• Journal of Korean Association for Spatial Structures
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• v.16 no.4
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• pp.45-52
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• 2016

The single layer latticed domes have attracted many designers and researchers's attention all of the world, because these structures as spatial structure are of great advantage in not only mechanical rationality but also function, fabrication, construction and economic aspect. But single layer latticed domes are apt to occur the unstable phenomena that are called "buckling" because of the lack of strength of members, instability of structural shape, etc. In the case of latticed dome, there are several types of buckling mode such as overall buckling, local buckling, and member buckling according to the shape of dome, section type of member, the size of member, junction's condition of member and so on. There are many methods to increase the buckling strength of the single layer latticed dome, that is, with the change of geometrical shape of dome, the reinforcement of buckled member, etc. Therefore, the purpose of this study is to verify the reinforcement effect of buckled member when designers reinforce the buckled member to increase the buckling strength of single layer latticed dome with 3-way grid.

• Geomechanics and Engineering
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• v.5 no.3
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• pp.187-194
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• 2013

The most soil anchor works have been concerned with the uplift problem on embedded in non-reinforced soils under pullout test. Symmetrical anchor plates are a foundation system that can be resisting tensile load with the support of around soil in which symmetrical anchor plate is embedded. Engineers and authors proved that the uplift response can be improved by grouping the symmetrical anchor plates, increasing the unit weight, embedment ratio and the size of symmetrical anchor plates. Innovation of geosynthetics in the field of geotechnical engineering as reinforcement materials found to be possible solution in symmetrical anchor plate responses. Unfortunately the importance of reinforcement in submergence has received very little attention by researchers. In this paper, provision of tensile reinforcement under embedded conditions has been studied through uplift experiments on symmetrical anchor plates by few researchers. From the test results it has been showed that the provision of geogrid reinforcement system enhances the uplift response substantially under uplift test although other results are such as increase the ultimate uplift response of symmetrical anchor plate embedded using geosynthetic and Grid Fixed Reinforced (GFR) and symmetrical anchor plate improvement is very dependent on geosynthetic layer length and increases significantly until the amount of beyond that further increase in the layer length does not show a significant contribution in the anchor response.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.72-79
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• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• The Journal of Korean Academy of Prosthodontics
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• v.32 no.3
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• pp.411-430
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• 1994

The denture may be fractured accidentally by an impact while outside the mouth, or may be cracked or broken while in service in the mouth. The latter is generally a fatigue failure caused by repeated flexure over a period of time. This investigation compared the flexural fatigue resistance, the impact force and the transverse strength of two denture base materials with and without the grid strengthener, the T300, the T800 and the Kevlar fiber to evaluate the fracture resistance. The distribution and behavior of fibers across fracture lines were examined by Hi-Scope Compact Microvision System. Through analyses of the data from this study, the following conclusions were obtained. 1. The flexural fatigue resistance, impact strength and transverse strength of high impact strength resin were higher than those of conventional heat polymerizing resin, but statistically there was no significant difference(p>0.05). 2. All specimens with and without the grid strengthener did not show significant differences in the flexural fatigue, the impact and the transverse strength test(p>0.05). 3. All specimens reinforced with the T300, the T800 and the Kevlar fiber showed significant increase of the fatigue resistance and the impact force(p<0.05). 4. All specimens reinforced with the T800 and the Kevlar fiber showed significant increase of the transverse strength(p<0.05). 5. All specimens reinforced with the T300, the T800 and the Kevlar fiber exhibited greenstick fractures. The fibers tended to remain enveloped in the resin, resisting pull-out.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.79-82
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• 2006

This paper presents to examine the ability of an electrical resistivity method to monitor the grouting effect at subsidence area. To monitor the changes in ground resistivity before and during the grout, series of electrical resistivity monitoring surveys have been conducted. Data has acquired in the form of grid making nine lines parallel to road and four lines traverse the road. Two kinds of electrode arrays modify pole-pole and dipole-dipole arrays were used during resistivity data acquisition. In this paper, the results show that electrical prospecting is an effective method to detect low resistivity imaging zone by grout during the ground reinforcement.

