• Proceedings of the Korea Concrete Institute Conference
• /
• 1998.04a
• /
• pp.243-248
• /
• 1998

This study was initiated to develop a precast polymer concrete production method and to describe an criterion for the optimum thickness of precast polymer concrete by a series of experiment and structural analysis. Nine specimens with different thickness and steel bar reinforcement were prepared and tested and analyzed with respect to structural behaviors. Cracking moment was mostly affected by the thickness but steel reinforcement seemed not to have effect on the moment. Data of the study could be widely applied in designing and planning of production processes of many polymer concrete products of which all or some of components are composed with thin panels.

• International Journal of Railway
• /
• v.6 no.2
• /
• pp.59-63
• /
• 2013

The purpose of this paper was to evaluate the effectiveness of geogrid for conventional ballasted track and asphalt concrete underlayment track using PLAXIS finite element program. Geogrid element was modeled at various locations that include subballast/subgrade, subballast/ballast interfaces, middle of the ballast, and one-third depth of the ballast. The results revealed that the effectiveness of geogrid reinforcement appeared to be larger for ballasted track structure compared to asphalt concrete underlayment track. Particularly, in case of installing geogrid at one-third depth of ballast layer in a conventional ballasted track, the most effectiveness of geogrid reinforcement was achieved. The influence of geogrid axial stiffness on track substructure response was not clear to conclude. Further validations using a discrete element method along with experimental investigation are considered as a future study. The effect of asphalt concrete layer modulus was evaluated. The results exhibited that higher layer modulus seems to be effective in controlling displacement and strain of track substructure. However it also yields slightly higher stresses within track substructure. It infers that further validations are required to come up with optimum asphalt concrete mixture design to meet economical and functional criteria.

• Proceedings of the KIEE Conference
• /
• 1998.07g
• /
• pp.2189-2192
• /
• 1998

The objective of this paper is, based upon the principles of artificial life, to induce emergent behaviors of multiple autonomous mobile robots which form from simple local rules to complex global intelligence. Here, we propose an architecture of neural network learing with reinforcement signals which perceives the neighborhood information and decides the direction and the velocity of movement as mobile robots navigates in a group. As results of the simulations, the optimum weights are obtained in real time, which not only prevent from the collisions between agents and obstacles in the dynamic environment, but also have the mobile robots move and keep in various patterns.

• Structural Engineering and Mechanics
• /
• v.55 no.1
• /
• pp.137-160
• /
• 2015

The one-way (two-way) flexural strength of RCC prisms (circular slabs) reinforced with glass fiber textiles is addressed. To this end, alkaline-resistant glass fiber textiles with three surface weights were used in the composite, the matrix concrete was designed with zero/nonzero slump, and the textiles were used with/without an intermediate layer provided by epoxy resin and sand mortar. Prisms were tested under a four-point loading apparatus and circular slabs were placed on simple supports under a central load. Effects of the amount and geometry of reinforcement, matrix workability, and the intermediate layer on the ultimate load and deflection were investigated. Results revealed that, with a specific reinforcement amount, there is an optimum textile tex for each case, depending on the matrix mix design and the presence of intermediate layer. Similar results were obtained in one-way and two-way bending tests.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.16 no.11
• /
• pp.1068-1076
• /
• 2004

Technology on the proportional integral (PI) control have grown rapidly owing to the needs for the robust capacity of the controllers from industrial building sectors. However, PI controller requires tuning of gains for optimal control when the outside weather condition changes. The present study presents the possibility of reinforcement learning (RL) control algorithm with PI controller adapted in the HVAC system. The optimal design criteria of RL controller was proposed in the Environment Chamber experiment and a theoretical analysis was also conducted using TRNSYS program.

