• The Journal of Engineering Geology
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• v.10 no.2
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• pp.98-112
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• 2000

Discrimination between natural earthquakes and man-made explosions is very essential but critical matter in Seismology. In the CTBT Monitoring business, this is very crucial issue and sometimes could occur the international conflict. In this study, we analyzed seismic and infrasound data from Chulwon Seismo-Acoustic Array and would like to introduce routine data processing procedures at the Korea Institute of Geology, Mining and Materials(KIGAM) to discriminate the earthquakes and artificial explosions. We found analyzing acoustic data together with seismic data is very effective way to identify and discriminate man made explosion from natural earthquake. Recent earthquakes in and around the Korean Peninsula are concentrated in a narrow zone with N60-70$^{\circ}$W in southern Korea, and Pyungan and Hwanghae Province in northern Korea. The mechanism of 14 larger earthquakes in and around the Korean Peninsula since 1936 show predominant strike-slip faulting together with minor thrust component. This indicates horizontal compression is dominant in and around the Korean Peninsula.

• Earthquakes and Structures
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• v.3 no.3_4
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• pp.231-248
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• 2012

In this study, a systematic investigation is carried out on the seismic behaviour of plane moment resisting steel frames (MRF) to repeated strong ground motions. Such a sequence of earthquakes results in a significant damage accumulation in a structure because any rehabilitation action between any two successive seismic motions cannot be practically materialised due to lack of time. In this work, thirty-six MRF which have been designed for seismic and vertical loads according to European codes are first subjected to five real seismic sequences which are recorded at the same station, in the same direction and in a short period of time, up to three days. Furthermore, the examined frames are also subjected to sixty artificial seismic sequences. This investigation shows that the sequences of ground motions have a significant effect on the response and, hence, on the design of MRF. Additionally, it is concluded that ductility demands, behaviour factor and seismic damage of the repeated ground motions can be satisfactorily estimated using appropriate combinations of the corresponding demands of single ground motions.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.33-39
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• 2019

In this paper, we propose deep convolutional neural network(CNN) with bottleneck structure which improves the performance of earthquake classification. In order to address all possible forms of earthquakes including micro-earthquakes and artificial-earthquakes as well as large earthquakes, we need a representation and classifier that can effectively discriminate seismic waveforms in adverse conditions. In particular, to robustly classify seismic waveforms even in low snr, a deep CNN with 1x1 convolution bottleneck structure is proposed in raw seismic waveforms. The representative experimental results show that the proposed method is effective for noisy seismic waveforms and outperforms the previous state-of-the art methods on domestic earthquake database.

• Earthquakes and Structures
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• v.5 no.4
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• pp.417-438
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• 2013

This study was concerned on the application of a hybrid approach for analyzing the buried pipelines deformations subjected to earthquakes. Nonlinear time-history analysis of Finite Element (FE) model of buried pipelines, which was modeled using laboratory data, has been performed via selected earthquakes. In order to verify the FE model with experiments, a statistical test was done which demonstrated a good conformity. Then, the FE model was developed and the optimum intersection angle of pipeline and fault was obtained via genetic algorithm. Transient seismic strain of buried pipeline in the optimum intersection angle of pipeline and fault was investigated considering the pipes diameter, the distance of pipes from fault, the soil friction angles and seismic response duration of buried pipelines. Also, a two-layer perceptron Artificial Neural Network (ANN) was trained using results of FE model, and a nonlinear relationship was obtained to predict the bending strain of buried pipelines based on the pipes diameter, intersection angles of the pipelines and fault, the soil friction angles, distance of pipes from the fault, and seismic response duration; whereas it contains a wide range of initial input data without any requirement to laboratory measurements.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1139-1158
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• 2015

