• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.6
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• pp.18-25
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• 2012

This paper estimates the ductility of reinforced concrete columns according to configurations of transverse reinforcement. A total of 8 reinforced concrete columns were cast and tested in flexure. The test variables in this study were the configurations, yield strength, and amount of transverse reinforcement. The specimens had a cross-section of $250{\times}250mm$ and had a shear span-to-depth ratio of 4.1 to induce flexural failure. In the test, cyclic lateral load was applied to the specimens with a constant axial load. The experimental result indicated that the specimens with proposed configurations of transverse reinforcement showed higher ductility and energy dissipation capacity than the specimens with rectangular tie.

• Advances in concrete construction
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• v.14 no.2
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• pp.79-92
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• 2022

The amount and configuration of transverse reinforcement are known as critical parameters that significantly affect the lateral confinement of concrete, the ductility capacity, and the plastic hinge length of RC columns. Based on test results, this study investigated the effect of the three variables on structural indexes such as neutral axis depth, lateral expansion of concrete, and ductility capacity. Five reinforced concrete column specimens were tested under cyclic flexure and shear while simultaneously subjected to a constant axial load. The columns were reinforced by two types of reinforcing steel: rectangular hoops and spiral type reinforcing bars. The variables in the test program were the shape, diameter, and yield strength of transverse reinforcement. The interactive influence of the amount of transverse reinforcement on the structural indexes was evaluated. Test results showed that when amounts of transverse reinforcement were similar, and yield strength of transverse reinforcement was 600 MPa or less, the neutral axis depth of a column with spiral type reinforcing bars was reduced by 28% compared with that of a column reinforced by existing rectangular hoops at peak strength. While the diagonal elements of spiral-type reinforcing bars significantly contributed to the lateral confinement of concrete, the strain of diagonal elements decreased with increases of their yield strength. It was confirmed that shapes of transverse reinforcement significantly affected the lateral confinement of concrete adjacent to plastic hinges. Transverse reinforcement with a yield strength exceeding 600 MPa, however, increased the neutral axis depth of normal-strength concrete columns at peak strength, resulting in reductions in ductility and energy dissipation capacity.

• Advances in nano research
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• v.17 no.3
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• pp.257-274
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• 2024

This work aims to study and analyse the dynamic size dependent behvior of functionally graded carbon nanotubes (FGCNTs) nanoplates embedded in elastic media and subjected to moving point load. The non-classical effect is incorporated into the governing equations using the nonlocal strain gradient theory (NSGT). Four different reinforcement configurations of the carbon nanotubes (CNTs) are considered to show the effect of reinforcement configuration on the dynamic behvior of the FGCNTs nanoplates. The material characteristics of the functionally graded materials are assumed to be continuously distributed throughout the thickness direction according to the power law. The Hamiltonian principle is exploited to derive the dynamic governing equations of motion and the associated boundary conditions in the framework of the first order shear deformation plate theory. The Navier analytical approach is adopted to solve the governing equations of motion. The obtained solution is checked by comparing the obtained results with the available results in the literature and the comparison shows good agreement. Numerical results are obtained and discussed. Obtained results showed the significant impact of the elastic foundation parameters, the non-classical material parameters, the CNT configurations, and the volume fractions on the free and forced vibration behaviors of the FGCNT nanoplate embedded in two parameters elastic foundation and subjected to moving load.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.830-833
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• 2002

To solve the internal security problem such as human error and bad faith, the automation of computer system management is significant. For this purpose, we focus attention in the automation of Mail Delivery Service. Today, requirement for reliable mail delivery system becomes larger and larger. However, existing systems are too strict about their configuration. Hence, we propose the method based on Reinforcement Learning (RL) to achieve proper MX record ordering. A measure on validity of the design of system, such as network topology number of servers and so on, is also obtained as side benefit. In order to verify the usability of the presented method, we did on a small model of mail delivery system. As a result, we show that RL is available for determination of the proper MX record ordering. Additionally, we suggest that it is also available for comparing validity of setting of MTA and the network design.

• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.13-23
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• 2021

In this paper, we proposed a framework that generates the trajectory of a single rigid body based on its COM configuration and contact pose. Because we use a smaller input dimension than when we use a full body state, we can improve the learning time for reinforcement learning. Even with a 68% reduction in learning time (approximately two hours), the character trained by our network is more robust to external perturbations tolerating an external force of 1500 N which is about 7.5 times larger than the maximum magnitude from a previous approach. For this framework, we use centroidal dynamics to calculate the next configuration of the COM, and use reinforcement learning for obtaining a policy that gives us parameters for controlling the contact positions and forces.

