• Journal of the Korean Geosynthetics Society
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• v.16 no.3
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• pp.1-10
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• 2017

Recently, one of the natural disasters, landslide is causing huge damage to people and properties. In order to minimize the damage caused by continuous landslide, a scientific management system is needed for technologies related to measurement and monitoring system. This study aims to establish a management system for landslide damage by prediction of slope failure. Ground behavior was predicted by surface ground deformation in case of slope failure, and the change in ground displacement was observed as slope surface. As a result, during the slope failure, the ground deformation has the collapse section, the after collapse precursor section, the acceleration section and the burst acceleration section. In all cases, increase in displacement with time was observed as a slope failure, and it is very important event of measurement and maintenance of risky slope. In the future, it can be used as basic data of slope management standard through continuous research. And it can contribute to reduction of landslide damage and activation of measurement industry.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.113-120
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• 2020

Safety accidents, called industrial accidents in construction work, are causing a lot of casualties, property damage and social controversy in the event of an accident, causing the construction to lose public confidence. The risk of safety accidents at construction sites may continue to increase as the construction of high-rise, large-scale, and multi-purpose complex buildings has increased in recent years. In particular, the most frequently constructed apartment construction among reinforced concrete buildings is designed and constructed with a wall-like structure with no beams for each floor, while the lower floors are made of lamen with columns and beams. As a result, the transfer beam or transfer slab to withstand the upper load is installed on the upper part of the Ramen structure, so the system Dongbari, which is installed as a temporary material during concrete laying construction, may collapse at any time during plowing and curing. The purpose of this study is to apply IT convergence technology to prevent the collapse of the system Dongbari during concrete installation, and to apply many of the variables that may occur during construction on a case-by-case basis to check the stability of the system Dongbari and to propose a model of the anti-conducting prediction system.

• Fire Science and Engineering
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• v.24 no.4
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• pp.33-40
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• 2010

A numerical model considering the vapor pressure and the creep models, in the form of a analytical program, for tracing the behavior of high strength concrete (HSC) members exposed to fire is presented. The two stages, i.e., spalling procedure and fire resistance time, associated with the thermal, moisture flow, creep and structural analysis, for the prediction of fire resistance behavior are explained. The use of the analytical program for tracing the response of HSC member from the initial pre-loading stage to collapse, due to fire, is demonstrated. The validity of the numerical model used in this program is established by comparing the predictions from this program with results from others fire resistance tests. The analytical program can be used to predict the fire resistance of HSC members for any value of the significant parameters, such as load, sectional dimensions, member length, and concrete strength.

• Journal of the Korean Geotechnical Society
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• v.35 no.9
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• pp.37-45
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• 2019

Quick identification of the condition of tunnel face and optimized determination of support patterns during tunnel excavation in underground construction projects help engineers prevent tunnel collapse and safely excavate tunnels. This study investigates a CNN technique for quick determination of rock quality classification depending on the condition of tunnel face, and presents the procedure for rock quality classification using a deep learning technique and the improved method for accurate prediction. The VGG16 model developed by tens of thousands prestudied images was used for deep learning, and 1,469 tunnel face images were used to classify the five types of rock quality condition. In this study, the prediction accuracy using this technique was up to 83.9%. It is expected that this technique can be used for an error-minimizing rock quality classification system not depending on experienced professionals in rock quality rating.

• Journal of Korean Tunnelling and Underground Space Association
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• v.8 no.1
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• pp.21-30
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• 2006

In case of an urban tunnel, the displacement of ground base controls the tunnel design because it is built on shallow and unconsolidated ground many times. There are more insufficiency to describe the ground movement which coincides in the measured result of the situ because the design of an urban tunnel is dependent on the method of numerical analysis used to the existing elastic and elasto-plastic models. We studied about the predict ion for the ground movement of a shallow tunnel in unconsolidated ground, mechanism of collapse, and settlement. Also this paper shows comparison with the existing elastic and elasto-plastic model using the unlinear analysis of the strain-softening model. We can model the real ground movement as the increasement of ground surface inclination or occurrence of shear band by using strain-softening model for the result of ground movement of an urban NATM tunnel.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.416-429
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• 2018

Typhoons and floods are natural disasters that occur frequently, and the damage resulting from these disasters must be in advance predicted to establish appropriate responses. Direct damages such as building collapse, human casualties, and loss of farms and fields have more attention from people than indirect damages such as increase of consumer prices. But indirect damages also need to be considered for living. The agricultural products are typical consumer items affected by typhoons and floods. Sudden, powerful typhoons are mostly accompanied by heavy rains and damage agricultural products; this increases the retail price of such products. This study analyzes the influence of natural disasters on the price of agricultural products by using a deep learning algorithm. We decided rice, onion, green onion, spinach, and zucchini as target agricultural products, and used data on variables that influence the price of agricultural products to create a model that predicts the price of agricultural products. The result shows that the model's accuracy was about 0.069 measured by RMSE, which means that it could explain the changes in agricultural product prices. The accurate prediction on the price of agricultural products can be utilized by the government to respond natural disasters by controling amount of supplying agricultural products.

