• Proceedings of the Korea Concrete Institute Conference
• /
• 1998.10b
• /
• pp.643-648
• /
• 1998

Despite many advantages of FRP materials, such as corrosion resistance, their linear elastic behavior up to rupture is likely to result in a lack of ductility. This paper discusses ductility improvement methods for prestressed concrete beams using FRP tendons. The methods were evaluated thorough extensive analytical and experimental investigations. The methods include optimization of sectional ductility through proper reinforcement, concrete confinement, concrete reinforcement with fibers, and prestressing with unbonded tendons.

• Journal of Korean Association for Spatial Structures
• /
• v.17 no.1
• /
• pp.59-67
• /
• 2017

In this study, load transfer tests based on KCI-PS101 were conducted to verify the performance of spiral anchorage zone reinforcement for banded post-tensioning (PT) monostrands. With results, the compressive strength of spiral reinforcement was increased by about 20% than that of specimens with two horizontal steel bars and 8% than that of U-shaped bars. Advanced spiral reinforcement for corner increases compressive strength and can resist the spalling forces or fall-out effect at the corner by shear. The ratio of maximum load to amount of steel of the spiral reinforcement is about twice than that of U-shaped reinforcement. With increase of compressive strength capacity and improvement of constructability, the spiral reinforcement is considered to have advantages of promoting the performance of PT anchorage zone compared to conventional methods.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.5
• /
• pp.1303-1311
• /
• 1999

In order to learn in dynamic environments, reinforcement learning algorithms like Q-learning, TD(0)-learning, TD(λ)-learning have been proposed. however, most of them have a drawback of very slow learning because the reinforcement value is given when they reach their goal state. In this thesis, we have proposed a reinforcement learning method that can approximate fast to the goal state in maze environments. The proposed reinforcement learning method is separated into global learning and local learning, and then it executes learning. Global learning is a learning that uses the replacing eligibility trace method to search the goal state. In local learning, it propagates the goal state value that has been searched through global learning to neighboring sates, and then searches goal state in neighboring states. we can show through experiments that the reinforcement learning method proposed in this thesis can find out an optimal solution faster than other reinforcement learning methods like Q-learning, TD(o)learning and TD(λ)-learning.

• Proceedings of the Korea Concrete Institute Conference
• /
• 1999.10a
• /
• pp.689-692
• /
• 1999

In recent years, FRP plates have been studied for flexural reinforcement of RC structures due to easy installation and good quality control. This study presents experimental results for the effectiveness of flexural reinforcement of the RC beams using thin CFRP and GFRP stripe made by the pultrusion process. For the selected FRP strips of various thicknesses and widths, it was demonstrated that both flexural strength and ductility were considerably increased with relatively easy installation when compared to the other methods used for the composite reinforcement.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2000.10a
• /
• pp.828-835
• /
• 2000

In recent years, RC structures need reinforcement due to physical and chemical deterioration, reduction of serviceability and structural capacity. For reinforcement of RC structures, steel plate attachment, area increase and composite fiber sheet attachment methods are used, but there are some problems like weight increase, workability, quality control and fire resistance capacity. This study presents the effectiveness of flexural reinforcement of RC beams using composite rods that are inserted in high strength special purposed polymer mortar.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.10a
• /
• pp.230-237
• /
• 2000

Tubular joints of jacket structures are usually reinforced using thicker can section, internally ring stiffeners, diaphragm, or externally gusset plates to increase load carry capacity. In this paper, the effect of reinforcement type and geometric parameters of stiffener on the ultimate strength of tubular X-joints subjected to brace compression have been studied numerically Three reinforcement methods were considered; (1)can reinforcement (2)internally ring stiffener (3)internally longitudinal diaphragm. The ANSYS software was used nonlinear strength analysis. It was found that there is significant strength enhancement for reinforced joints.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2005.03a
• /
• pp.870-877
• /
• 2005

This study examined a case of collapse and reinforcement of the colluvial deposit slope in Kyeongnam Geoje Area. The reason for the collapse was found first in the reduction of the resistant force due to slope-cut for constructing retaining walls. This decreased the resistant force against sliding, which enabled precipitation during the rainy period to seep into the ground in the upper colluvium, resulting in increase in porewater pressure. This leads to decreased shear strength and increased sliding force, which ultimately caused the collapse of the slope. For the long-term stability, methods attained for stability reinforcement are summarized in the following table.