• Journal of the Korea Concrete Institute
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• v.21 no.3
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• pp.311-318
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• 2009

An experimental investigation was conducted to examine the hysteretic behaviors of ultra-high strength concrete tied columns. The purpose of this study is to propose the volumetric ratio of transverse reinforcement for ultra-high strength concrete tied columns with 100 MPa compressive strength. Nineteen 1/3 scaled columns were fabricated to simulate an 1/2 story of actual structural members with the main variables of axial load ratio, configurations and volumetric ratios of transverse reinforcement. The results show that the deformability of columns are affected by the configurations and volumetric ratios of transverse reinforcement. Especially, it has been found that the behavior of columns are affected by axial load ratio rather than the amounts and the configurations of transverse reinforcement. To improve the ductility behavior of RC column using ultra high strength concrete in a seismic region, We suggested the amount of transverse reinforcement for all data that satisfy the required displacement ductility ratio over 4. It is means that the lateral confining reduction factor (${\lambda}^c$) considering the effective legs, configuration and spacing of transverse reinforcement and axial load ratio was reflected for the volumetric ratio of transverse reinforcement.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• International Journal of Concrete Structures and Materials
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• v.18 no.2E
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• pp.79-87
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• 2006

The main objective of this research is to examine the behavior of high-strength concrete(HSC) columns. Eight test columns in one-third scale were tested under the conditions of cyclic lateral force and a constant axial load equal to 30% of the column axial load capacity. The $200{\times}200mm$ square columns were reinforced with eight DB bars constituting a longitudinal steel ratio of 2.54% of the column cross-sectional area. The main experimental parameters were volumetric ratio of transverse reinforcement(${\rho}_s$=1.58, 2.25 percent), tie configuration(Type H, Type C, Type D) and tie yield strength($f_{yh}$=548.8 and 779.1 MPa). It was found that the hysteretic behaviour and ultimate deformability of HSC columns were influenced by the amount and details of transverse reinforcement in the potential plastic hinge regions. Columns of transverse reinforcement in the amount 42 percent higher than that required by seismic provisions of ACI 318-02 showed ductile behavior. At 30% of the axial load capacity, it is recommended that the yield strength of transverse reinforcement be held equal to or below 548.8 MPa. Correlations between the calculated damage index and the damage progress are proposed.

• Architectural research
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• v.7 no.1
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• pp.39-48
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• 2005

Main objective of this research is to evaluate performance of high-strength concrete (HSC) columns for ductility and strength. Eight one-third scale columns with compressive strength of 69 MPa were subjected to a constant axial load corresponding to 30 % of the column axial load capacity and a cyclic horizontal load-inducing reversed bending moment. The variables studied in this research are the volumetric ratio of transverse reinforcement (${\rho}_s=1.58$, 2.25 %), tie configuration (Type H, Type C and Type D) and tie yield strength ($f_{yh}=549$ and 779 MPa). Test results show that the flexural strength of every column exceeds the calculated flexural capacity based on the equivalent concrete stress block used in the current design code. Columns with 42 % higher amounts of transverse reinforcement than that required by seismic provisions of ACI 318-02 showed ductile behaviour, showing a displacement ductility factor (${\mu}_{{\Delta}u}$) of 3.69 to 4.85, and a curvature ductility factor (${\mu}_{{\varphi}u}$) of over 10.0. With an axial load of 30 % of the axial load capacity, it is recommended that the yield strength of transverse reinforcement be held equal to or below 549 MPa.

• Architectural research
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• v.26 no.1
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• pp.1-12
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• 2024

This study introduces a deep reinforcement learning (DRL)-based methodology for optimizing apartment space arrangements, addressing the limitations of human capability in evaluating all potential spatial configurations. Leveraging computational power, the methodology facilitates the autonomous exploration and evaluation of innovative layout options, considering architectural principles, legal standards, and client re-quirements. Through comprehensive simulation tests across various apartment types, the research demonstrates the DRL approach's effec-tiveness in generating efficient spatial arrangements that align with current design trends and meet predefined performance objectives. The comparative analysis of AI-generated layouts with those designed by professionals validates the methodology's applicability and potential in enhancing architectural design practices by offering novel, optimized spatial configuration solutions.