• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.5
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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.

• Journal of the Korean Geotechnical Society
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• v.39 no.5
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• pp.41-50
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• 2023

This study reviewed the liquefaction reinforcement and ground reinforcement methods widely used domestically and abroad through construction method characteristics and analyzed the economic feasibility and reinforcement efficiency of each reinforcement method. The analysis results were used to evaluate the applicability of the appropriate reinforcement method for the liquefaction reinforcement of new and existing structures. As a result of evaluating the applicability of the reinforcement method based on the economic feasibility and reinforcement effect of each reinforcement method, the compaction method, which secures the construct ability by applying large equipment, is advantageous when reinforcing a new structure, and the low-fluidity mortar injection method (C.G.S method) and the high-pressure injection method (J.S.P method) are considered appropriate in the existing structure.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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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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• 2001.10a
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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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• v.18 no.1E
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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.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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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.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.1
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• pp.48-58
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• 2014

In this study, quasi-static according to the displacement-controlled (strain control) method tests on RC columns for seismic reinforcement performance in accordance with the provisions of the seismic design and construction before 1992 design code for highway bridges in korea. Used reinforcement that improves the performance of Inorganic Helical Bar, a kind of alloy steel, circular columns were tested outside the seismic reinforcing. In the experiment, fracture behavior, lateral load-displacement relation, ductility and energy assessment evaluation was performed through tests. The variables in experimental are section force of reinforcement, spiral reinforcement spacing, reinforcement method. Improved seismic performance and effect were confirmed through quasi-static test experiments. The results of study confirmed determination the appropriate size of reinforcement, reinforcement forces, spacing and selection of the type required, furthermore, not only mechanical reinforcement but also substitution of high-strength concrete reinforced with concrete cover improved seismic performance.

• Geomechanics and Engineering
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• v.28 no.2
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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.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.8
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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.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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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.