• 한국해양공학회지
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• 제31권1호
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• pp.1-7
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• 2017

There are two wave modes induced by an oscillating body on the free surface of a two-layer fluid: the barotropic and baroclinic modes. To investigate the generated waves composed of two modes, a radiation problem involving a heaving rectangular body was solved in a numerical wave tank. A new artificial damping zone scheme was developed and applied in the frequency-domain analysis. The performance of this damping scheme was compared with given radiation boundary conditions for various conditions. The added mass and radiation damping coefficients for the heaving rectangular body were also calculated for various fluid-density ratios.

• 기술사
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• 제45권2호
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• pp.28-32
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• 2012

The European Alps face a number of major threats - from habitat loss to pollution, from mass tourism to the impacts of climate change. The European alpine climate has changed significantly during the past century, with temperatures increasing more than twice the global average. This makes alpine mountains especially vulnerable to changes in the hydrological cycle and decreases in snow and glacier cover, which are already occurring. In winter, artificial snow-making is currently the most widespread strategy to extend and supplement natural snow cover and secure winter tourism. Artificial snow-making is not only very costly, but also has knock-on effects such as increased water consumption and energy demand or ecological damage, which may lead to negative externalities. The European Alps facing the challenge of changing climate and anthropogenic pressures.

• 한국정밀공학회지
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• 제13권9호
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• pp.94-103
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• 1996

This paper is concerned with the theroretical and experimental study on the force control of a miniature robotic finger that grasps an object at three other positions with the fingertip. The artificial finger is uniform flexible cantilever beam equipped with a distributed set of compact grasping force secnsors. Control action is applied by a qiexoceramic bimorph strip placed at the base of the finger. The mathematical model of the assembled electro-mechanical system is developed. The distributed sensors are described by a set of concentrated mass-spring system. The formulated equations of motion are then applied to a control problem which the finger is commanded to grasp an object The PID-controller is introduced to drive the finger. The usefulness of the proposed control technique is verified by simulation and experiment.

• International Journal of Industrial Entomology and Biomaterials
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• 제33권1호
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• pp.15-23
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• 2016

One major constraint in the development and implementation of a successful and cost-effective area-wide integrated pest management (AW-IPM) programme with a SIT component for Bactrocera oleae (Diptera: Tephritidae) is the ability to produce a large number of high quality mass-reared individuals. The aim of this study was to develop a more efficient and practical egg collection system in an attempt to improve the mass-rearing of this species. The following basic parameters were examined: egg production per female, egg hatch, pupal recovery, pupal weight, adult emergence and percentage of fliers. Three different strains (Israel wild-type, France wild-type, and Greece laboratory) were tested and each strain was evaluated for six generations. Female flies of the Israel strain produced significantly more eggs per female than the other two strains, but egg hatch was significantly lower. Egg hatch of the France wild type and the Greece laboratory strain was similar. For all other parameters, there was no significant difference between strains; however, there was a significant generational effect for all parameters observed. As a result of this study, a protocol was developed for the mass-rearing of this species that included the use of large adult holding cages that could house up to 96,000 flies per cage. The newly developed method of egg collection using a flat wax panel as one of the sides of an adult holding cage proved to be cost-effective, efficient, making colony growth easier for industrial mass-rearing.

• KEPCO Journal on Electric Power and Energy
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• 제6권3호
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• pp.305-313
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• 2020

전력송전을 위한 터널식 전력구는 점차 시공실적이 증가하고 있는 추세이며, 해저 및 대심도 등 시공환경이 어려운 구간의 건설도 증가하고 있다. 이에 소단면 쉴드TBM의 효율적 운영을 위해 굴진율 및 설계모델이 필요하다. 그러나, 제한된 지반조사 회수 및 굴착면 맵핑으로 인하여 암반특성과 굴진데이터를 정확히 매칭시켜 상호간 상관관계 및 굴진율 모델을 도출하는데 어려움이 있다. 이에 소단면 쉴드TBM에 적합한 굴진율 및 설계모델을 제시하기 위하여 커터헤드의 직경이 3.56 m인 실험용 EPB 쉴드TBM을 제작하고, 총 부피 87.5 ㎥인 인공암반 내에서 총 19번의 실대형 굴진실험을 수행하였다. 본 실험은 70MPa의 균질한 암반강도에서 수행되었기 때문에 운전변수인 추력과 커터헤드의 RPM에 따른 굴진율과 기계데이터간 상관관계를 효율적으로 분석할 수 있으며, 실제 굴착메커니즘과 동일하기 때문에 도출된 압입깊이와 토크값은 활용성이 높다. 본 연구를 통해 디스크커터 당 연직력과 압입깊이의 상관관계 및 연직력과 회전력의 상관관계를 도출하였다. 이러한 상관관계들을 이용하여 70 MPa급 암반에 대해 굴진율 예측과 TBM 설계가 가능할 것으로 판단한다. 또한, 인공암반의 RQD가 100%로 현장적용에 대한 한계점에 대해 FPI의 개념을 도입하여 굴진율 모델의 활용성을 증대시키고자 하였다.