• KIEAE Journal
• /
• v.2 no.1
• /
• pp.41-48
• /
• 2002

This study aims to investigate and evaluate the room acoustic designs of a multi purpose gymnasiums which do not use adjustable treatments in order to change the acoustical characteristics. Considering the main uses of gymnasium and auditorium, experiments were carried out using both nondirectional speakers on the stage and loudspeaker installed on the ceiling. The result from the study are as follows; Measured RT under unoccupied condition was a little longer than the expected value, therefore, in the case of occupied condition RT would be close to the optimum value. However, parameters that evaluate intelligibility and speech transmission property appeared to be low and have large differences depending on the measuring points, therefore, more effective sound reflecting surfaces and sound reinforcement systems should be considered.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.46 no.5
• /
• pp.69-77
• /
• 2004

FRP rebar has low bond performance than steel rebar. Usually, FRP rebar has about 60% of bond strength of steel rebar. Without adequate bond to concrete, the full composite action between reinforcement and concrete matrix can not be achieved. Therefore, FRP rebars must also have surface deformations that provide good bond to concrete. The purpose of this research was decided an optimum surface deformation patterns through bond test of FRP rebar. Eighteen surface deformation patterns of FRP rebar with widely different geometries were investigated. Based on the test results, we established optimum surfale deformation pattern. Bond tests were performed for three types of surface deformation patterns of FRP rebar including sand coated rebar, ribbed rebar, and wrapped and sand coated rebar that commercially available, and two types of FRP rebar including CFRP, GFRP rebars that optimum surface deformation pattern is applied. According to bond test results, FRP rebars that optimum surface deformation pattern is applied were found to have better bond strength with concrete than currently using FRP rebar.

• Structural Engineering and Mechanics
• /
• v.54 no.6
• /
• pp.1097-1109
• /
• 2015

A novel optimization approach for reinforced concrete (RC) biaxially loaded columns is proposed. Since there are several design constraints and influences, a new computation methodology using iterative analyses for several stages is proposed. In the proposed methodology random iterations are combined with music inspired metaheuristic algorithm called harmony search by modifying the classical rules of the employed algorithm for the problem. Differently from previous approaches, a detailed and practical optimum reinforcement design is done in addition to optimization of dimensions. The main objective of the optimization is the total material cost and the optimization is important for RC members since steel and concrete are very different materials in cost and properties. The methodology was applied for 12 cases of flexural moment combinations. Also, the optimum results are found by using 3 different axial forces for all cases. According to the results, the proposed method is effective to find a detailed optimum result with different number of bars and various sizes which can be only found by 2000 trial of an engineer. Thus, the cost economy is provided by using optimum bars with different sizes.

• Computers and Concrete
• /
• v.13 no.4
• /
• pp.547-567
• /
• 2014

Precast Seismic Structural Systems (PRESSS) provided an iterative procedure for obtaining optimum design of unbonded post-tensioned coupled precast concrete wall systems. Although PRESSS procedure is effective, however, it is lengthy and laborious. The purpose of this research is to employ Artificial Neural Network (ANN) to predict the optimum design parameters for such wall systems while avoiding the demanding iterative process. The developed ANN model is very accurate in predicting the nondimensional optimum design parameters related to post-tensioning reinforcement area, yield force of shear connectors and ratio of moment resisted by shear connectors to the design moment. The Mean Absolute Percent Error (MAPE) for the test data for these design parameters is around %1 and the correlation coefficient is almost equal to 1.0. The developed ANN model is then used to study the effect of different design parameters on wall behavior. It is observed that the design moment and the concrete strength have the most influence on the wall behavior as compared to other parameters. Several design examples were presented to demonstrate the accuracy and effectiveness of the ANN model.

• International Journal of Highway Engineering
• /
• v.3 no.1 s.7
• /
• pp.151-163
• /
• 2001

Very few studies have been attempted to understand the stress-strain behavior of flexible pavements reinforced with geosynthetics in the middle of asphalt layer. In this study, the flexible asphalt layer was analyzed with finite element method to understand stress-strain behavior. The asphalt layer was reinforced with glass grid and geogrid. The reinforcement was applied in the asphalt layer to prevent its excessive deformation and shear failure. The location of installation and stiffness of the geosynthetics were varied to obtain optimum depth of reinforcement and proper modulus. The results indicate that geosynthetics are more effective for reducing maximum shear stress than those of vertical stress and vertical displacement. Maximum shear stress decreased 15$\sim$20%, and glass grid with high value of modulus was the most effective. Also, in order to prevent failure of asphalt layer, reinforcement should be installed in the 3cm$\sim$5cm depth.