• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.2
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• pp.195-202
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• 2002

Urbanization and development of industry makes people concerned about quality of circumstances. Problems of vibration are on the rise. Vibration makes inhabitants feel unpleasant and involves structural damage. The purpose of this study is to assess damage of reinforced concrete structures due to ground motions as the parameters of frequency, duration time and aspect ratio of structures are changed. Ground motions were modeled as sine waves. To compare sine waves with real ground motions, two cases are selected; one is blast loading case and the other is earthquake loading. It was intended to provide means to assess R/C structure damage due to ground motions.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.80-88
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• 2020

This paper describes the development trends and service provision examples of disaster occurrence and spread prediction technology for various disasters such as tsunamis, floods, and fires. In terms of fires, we introduce the WIFIRE system, which predicts the spread of large forest fires in the United States, and the Metro21: Smart Cities Institute project, which predicts the risk of building fires. This paper describes the development trends in tsunami prediction technology in the United States and Japan using artificial intelligence (AI) to predict the occurrence and size of tsunamis that cause great damage to coastal cities in Japan, Indonesia, and the United States. In addition, it introduces the NOAA big data platform built for natural disaster prediction, considering that the use of big data is very important for AI-based disaster prediction. In addition, Google's flood forecasting system, domestic and overseas earthquake early warning system development, and service delivery cases will be introduced.

• Structural Engineering and Mechanics
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• v.23 no.2
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• pp.177-193
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• 2006

Determining the hysteretic energy demand and dissipation capacity and level of damage of the structure to a predefined earthquake ground motion is a highly non-linear problem and is one of the questions involved in predicting the structure's response for low-performance levels (life safe, near collapse, collapse) in performance-based earthquake resistant design. Neural Network (NN) analysis offers an alternative approach for investigation of non-linear relationships in engineering problems. The results of NN yield a more realistic and accurate prediction. A NN model can help the engineer to predict the seismic performance of the structure and to design the structural elements, even when there is not adequate information at the early stages of the design process. The principal aim of this study is to develop and test multi-layered feedforward NNs trained with the back-propagation algorithm to model the non-linear relationship between the structural and ground motion parameters and the hysteretic energy demand in steel moment resisting frames. The approach adapted in this study was shown to be capable of providing accurate estimates of hysteretic energy demand by using the six design parameters.

• Journal of the Earthquake Engineering Society of Korea
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• v.17 no.3
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• pp.133-141
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• 2013

This paper presents the seismic evaluation and prediction of a damaged piloti-type Reinforced Concrete (RC) building before and after post-retrofitting under successive earthquakes. For considering realistic successive earthquakes, the past records measured at the same station were combined. In this study, the damaged RC building due to the first earthquake was retrofitted with a buckling-restrained brace (BRB) before the second earthquake occurred. Nonlinear Time History Analysis (NTHA) was performed under the scaled intensity of the successive ground motions. Based on the extensive structural response data obtained form from the NTHA, the fragility relationships between the ground shaking intensity and the probability of reaching a pre-determined limit state was were derived. In addition, The the fragility curves of the pre-damaged building without and with the BRBs were employed to evaluate the effect of the successive earthquakes and the post-retrofit effect. Through the seismic assessment subjected to the successive records, it was observed that the seismic performance of the pre-damaged building was significantly affected by the severity of the damage from the first earthquake damages and the hysteresis behavior of the retrofit element.

• Earthquakes and Structures
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• v.8 no.6
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• pp.1363-1386
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• 2015

The October 23 2011 Van Earthquake is studied from an earthquake engineering point of view. Strong ground motion processing was performed to investigate features of the earthquake source, forward directivity effects during the rupture process as well as local site effects. Strong motion characteristics were investigated in terms of peak ground motion and spectral acceleration values. Directiviy effects were discussed in detail via elastic response spectra and wide band spectograms to see the high frequency energy distributions. Source parameters and slip distribution results of the earthquake which had been proposed by different researchers were summarized. Influence of the source parameters on structural response were shown by comparing elastic response spectra of Muradiye synthetic records which were performed by broadband strong motion simulations of the earthquake. It has been emphasized that characteristics of the earthquake rupture dynamics and their effects on structural design might be investigated from a multidisciplinary point of view. Seismotectonic calculations (e.g., slip pattern, rupture velocity) may be extended relating different engineering parameters (e.g., interstorey drifts, spectral accelerations) across different disciplines while using code based seismic design approaches. Current state of the art building codes still far from fully reflecting earthquake source related parameters into design rules. Some of those deficiencies and recent efforts to overcome these problems were also mentioned. Next generation ground motion prediction equations (GMPEs) may be incorporated with certain site categories for site effects. Likewise in the 2011 Van Earthquake, Reverse/Oblique earthquakes indicate that GMPEs need to be feasible to a wider range of magnitudes and distances in engineering practice. Due to the reverse faulting with large slip and dip angles, vertical displacements along with directivity and fault normal effects might significantly affect the engineering structures. Main reason of excessive damage in the town of Erciş can be attributed to these factors. Such effects should be considered in advance through the establishment of vertical design spectra and effects might be incorporated in the available GMPEs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.69-75
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• 2019