• Nuclear Engineering and Technology
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• 제53권4호
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Journal of Microbiology and Biotechnology
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• 제8권1호
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• pp.1-7
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• 1998

• 시스템엔지니어링학술지
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• 제16권2호
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• pp.38-46
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• 2020

The accurate measurement of critical heat flux (CHF) in flow boiling is important for the safety requirement of the nuclear power plant to prevent sharp degradation of the convective heat transfer between the surface of the fuel rod cladding and the reactor coolant. In this paper, a System Engineering approach is used to develop a model that predicts the CHF using machine learning. The model is built using artificial neural network (ANN). The model is then trained, tested and validated using pre-existing database for different flow conditions. The Talos library is used to tune the model by optimizing the hyper parameters and selecting the best network architecture. Once developed, the ANN model can predict the CHF based solely on a set of input parameters (pressure, mass flux, quality and hydraulic diameter) without resorting to any physics-based model. It is intended to use the developed model to predict the DNBR under a large break loss of coolant accident (LBLOCA) in APR1400. The System Engineering approach proved very helpful in facilitating the planning and management of the current work both efficiently and effectively.

• Geomechanics and Engineering
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• 제31권4호
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• pp.353-364
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• 2022

This study presents a hybrid algorithm for classifying the rock joints, where the improved artificial bee colony (IABC) and the fuzzy C-means (FCM) clustering algorithms are incorporated to take advantage of the artificial bee colony (ABC) algorithm by tuning the FCM clustering algorithm to obtain the more reasonable and stable result. A coefficient is proposed to reduce the amount of blind random searches and speed up convergence, thus achieving the goals of optimizing and improving the ABC algorithm. The results from the IABC algorithm are used as initial parameters in FCM to avoid falling to the local optimum in the local search, thus obtaining stable classifying results. Two validity indices are adopted to verify the rationality and practicability of the IABC-FCM algorithm in classifying the rock joints, and the optimal amount of joint sets is obtained based on the two validity indices. Two illustrative examples, i.e., the simulated rock joints data and the field-survey rock joints data, are used in the verification to check the feasibility and practicability in rock engineering for the proposed algorithm. The results show that the IABC-FCM algorithm could be applicable in classifying the rock joint sets.

• 한국지반공학회논문집
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• 제22권8호
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• pp.107-118
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• 2006

터널과 관련된 여러 영향인자중 시간의 따른 투수상태와 지반의 장기거동은 터널의 이상 거동을 이해하는데 있어서 중요하다. 터널은 이러한 인자에 의해서 심각한 손상을 입을 수 있으나 시공 후 이러한 인자들에 의해 발생한 영향을 정량적으로 분석해 내는 것은 쉽지 않다. 입력과 출력간의 상관관계가 비교적 독립적이라면 터널거동에 미치는 인자들의 영향은 역해석 기법을 적용하여 예측할 수 있다. 모델을 구성하는 입출력 자료의 특성에 따라 인공신경망 기법이나 최소제곱법 등 다양한 역해석 방법이 개발 될 수 있으며 수치해석, 실험 또는 계측 결과가 역해석 모델의 구성 및 검증을 위해 쓰일 수 있다. 본 연구에서는 시공 후 터널의 내공 변위 변화로부터 투수 및 지반의 장기거동과 관련된 인자들 중 배수재의 투수계수, 지하수위, 장기 이완 하중 크기 및 암반 손상 패턴 등의 변화에 의한 영향을 정량적으로 분석할 수 있는 역해석 기법을 개발하였다. 역해석은 인공신경망 기법을 적용하였으며 학습데이터 확보를 위해 수치해석 모델이 개발 되고 다양한 하중 상태에 대한 거동 분석이 이루어졌다.