• The Journal of Korea Robotics Society
• /
• v.18 no.3
• /
• pp.352-357
• /
• 2023

Since robotic assembly in an unstructured environment is very difficult with existing control methods, studies using artificial intelligence such as reinforcement learning have been conducted. However, since long-time operation of a robot for learning in the real environment adversely affects the robot, so a method to shorten the learning time is needed. To this end, a method based on a pre-trained neural network was proposed in this study. This method showed a learning speed about 3 times than the existing methods, and the stability of reward during learning was also increased. Furthermore, it can generate a more optimal policy than not using a pre-trained neural network. Using the proposed reinforcement learning-based assembly trajectory generator, 100 attempts were made to assemble the power connector within a random error of 4.53 mm in width and 3.13 mm in length, resulting in 100 successes.

• The Journal of Korea Robotics Society
• /
• v.1 no.2
• /
• pp.142-150
• /
• 2006

This study examines whether the reinforcement theory would be effectively applied to teaching assistant robots between a robot and a student in the same way as it is applied to teaching methods between a teacher and a student. Participants interact with a teaching assistant robot in a 3 (types of robots: positive reinforcement vs. negative reinforcement vs. both reinforcements) by 2 (types of participants: honor students vs. backward students), within-subject experiment. Three different types of robots, such as 'Ching-chan-ee' which gives 'positive reinforcement', 'Um-bul-ee' which gives 'negative reinforcement', and 'Sang-bul-ee' which gives both 'positive and negative reinforcement' are designed based on the reinforcement theory and the token reinforcement system. Participants' task performance and reaction rate are measured according to the types of robots and the types of participants. In task performance, the negative reinforcement robot is more effective than the other two types, but regarding the number of stimulus, the less the stimulus is, the more effective the task performance is. Also, participants showed the highest reaction rate on the negative reinforcement robot which implies that the negative reinforcement robot is most effective to motivate students. The findings demonstrate that the participants perceive the teaching assistant robot not as a toy but as a teaching assistant and the reinforcement interaction is important and effective for teaching assistant robots to motivate students. The results of this study can be implicated as an effective guideline to interaction design of teaching assistant robots.

• Computers and Concrete
• /
• v.12 no.2
• /
• pp.131-149
• /
• 2013

Various types of reinforcement splicing methods have been developed and implemented in reinforced concrete construction projects for achieving the continuity of reinforcements. Due to the complicated reinforcement arrangements and the difficulties in securing bar spacing, the traditional lap splicing method, which has been widely used in reinforced concrete constructions, often shows low constructability and difficulties in quality control. Also, lap spliced regions are likely to be over-reinforced, which may not be desirable in seismic design. On the other hand, mechanical splicing methods can offer simple and clear arrangements of reinforcement. In order to utilize the couplers for the ribbed-deformed bars, however, additional screw processing at the ends of reinforcing bars is typically required, which often lead to performance degradations of reinforced concrete members due to the lack of workmanship in screw processing or in adjusting the length of reinforcing bars. On the contrary, the use of screw-ribbed reinforcements can easily solve these issues on the mechanical splicing methods, because it does not require the screw process on the bar. In this study, the mechanical coupler suitable for the screw-ribbed reinforcements has been developed, in which any gap between the reinforcements and sleeve device can be removed by grouting high-flow inorganic mortar. This study presents the uniaxial tension tests on the screw-ribbed reinforcement with the mechanical sleeve devices and the cyclic loading tests on RC columns with the developed coupler. The test results show that the mechanical sleeve connection developed in this study has an excellent splicing performance, and that it is applicable to reinforced concrete columns with a proper confinement by hoop reinforcement.