• 대한토목학회논문집
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• 제29권5A호
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• pp.511-518
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• 2009

본 연구에서는 콘크리트와 철근과의 부착강도에 영향을 미치는 요인 중 철근의 위치를 수평하부철근(Horizontal reinforcement at Bottom position, HB), 수평상부철근(Horizontal reinforcement at Top position, HT), 및 수직철근(Vertical reinforcement type, V)으로 변화시킨 시험체를 제작하여 3수준의 콘크리트 강도 변화(30, 50 및 70 MPa)에 따른 고유동 자기충전 콘크리트(High flowing Self-compacting Concrete, HSCC) 및 일반콘크리트(Conventional Concrete, CC)와 이형철근의 부착 특성을 비교 분석 하였다. HSCC 및 CC의 상부근 철근계수를 평가하기 위하여 HB/HT 철근의 부착강도비를 측정한 결과 50 및 70 MPa의 경우 HB/HT의 부착강도비는 1.3이하로 나타났으며, 30 MPa의 경우 HSCC 및 CC에서 각각 1.2 및 2.1로 나타났다. 따라서 HSCC 30, 50 및 70 MPa의 경우 콘크리트구조설계기준(2007) 정착길이 설계시 상부근 계수에 제시되는 수평상부철근에 대한 정착길이 보정계수를 CC의 1.3보다는 감소시켜 적용하는 것이 바람직할 것으로 판단된다.

• 한국조리학회지
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• 제10권3호
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• pp.83-96
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• 2004

According to construction of global administration environment, all over the world was ended up in infinite competition period. Because eating out company also competes with another company, it must enjoy competitive power high position to secure high position continuously, classified by formation constituent's individuation and two aspects of organic special quality by the factor. Individuation classified by formation constituent's business ability, personal relations, age factors of Information Technology, and organic special quality classifies by factor of formation culture and result that analyze eating out company's business condition competitive power reinforcement effect factor is same as following. First, was construed by company culture, personal relations, business ability period of ten days with family Restaurant, and Information Technology showed that do not influence. Competitive power reinforcement effect factor with special restaurant was construed by company culture, personal relations, business ability period of ten days, and fast food company culture and Information Technology factor with hotel restaurant company culture by competitive power reinforcement effect factor construe.

• 한국정보기술학회논문지
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• 제17권8호
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• pp.75-83
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• 2019

본 논문에서는 Median flow와 영상의 Depth 정보를 이용하여 산업 현장의 다양한 환경 조건에서 실시간 철근의 끝점 추적 및 검출이 가능한 방법을 제안한다. 영상의 Depth 정보에 Median filter, Binarization, Morphology, Blob의 알고리즘을 사용하여 2개의 철근 끝점을 검출하는 방법을 제안하였다. 실시간 철근 끝점 추적을 위해서는 Median flow의 알고리즘을 이용하여 철근의 움직임 방향과 위치 추적을 제안하였다. 그리고 Depth 영상에서 검출된 철근 끝점 좌표와 Median flow를 이용한 철근의 위치추적 좌표를 서로 비교하여 최종 위치 좌표를 결정하였다. 그 결과 기존 Median flow 방식만 적용하였을 때 75% 정도의 철근의 최종 위치 판단 성공률이 Depth의 철근 끝점 정보까지 활용하였을 때는 95%까지 추적 성공률이 높아졌다.

• 한국기계가공학회지
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• 제15권5호
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• pp.145-151
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• 2016

We consider the position and thickness of reinforcement with respect to fatigue fracture of welded bogie frames and propose an appropriate reinforcement method for many cases. The bogie frame is usually designed in accordance with JIS and KS, and operates under harsh load conditions: dynamic loads generated while driving, various loads during operation, and large load differences between loading and unloading. Consequently, fatigue failure often occurs throughout the bogie frame. We modelled the reinforcing method using ANSYS software and reviewed stress in the vicinity of common fatigue failure sites through computer simulation, optimizing the position and thickness of reinforcement.

• 한국정밀공학회지
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• 제29권1호
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• pp.79-86
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• 2012

This paper proposes PID and RIC (Robust Internal-loop Compensator) based motion controller using dual learning algorithm for position control of linear synchronous motor respectively. Its gains are auto-tuned by using two learning algorithms, reinforcement learning and neural network. The feedback controller gains are tuned by reinforcement learning, and then the feedforward controller gains are tuned by neural network. Experiments prove the validity of dual learning algorithm. The RIC controller has better performance than does the PID-feedforward controller in reducing tracking error and disturbance rejection. Neural network shows its ability to decrease tracking error and to reject disturbance in the stop range of the target position and home.

• 국제학술발표논문집
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• The 10th International Conference on Construction Engineering and Project Management
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• pp.665-671
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• 2024

This research presents a method for Augmented Reality (AR) object superimposition leveraging reinforcement learning techniques to significantly reduce manual input during the exploration of digital information on construction sites. A distinctive feature of this approach is the application of a reinforcement learning neural network, trained with pairs of real and virtual view images, for AR superimposition. This approach enables the precise adjustment of the virtual camera's position and orientation within a virtual scene, aiming to seamlessly integrate AR objects into real-world views. This research initially focuses on simpler scenarios involving 2 and 3 degrees of freedom for orientation and position adjustments. The purpose is to explore the feasibility of the application through those experiments, with the expectation that the results would be interpreted positively. These initial findings highlight the promise of the suggested method in improving AR applications, especially within the construction sector, by enabling more natural and precise merging of virtual and physical objects, without requiring user intervention.