The frequency of natural disasters and the scale of damage are increasing due to the abnormal weather phenomenon that occurs worldwide. Especially, damage caused by natural disasters in coastal areas around the world such as Earthquake in Japan, Hurricane Katrina in the United States, and Typhoon Maemi in Korea are huge. If we can predict the damage scale in response to disasters, we can respond quickly and reduce damage. In this study, we developed damage prediction functions for Wind waves caused by sea breezes and waves during various natural disasters. The disaster report (1991 ~ 2017) has collected the history of storm and typhoon damage in coastal areas in Korea, and the amount of damage has been converted as of 2017 to reflect inflation. In addition, data on marine weather factors were collected in the event of storm and typhoon damage. Regression analysis was performed through collected data, Finally, predictive function of the sea turbulent damage by the sea area in 74 regions of the country were developed. It is deemed that preliminary damage prediction can be possible through the wind damage prediction function developed and is expected to be utilized to improve laws and systems related to disaster statistics.

• Smart Structures and Systems
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• v.4 no.6
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• pp.759-777
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• 2008

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

• Earthquakes and Structures
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• v.22 no.5
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• pp.503-515
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• 2022

This paper presents the development of seismic fragility curves for a precast reinforced concrete bridge instrumented with a structural health monitoring (SHM) system. The bridge is located near an active seismic fault in the Dominican Republic (DR) and provides the only access to several local communities in the aftermath of a potential damaging earthquake; moreover, the sample bridge was designed with outdated building codes and uses structural detailing not adequate for structures in seismic regions. The bridge was instrumented with an SHM system to extract information about its state of structural integrity and estimate its seismic performance. The data obtained from the SHM system is integrated with structural models to develop a set of fragility curves to be used as a quantitative measure of the expected damage; the fragility curves provide an estimate of the probability that the structure will exceed different damage limit states as a function of an earthquake intensity measure. To obtain the fragility curves a digital twin of the bridge is developed combining a computational finite element model and the information extracted from the SHM system. The digital twin is used as a response prediction tool that minimizes modeling uncertainty, significantly improving the predicting capability of the model and the accuracy of the fragility curves. The digital twin was used to perform a nonlinear incremental dynamic analysis (IDA) with selected ground motions that are consistent with the seismic fault and site characteristics. The fragility curves show that for the maximum expected acceleration (with a 2% probability of exceedance in 50 years) the structure has a 62% probability of undergoing extensive damage. This is the first study presenting fragility curves for civil infrastructure in the DR and the proposed methodology can be extended to other structures to support disaster mitigation and post-disaster decision-making strategies.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.4
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• pp.443-451
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• 2016

Globally, landslides triggered by natural or human activities have resulted in enormous damage to both property and life. Recent climatic changes and anthropogenic activities have increased the number of occurrence of these disasters. Despite many researches, there is no standard method that can produce reliable prediction. This article discusses the process of landslide susceptibility mapping using various methods in current literatures and applies the FR (Frequency Ratio) method to develop a susceptibility map for the 2015 earthquake region of Sindhupalchowk, Nepal. The complete mapping process describes importance of selection of area, and controlling factors, widespread techniques of modelling and accuracy assessment tools. The FR derived for various controlling factors available were calculated using pre- and post- earthquake landslide events in the study area and the ratio was used to develop susceptibility map. Understanding the process could help in better future application process and producing better accuracy results. And the resulting map is valuable for the local general and authorities for prevention and decision making tasks for landslide disasters.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.913-916
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• 2005

This paper presents the development of Artificial Neural Network models for forecasting the cost and contract duration of school reconstruction projects to assist the planners' decision-making in the early stage of the projects. 132 schools reconstruction projects in central Taiwan, which received the most serious damage from the Chi-Chi Earthquake, were collected. The developed Artificial Neural Network prediction models demonstrate good prediction abilities with average error rates under 10% for school reconstruction projects. The analytical results indicate that the Artificial Neural Network model with back-propagation learning is a feasible method to produce accurate prediction results to assist planners' decision-making process.