel mixing model is required for analyzing the rod bundle, appropriately.

• 한국진공학회지
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• 제18권3호
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• pp.164-175
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• 2009

전산 유체 역학 코드를 사용하여 안테나 내장형 유도 결합 플라즈마 시스템의 가스 유동 특성, 전력 흡수, 전자 온도, 전자 밀도, 화학종의 분포에 대해서 살펴보았다. 복잡한 현실적 3차원 시스템에 대한 안정한 수치해의 도출을 위해서 최적화된 격자생성 전략을 구사하였으며, 이를 이용하여 플라즈마 질화 시스템을 한 예로 전력 흡수, 가스 유동, 전자 온도, 전자 밀도, 화학종의 분포를 분석하였다. 금속 노출형 안테나의 경우 전력 도입부 쪽에 전력 흡수의 불균형이 모델에서 예측되었으며 유전체피복 안테나의 한 예에서 전력 흡수 표피 깊이가 실제 보고된 값인 53 mm와 잘 일치하는 50 mm로 예측되었다. 또한 수소연료 전지 분리판을 위한 고속 질화 공정용 시스템의 모델링에서도 산업용 대량 처리 시스템에 적절한 다중 분리판의 장입 간격을 가스 유동, 활발한 질화종인 질소 원자와 질소 분자 이온의 농도를 근거로 예측하였다.

• 한국대기환경학회지
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• 제33권3호
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• pp.217-232
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• 2017

An Eulerian-Lagrangian hybrid modeling system to analyze physical and chemical processes during the transport of air parcels was developed. The Backward-tracking Model Analyzer (BMA) was designed to take advantages of both Eulerian and Lagrangian modeling approaches. Simulated trajectories from the National Oceanic and Atmospheric Administration HYSPLIT model were combined with the US Environmental Protection Agency Community Multi-scale Air Quality (CMAQ)-simulated concentrations and additional diagnostic analyses. In this study, we first introduced a generalized methodology to seamlessly match polylines (HYSPLIT) and threedimensional polygons (CMAQ), which enables mass-conservative analyses of physio-chemical processes of transporting air parcels. Two applications of the BMA were conducted: (1) a long-range transport case of pollutant plume across the Yellow Sea using CMAQ Integrated Process Rate analyses, and (2) a domestic circulation of pollutants within (and near) the South Korea based on the sulfate tracking analyzer. The first episode demonstrated a secondary formation of nitrate and ammonium during the transport over the Yellow Sea while sulfate is mostly transported after being formed over the China, and the second episode demonstrated a dominant impact of boundary condition with active sulfate formation from gas-phase oxidation near the Seoul Metropolitan Area.

• Biotechnology and Bioprocess Engineering:BBE
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• 제5권5호
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• pp.355-361
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• 2000

A recycling reactor system operated under sequential anoxic and oxic conditions for the treatment of swine wastewater has been developed, in which piggery slurry is fermentatively and aerobically treated and then part of the effluent is recycled to the pigsty. This system significantly removes offensive smells (at both the pigsty and the treatment plant), BOD and others, and may be cost effective for small-scale farms. The most dominant heterotrophic were, in order, Alcaligenes faecalis, Brevundimonas diminuta and Streptococcus sp., while lactic acid bacteria were dominantly observed in the anoxic tank. We propose a novel monitoring system for a recycling piggery slurry treatment system through the use of neural networks. In this study, we tried to model the treatment process for each tank in the system (influent, fermentation, aeration, first sedimentation and fourth sedimentation tanks) based upon the population densities of the heterotrophic and lactic acid bacteria. Principal component analysis(PCA) was first applied to identify a relationship between input and output. The input would be microbial densities and the treatment parameters, such as population densities of heterotrophic and lactic acid bacteria, suspended solids(SS), COD, NH$_4$(sup)+-N, ortho-phosphorus (o-P), and total-phosphorus (T-P). then multi-layer neural networks were employed to model the treatment process for each tank. PCA filtration of the input data as microbial densities was found to facilitate the modeling procedure for the system monitoring even with a relatively lower number of imput. Neural network independently trained for each treatment tank and their subsequent combined data analysis allowed a successful prediction of the treatment system for at least two days.

• 한국기후변화학회지
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• 제9권1호
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• pp.1-12
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• 2018

There is an emphasis on the importance of adaptation against to climate change and related natural disasters. As a result, various climate information with different time-scale can be used for science-based climate change adaptation policy. From the aspects of Global Framework for Climate Services (GFCS), various time-scaled climate information in Korea is mainly produced by Korea Meteorological Administration (KMA) However, application of weather and climate information in different application sectors has been done individually in the fields of agriculture and water resources mostly based-on weather information. Furthermore, utilization of climate information including seasonal forecast and climate change projections are insufficient. Therefore, establishment of the Cooperation Center for Application of Weather and Climate Information is necessary as an institutional platform for the UIP (User Interface Platform) focusing on multi-model ensemble (MME) based climate service, seamless climate service, and climate service based on multidisciplinary approach. In addition, APCC Integrated Modeling Solution (AIMS) was developed as a technical platform for UIP focusing on user-centered downscaling of various time-scaled climate information, application of downscaled data into impact assessment modeling in various sectors, and finally producing information can be used in decision making procedures. AIMS is expected to be helpful for the increase of adaptation capacity against climate change in developing countries and Korea through the voluntary participation of producer and user groups within in the institutional and technical platform suggested.

• 신재생에너지
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• 제9권3호
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• pp.20-28
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• 2013

The gasification process has developed to convert coal into the more useful energy and material since decades. Despite the numberous design of ones, entrained flow gasifier of the major companies has had an advantage on the market. Because it has a merit of full-scale and high performance plant. In this paper, the gasification technologies of GE energy, Phillips, Siemens and Shell have been reviewed to compare their characteristics and a high performance gasification process was suggested. And the simulation model of gasifiers using Aspen Plus offered the quantitative comparison data for difference designs. The simulation results revealed the poor performance of the slurry feed than dry design. The corresponding cold gas efficiency of 77% is much lower than the 80.3% for the dry feed cases. The exergy analysis of the difference syngas quenching system showed that chemical quenching is superior to another. The results of analysis recommend the two stage gasifier with dry multi-feeder as the energy effective design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권5호
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• pp.1252-1271
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• 2013

Automatic image annotation has become an increasingly important research topic owing to its key role in image retrieval. Simultaneously, it is highly challenging when facing to large-scale dataset with large variance. Practical approaches generally rely on similarity measures defined over images and multi-label prediction methods. More specifically, those approaches usually 1) leverage similarity measures predefined or learned by optimizing for ranking or annotation, which might be not adaptive enough to datasets; and 2) predict labels separately without taking the correlation of labels into account. In this paper, we propose a method for image annotation through collaborative similarity metric learning from dataset and modeling the label correlation of the dataset. The similarity metric is learned by simultaneously optimizing the 1) image ranking using structural SVM (SSVM), and 2) image annotation using correlated label propagation, with respect to the similarity metric. The learned similarity metric, fully exploiting the available information of datasets, would improve the two collaborative components, ranking and annotation, and sequentially the retrieval system itself. We evaluated the proposed method on Corel5k, Corel30k and EspGame databases. The results for annotation and retrieval show the competitive performance of the proposed method.