• Structural Engineering and Mechanics
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• v.83 no.2
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• pp.153-166
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• 2022

Structural pounding due to strong seismic excitations can result in severe damage or even collapse of colliding structures. Many researchers focused on studying the mutual pounding between two adjacent structures while very few researches were concerned with the pounding of a series of structures. This paper aims to study the pounding effect on a series of four buildings having different natural frequencies. The paper also investigates the effect of different arrangements of the four buildings on their pounding response. For this, a mathematical model was constructed using Matlab code where, pounding was modeled using a contact force-based approach. A Non-Linear viscoelastic (Hertzdamp) contact element was used and activated only during the approach period of collision. The mathematical model was validated by comparing its prediction versus experimental results on three adjacent buildings. Then the model was used to study the pounding between four adjacent structures arranged in different sequences according to their natural frequencies. The results revealed that increasing the gap distance generally led to decrease the peak responses of the towers. Such response is somehow different from that predicted earlier by the authors for the case of three adjacent buildings. Moreover, the arrangement of towers has a significant effect on their pounding response. Significant difference between the natural frequencies of adjacent structures increases the pounding forces especially when the more flexible buildings are located at the outer edge of the series. The study points out the need for further researches on buildings in series to gain a better understanding of such complex phenomena.

• Computers and Concrete
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• v.21 no.1
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• pp.55-66
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• 2018

A large main shock may consist of numerous aftershocks with a short period. The aftershocks induced by a large main shock can cause the collapse of a structure that has been already damaged by the preceding main shock. These aftershocks are important factors in structural damages. Furthermore, despite what is often assumed in seismic design codes, earthquakes do not usually occur as a single event, but as a series of strong aftershocks and even fore shocks. For this reason, this study investigates the effect and potential of consecutive earthquakes on the response and behavior of concrete structures. At first, six moment resisting concrete frames with 3, 5, 7, 10, 12 and 15 stories are designed and analyzed under two different records with seismic sequences from real and artificial cases. The damage states of the model frames were then measured by the Park and Ang's damage index. From the results of this investigation, it is observed that the sequences of ground motions can almost double the accumulated damage and increased response of structures. Therefore, it is certainly insufficient to ignore this effect in the design procedure of structures. Also, the use of artificial seismic sequences as design earthquake can lead to non-conservative prediction of behavior and damage of structures under real seismic sequences.

• Transactions of Materials Processing
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• v.14 no.8 s.80
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• pp.718-724
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• 2005

An efficient finite element method has been introduced for analysis of metallic sandwich plates subject to bending moment. A full model 3-point bending FE-analysis shows that the plastic behavior of inner structures appears only at the load point. The unit structures of sandwich plates are defined to numerically calculate the bending stiffness and strength utilizing the recurrent boundary condition for pure bending analysis. The equivalent models with the same bending stiffness and strength of full models are then designed analytically. It is demonstrated that the results of both models are almost the same and the FE-analysis method incorporating the equivalent models can reduce the computation time effectively. The dominant collapse modes are face buckling and face yielding. Since the inner dimpled structures prevent face buckling, sandwich plates with inner dimpled shell structure can absorb more energy than other types of sandwich plates during the bending behavior.

• Journal of Korean Tunnelling and Underground Space Association
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• v.15 no.2
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• pp.81-95
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• 2013

When collapse occurs due to explosion near a tunnel, fragmentation zone should be comprehended quickly to recover the function of the tunnel itself. In this study, a method to interpret explosion behavior and predict the fragmentation zone fast. For this purpose, the various 3D-meshes were generated using SolidWorks and explosion analyses were carried out using AUTODYN. The influence of explosion variables such as source location on fragmentation volume were examined by performing sensitivity analyses. Also, a training database for an artificial neural network analysis had been established and the optimal training model was selected, and the predicted results for fragmentation volume and radius were verified. The suggested method had demonstrated that it could be effective for the fast prediction of fragmentation zone.