• 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.

• 한국지반공학회논문집
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• 제39권5호
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• pp.41-50
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• 2023

본 연구에서는 국내외에서 널리 사용되고 있는 액상화 보강 및 지반 보강 공법들에 대해 공법 특성별로 검토하고, 각 보강방안의 경제성 및 보강효과를 분석하였다. 또한 분석 결과를 바탕으로 신설구조물 및 기존구조물의 액상화 보강시 적절한 보강 방안 적용성 평가를 수행하였다. 보강방안 별 경제성, 보강효과를 바탕으로 보강 방안의 적용성을 평가한 결과, 신설 구조물의 보강시에는 대형장비를 적용하여 시공성이 확보되는 다짐계열 공법이 유리하며, 기존 구조물에서는 저유동성 몰탈 주입공법(C.G.S공법) 및 고압분사공법(J.S.P공법)의 적용이 적절할 것으로 판단된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1072-1075
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• 2005

This paper presents that TD method is applied to the human adaptive devices for smart home with context awareness (or recognition) technique. For smart home, the very important problem is how the appliances (or devices) can adapt to user. Since there are many humans to manage home appliances (or devices), managing the appliances automatically is difficult. Moreover, making the users be satisfied by the automatically managed devices is much more difficult. In order to do so, we can use several methods, fuzzy controller, neural network, reinforcement learning, etc. Though the some methods could be used, in this case (in dynamic environment), reinforcement learning is appropriate. Among some reinforcement learning methods, we select the Temporal Difference learning method as a core algorithm for adapting the devices to user. Since this paper assumes the environment is a smart home, we simply explained about the context awareness. Also, we treated with the TD method briefly and implement an example by VC++. Thereafter, we dealt with how the devices can be applied to this problem.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.96.3-96
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• 2001

In this paper the self-organized and fuzzy inference used stochastic gradient ascent method is proposed. Fuzzy rule and fuzzy set increase as occasion demands autonomously according to the observation information. And two rules(or two fuzzy sets)becoming to be similar each other as progress of learning are unified. This unification causes the reduction of a number of parameters and learning time. Using fuzzy inference and making a rule with an appropriate state division, our proposed method makes it possible to construct a robust reinforcement learning system.

• International Journal of Concrete Structures and Materials
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• 제18권1E호
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• pp.49-54
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• 2006

Confinement is major contribution to bond strength between reinforcement steel bars and concrete. Cover thickness, bar spacing and transverse reinforcement are the key confinement factors of current provisions for the development and splices of reinforcement. However, current provisions are still too complicated to determine the values of the confinement, which need to be well delineated in the process of design. In this study, an experimental work using beam-end and splice specimens was performed to examine the effect of concrete cover on bond strength. The results of this experiment and previously available data are analyzed to identify the effects of confinement on bond strength. From this reevaluation, new provisions for the development and splices of reinforcement are proposed. The provisions suggest some limitations in the confinement index. The new provisions will allow the engineers to use a simple and yet satisfactory and appropriate method or a precise approach for design to determine the values of confinement on the calculation of development and splice lengths.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.303-314
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• 2010

This study, as basic research which was intended to develope the surface reinforcement method using reinforcement material which is applicable to very soft ground in Korea, was aimed at proposing the design parameter for the surface ground improvement method. To that end, a wide width tensile test using geotextile, geogrid and steel bar (substitute for bamboo) and 49 kinds of the laboratory model tests were conducted. And the result the study suggested $\beta_s$, the stiffness coefficient to evaluate the stiffness effect of reinforcement materials. Then, it was also found that the stiffness coefficient, $\beta_s$ as the testing constant would be appropriate as high as 1.0, 1.1 and 1.5 for geotextile, geogrid and steel bar, respectively. And It was evaluated that the stiffness effect affecting reinforcement improvement effect would be reduced as the thickness of embeded depth increases and that RFe, the stiffness effect reduction coefficient would have positive correlation with H/B. Finally, it was confirmed that the bearing capacity gained from the method to calculate bearing capacity, which was suggested in the study, would almost correctly estimate the capacity, demonstrating the appropriateness of the proposed bearing capacity calculation method.