• Journal of the Korea institute for structural maintenance and inspection
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• v.3 no.2
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• pp.155-160
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• 1999

Recently, the study on mix design of lightweight concrete using the polystyrene foam balls is put into practice from the viewpoint to grade up the quality of concrete and recyclable usage of industrial by products. Polystyrene aggregate concrete, PAC, can be used as structural concrete in low strength application. For instance, PAC could be used in the middle part of sandwich panel where stresses are generally low and in the case of grid-type reinforcement where it does not need high bond strength but little compressive strength to resist the pressure of transverse reinforcement. From this point of view, the authors discussed the influence of fluidity and compressive strength of concrete by the difference of the volume percentage of polystyrene foam balls and water cement ratio.

• Geotechnical Engineering
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• v.12 no.6
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• pp.21-36
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• 1996

The stress transfer mechanism between soil and grid reinforcements involves two basic mechanism : frictional soil resistance and passive soil resistance. However the mechanism of the passive soil resistance is very complex to understand. To study the failure mechanism of ribbed reinforcement, the direct shear tests which are dominated by passive soil resistance are analyzed by using the finite element method. The finite element method is used to examine the effects of ribs on this passive soil resistance development and the met hanism of failure. The calculated behavior of the ribbed reinforcement is compared with the measured behavi or. Comparisons between the measured and the simulated strain pat terns, failure modes and load displacement relationship are presented. The behavior of the ribbed reinforcements in a cohesive soil is predicted on the basis of a good agreement between the measured and the Predicted behavior of the Ottawa sand.

• Smart Structures and Systems
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• v.5 no.4
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• pp.443-455
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• 2009

The use of fiber reinforced polymer (FRP) reinforcement in concrete structures has been on the rise due to its advantages over conventional steel reinforcement such as corrosion. Reinforcing steel corrosion has been the primary cause of deterioration of reinforced concrete (RC) structures, resulting in tremendous annual repair costs. One application of FRP reinforcement to be further explored is its use in RC frames. Nonetheless, due to FRP's inherently elastic behavior, FRP-reinforced (FRP-RC) members exhibit low ductility and energy dissipation as well as different damage mechanisms. Furthermore, current design standards for FRP-RC structures do not address seismic design in which the beam-column joint is a key issue. During an earthquake, the safety of beam-column joints is essential to the whole structure integrity. Thus, research is needed to gain better understanding of the behavior of FRP-RC structures and their damage mechanisms under seismic loading. In this study, two full-scale beam-column joint specimens reinforced with steel and GFRP configurations were tested under quasi-static loading. The control steel-reinforced specimen was detailed according to current design code provisions. The GFRP-RC specimen was detailed in a similar scheme. The damage in the two specimens is characterized to compare their performance under simulated seismic loading.

• Journal of Korean Association for Spatial Structures
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• v.23 no.3
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• pp.87-94
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• 2023

Chloride is one of the most common threats to reinforced concrete (RC) durability. Alkaline environment of concrete makes a passive layer on the surface of reinforcement bars that prevents the bar from corrosion. However, when the chloride concentration amount at the reinforcement bar reaches a certain level, deterioration of the passive protection layer occurs, causing corrosion and ultimately reducing the structure's safety and durability. Therefore, understanding the chloride diffusion and its prediction are important to evaluate the safety and durability of RC structure. In this study, the chloride diffusion coefficient is predicted by machine learning techniques. Various machine learning techniques such as multiple linear regression, decision tree, random forest, support vector machine, artificial neural networks, extreme gradient boosting annd k-nearest neighbor were used and accuracy of there models were compared. In order to evaluate the accuracy, root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE) and coefficient of determination (R2) were used as prediction performance indices. The k-fold cross-validation procedure was used to estimate the performance of machine learning models when making predictions on data not used during training. Grid search was applied to hyperparameter optimization. It has been shown from numerical simulation that ensemble learning methods such as random forest and extreme gradient boosting successfully predicted the chloride diffusion coefficient and artificial neural networks also provided accurate result.