This paper proposes an efficient system identification method for modeling nonlinear behavior of civil structures. This method is developed by integrating three different methodologies: principal component analysis (PCA), artificial neural networks, and fuzzy logic theory, hence named PANFIS (PCA-based adaptive neuro-fuzzy inference system). To evaluate this model, a 3-story building equipped with a magnetorheological (MR) damper subjected to a variety of earthquakes is investigated. To train the input-output function of the PANFIS model, an artificial earthquake is generated that contains a variety of characteristics of recorded earthquakes. The trained model is also validated using the1940 El-Centro, Kobe, Northridge, and Hachinohe earthquakes. The adaptive neuro-fuzzy inference system (ANFIS) is used as a baseline. It is demonstrated from the training and validation processes that the proposed PANFIS model is effective in modeling complex behavior of the smart building. It is also shown that the proposed PANFIS produces similar performance with the benchmark ANFIS model with significant reduction of computational loads.

• 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.

• Interaction and multiscale mechanics
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• v.6 no.4
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• pp.339-356
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• 2013

This paper investigates the optimized parameters of Tuned Mass Dampers (TMDs) for vibration control of high-rise structures including Soil Structure Interaction (SSI). The Artificial Bee Colony (ABC) method is employed for optimization. The TMD Mass, damping coefficient and spring stiffness are assumed as the design variables of the controller; and the objective is set as the reduction of both the maximum displacement and acceleration of the building. The time domain analysis based on Newmark method is employed to obtain the displacement, velocity and acceleration of different stories and TMD in response to 6 types of far field earthquakes. The optimized mass, frequency and damping ratio are then formulated for different soil types; and employed for the design of TMD for the 40 and 15 story buildings and 10 different earthquakes, and well results are achieved. This study leads the researchers to the better understanding and designing of TMDs as passive controllers for the mitigation of earthquake oscillations.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.11a
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• pp.453-456
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• 2003

This research is to evaluate the seismic performance of reinforced concrete bridge piers with lap-spliced longitudinal reinforcement steels in the plastic hinge region, and to develop the enhancement scheme of their seismic capacity. Six circular columns of 0.6m diameter and 1.5m height were made with two confinement steel ratios. They were damaged under series of artificial earthquakes that could be compatible in Korean peninsula. Directly after the pseudo-dynamic test, damaged columns were retested under inelastic reversal cyclic loading simultaneously under an axial load, P=$0.1f_{ck}A_{g}$, and residual seismic performance of damaged columns was evaluated. Test results show that RC bridge piers with lap-spliced longitudinal steels behaved with minor damage even under artificial earthquakes with 0.22g PGA, but failed at low ductility subjected to the subsequent quasi-static load test. This failure was due to the debonding of the lap splice. The specimens externally wrapped with composite FRP straps in the potential plastic hinge region showed significant improvement both in flexural strength and displacement ductility.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.10a
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• pp.91-97
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• 2000

Once a response spectrum is estimated for the site, if there is a need of generating realistic earthquakes time histories considering seismic sources and path effects, one alternative is to use statistical phase characteristics based on real earthquake records other than assuming arbitrary duration and envelope curves. In this study, statistics of group delay times derived from Japanese strong earthquake data were used for phase generation to fully capture the stochastic property of earthquakes. The result shows that simulated earthquake time histories can be generated according to earthquake magnitude and distances with target response spectrum.

• Earthquakes and Structures
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• v.22 no.4
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• pp.401-419
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• 2022

A novel hybrid extreme machine learning-multiverse optimizer (ELM-MVO) framework is proposed to predict the liquefaction phenomenon in seismically excited tunnel lining inside the sand lens. The MVO is applied to optimize the input weights and biases of the ELM algorithm to improve its efficiency. The tunnel located inside the liquefied sand lens is also evaluated under various near- and far-field earthquakes. The results demonstrate the superiority of the proposed method to predict the liquefaction event against the conventional extreme machine learning (ELM) and artificial neural network (ANN) algorithms. The outcomes also indicate that the possibility of liquefaction in sand lenses under far-field seismic excitations is much less than the near-field excitations, even with a small magnitude. Hence, tunnels designed in geographical areas where seismic excitations are more likely to be generated in the near area should be specially prepared. The sand lens around the tunnel also has larger settlements due to liquefaction.