• Computers and Concrete
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• 제18권3호
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• pp.337-354
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• 2016

To study the influence on fracture properties of reinforced concrete wedge splitting test specimens by the addition of reinforcement, and the restriction of steel bars on crack propagation, 7 groups reinforced concrete specimens of different reinforcement position and 1 group plain concrete specimens with the same size factors were designed and constructed for the tests. Based on the double-K fracture criterion and tests, fracture toughness calculation model which was suitable for reinforced concrete wedge splitting tensile specimens has been obtained. The results show that: the value of initial craking load Pini and unstable fracture load Pun decreases gradually with the distance of reinforcement away from specimens's top. Compared with plain concrete specimens, addition of steel bar can reduce the value of initial fracture toughness KIini, but significantly increase the value of the critical effective crack length ac and unstable fracture toughness KIun. For tensional concrete member, the effect of anti-cracking by reinforcement was mainly acted after cracking, the best function of preventing fracture initiation was when the steel bar was placed in the middle of the crack, and when the reinforcement was across the crack and located away from crack tip, it plays the best role in inhibiting the extension of crack.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.142-145
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• 2003

Many control applications using Neural Network need a priori information about the objective system. But it is impossible to get exact information about the objective system in real world. To solve this problem, several control methods were proposed. Reinforcement learning control using neural network is one of them. Basically reinforcement learning control doesn't need a priori information of objective system. This method uses reinforcement signal from interaction of objective system and environment and observable states of objective system as input data. But many methods take too much time to apply to real-world. So we focus on faster learning to apply reinforcement learning control to real-world. Two data types are used for reinforcement learning. One is reinforcement signal data. It has only two fixed scalar values that are assigned for each success and fail state. The other is observable state data. There are infinitive states in real-world system. So the number of observable state data is also infinitive. This requires too much learning time for applying to real-world. So we try to reduce the number of observable states by classification of states with Self-Organizing Map. We also use neural dynamic programming for controller design. An inverted pendulum on the cart system is simulated. Failure signal is used for reinforcement signal. The failure signal occurs when the pendulum angle or cart position deviate from the defined control range. The control objective is to maintain the balanced pole and centered cart. And four states that is, position and velocity of cart, angle and angular velocity of pole are used for state signal. Learning controller is composed of serial connection of Self-Organizing Map and two Multi-layer Feed-Forward Neural Networks.

• 한국지반신소재학회논문집
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• 제10권2호
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• pp.45-53
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• 2011

최근 보강토 옹벽은 점차 콘크리트옹벽을 대체하는 안정화된 공법으로 자리 잡아가고 있다. 그러나, 보강재로서 신장성보강재(Extensible reinforcement)를 사용할 경우 보강토 옹벽의 전면벽에서 배부름(Bulging) 현상이 발생할 수 있다. 보강토옹벽의 배부름(Bulging)은 임의의 블록 높이에서 그 블록의 상단 및 하단 블록이 설계상의 상대적인 위치를 확보하지 못하는 현상이다. 이는 보강재가 인장력을 발휘하기 위해서는 어느 정도 변형이 필요하기 때문에 이에 대한 설계상의 검토가 필요하다. 따라서 본 연구에서는 알루미늄 봉을 이용하는 소형모형실험을 통해서 보강재의 신장특성이 보강토 옹벽거동에 어떤 영향을 미치는지 연구하였다. 보강재는 비신장성 보강재로서 창호지와 신장성 보강재로서 멤브레인을 이용하였다. 실험결과로부터 보강재의 강성은 보강토옹벽의 변위형태에 많은 영향을 미치는 인자임을 알 수 있었으며, 전반적으로 보강재의 강성이 증가함에 따라 최대수평변위의 발생지점이 벽체 상부로 이동하는 경향을 보이고 있다.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2008년도 추계 학술발표회 제20권2호
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• pp.863-866
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• 2008

본 연구에서는 철근의 배근방향(수직, 수평) 및 위치(상부근, 하부근)를 주요 변수로 하여 이형철근과 순환굵은골재와의 부착거동을 단계별로 평가하기 위한 실험을 실시하였다. 본 연구를 통하여 얻어진 실험결과를 종합해 보면, 수평 시험체의 상부철근 시험체의 경우 하부철근 시험체 보다 부착 강도가 저하되는 것으로 나타났으며, 이는 굵은골재의 편중현상 및 상부철근 하부에서 부유물(Laitance) 발생에 따른 것으로 판단된다. 또한, 수직 시험체 및 수평철근 시험체의 부착에너지를 비교한 결과 수평 상부철근 시험체의 경우 수직 및 수평 하부철근 시험체에 비하여 부착에너지가 감소한 것으로 나타났다.