• 한국구조물진단유지관리공학회 논문집
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• 제18권1호
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• pp.48-58
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• 2014

본 연구에서는 1992년 도로교설계기준의 내진설계도입 이전 규정에 따라 설계, 시공된 교각의 축소 모델을 실험체로 제작하여 원형기둥의 변위비에 따른 횡하중을 변위제어 방식으로 입력하여 준정적 방법을 통해 실험을 실시하였다. 연구에 적용한 보강재는 성능을 향상시킨 무기계 합금강인 Helical Bar로써 원형기둥 외부에 보강 후 실내실험을 통하여 파괴거동, 하중-변위 관계, 연성도 평가 및 에너지 평가를 실시하였다. 실험변수로는 위험단면 내에서 나선으로 보강한 보강재의 단면력의 크기와 나선보강의 간격, 보강형태로 두었으며, 준정적 실험을 통해 보강성능의 차이와 효과를 확인하였다. 실험결과 보강대상 부재의 성능에 따라 적절한 보강재의 단면력 크기결정과 보강간격 및 형식의 선정이 필요하며 기계적 보강재뿐만 아니라 고강도 콘크리트 피복으로의 치환으로도 보강성능이 향상됨을 확인할 수 있었다.

• Geomechanics and Engineering
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• 제28권2호
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• pp.145-155
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• 2022

Safety is a most important parameters in underground railway transportation; Also stability of underground tunnel is very important in tunneling engineering. Design of a reliable support system requires an evaluation of both ground demand and support capacity. Iran's traditional railway tunnels are mainly supported with masonry structures or unsupported in high quality rock masses. A decrease in rock mass quality due to changes in groundwater regime creep and fatigue in rock and similar phenomena causes tunnel safety to decrease during time. The case study is an old tunnel in Iran, called "Keshvar"; it is more than 50 years old railway organization. In operating this Tunnel, until the several problems came up based on stability and leaking water. The goal of study is evaluation of the various reinforcement systems for supporting of the tunnel. The optimal selection of the reinforcement system is examined using TOPSIS Fuzzy method in light of the looming and available uncertainties. Several factors such as; the tunnel span, maintenance, drainage, sealing, ventilation, cost and safety were based to choose the method and system of designing. Therefore, by identifying these parameters, an optimal reinforcement system was selected and introduced. Based on optimization system for analysis, it is revealed that the systematic rock bolts and shotcrete protection had a most appropriate result for these kind of tunnel in Iran.

• 대한건축학회논문집:구조계
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• 제35권8호
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• pp.123-130
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• 2019

Recently, it is required to develop a monitoring technology that combines an FBG sensor as a means for continuously monitoring whether reinforcing effect of FRP is maintained on FRP reinforced structural members. However, most existing researches focus on the insertion of FBG sensors into bar-shaped FRPs, and there is insufficient study on the details strip-type FRPs combined with FBG sensors. Therefore, in this paper, it is studied to develop a reinforcement in which a FBG sensor is combined with a FRP strip. Especially, combination of FRP and FBG sensor. For this, a series of experiments were performed to find the adhesive strength of fiber-FRP-epoxy joints, the tensile strength of FBG sensor part with reflection-lattice, and the performance depending on the connection method of FRF and FBG sensor. As a result of the study, it was found that a minimum strength of $216.15N/mm^2$ is required for incorporating FBG sensors in FRP using epoxy. It is considered that the adhesion length of epoxy joints should be more than 50mm. When the FBG sensor is attached to the FRP strip as an epoxy, it is considered appropriate to use the complete attachment and the sensor non-attachment method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.166-169
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• 2003

Reinforcement learning if a kind of machine learning. It aims to adapt an agent to a given environment with a clue to a reward and a penalty. Q-learning [8] that is a representative reinforcement learning system treats a reward and a penalty at the same time. There is a problem how to decide an appropriate reward and penalty values. We know the Penalty Avoiding Rational Policy Making algorithm (PARP) [4] and the Penalty Avoiding Profit Sharing (PAPS) [2] as reinforcement learning systems to treat a reward and a penalty independently. though PAPS is a descendant algorithm of PARP, both PARP and PAPS tend to learn a local optimal policy. To overcome it, ion this paper, we propose the Multi Best method (MB) that is PAPS with the multi-start method[5]. MB selects the best policy in several policies that are learned by PAPS agents. By applying PS, PAPS and MB to a soccer game environment based on the SoccerBots[9], we show that MB is the best solution for the soccer game environment.