• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.775-788
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• 2006

Many disaster monitoring systems are constantly studied to prevent disasters such as environmental pollution, the breaking of a tunnel and a building, flooding, storm earthquake according to the progress of wireless telecommunication, the miniaturization of terminal devices, and the spread of sensor network. A disaster monitoring system can extract information of a remote place, process sensor data with rules to recognize disaster situation, and provide work for preventing disaster. However existing monitoring systems are not enough to predict and prevent disaster, because they can only process current sensor data through utilizing simple aggregation function and operators. In this paper, we design and implement a disaster prevention system to predict near future dangerous area through using outside sensor network and spatial Information. The provided prediction technique considers the change of spatial information over time with current sensor data, and indicates the place that could be dangerous in near future. The system can recognize which place would be dangerous and prepare the disaster prevention. Therefore, damage of disaster and cost of recovery would be reduced. The provided disaster prevention system and prediction technique could be applied to various disaster prevention systems and be utilized for preventing disaster and reducing damages.

• 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.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.771-777
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• 2018

This study proposes a big data based risk analysis framework to analyze more comprehensive disaster risk and vulnerability. We introduce a distributed and parallel framework that allows large volumes of data to be processed in a short time by using open-source disaster risk assessment tool. A performance analysis of the proposed system presents that it achieves a more faster processing time than that of the existing system and it will be possible to respond promptly to precise prediction and contribute to providing guideline to disaster countermeasures. Proposed system is able to support accurate risk prediction and mitigate severe damage, therefore will be crucial to giving decision makers or experts to prepare for emergency or disaster situation, and minimizing large scale damage to a region.

• Journal of Environmental Science International
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• v.15 no.8
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• pp.759-774
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• 2006

We employed two data assimilation techniques including MM5 Four Dimensional Data Asssimilation (FDDA) and Local Analysis and Prediction System (LAPS) to find out the effects of the changed inetial conditions on the wind fields simulation according to the objective analysis methods. We designed 5 different modeling cases. EXP B used no data assimilation system. Both EXP Fl using surface observations and EXP F2 with surface and upper-air observations employed MM5 FDDA. EXP Ll using surface observations and EXP L2 with surface and upper-air observations used LAPS. As results of, simulated wind fields using MM5 FDDA showed locally characterized wind features due to objective analysis techniques in FDDA which is forcefully interpolating simulated results into observations. EXP Fl represented a large difference in comparison of wind speed with EXP B. In case of LAPS, simulated horizontal distribution of wind fields showed a good agreement with the patterns of initial condition and EXP Ll showed comparably lesser effects of data assimilation of surface observations than EXP Fl. When upper-air observations are applied to the simulations, while MM5 FDDA could hardly have important effects on the wind fields simulation and showed little differences with simulations with merely surface observations (EXP Fl), LAPS played a key role in simulating wind fields accurately and it could contribute to alleviate the over-estimated winds in EXP Ll simulations.

• Journal of the Korean Geotechnical Society
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• v.36 no.8
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• pp.7-15
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• 2020

Constructing the maximum displacement and shear force database for the seismic performance of building with soil-structure interaction under varied earthquake scenarios and geotechnical conditions is critical in developing the neural network-based prediction models. However, using the available 3D FEM-based computer simulation techniques causes high computation costs in developing the database. This study introduces the framework of developing the artificial neural network (ANN) model to predict the seismic performance of building at given Poisson's ratio and shear wave velocity of soil. The simple Single-Degree-Of-Freedom system was used to develop the database and the performance of the developed neural network model is discussed through the evaluated coefficient of determination (R²). In addition, ANN models were developed for 90~100% percentile of the database to assess the accuracy of the developed ANN models in each percentile.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.533-535
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• 2021

The differences between this study and previous studies are as follows. First, by building a cloud-based system using IoT technology, the system was built to monitor the status of buildings in real time from anywhere with an internet connection. Second, a model for predicting the future was developed using artificial intelligence (LSTM) and statistical (ARIMA) methods for the measured time series sensor data, and the effectiveness of the proposed prediction model was experimentally verified using a scaled-down building model. Third, a method to analyze the condition of a building more three-dimensionally by visualizing the structural deformation of a building by convergence of multiple sensor data was proposed, and the effectiveness of the proposed method was demonstrated through the case of an actual earthquake-damaged building.

• Structural Engineering and Mechanics
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• v.30 no.3
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• pp.351-368
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• 2008

The purpose of this paper is to propose a simple analysis method of axial deformation of base-isolation rubber bearings in a building subjected to earthquake loading and present its applicability to the analysis of the bound of the aspect ratio of base-isolated buildings. The base shear coefficient is introduced as a key parameter for the bound analysis. The bound of the aspect ratio of base-isolated buildings is analyzed based on the relationship of the following four quantities; (i) ultimate state of the tensile stress of rubber bearings based on a proposed simple recursive analysis for seismic loading, (ii) ultimate state of drift of the base-isolation story for seismic loading, (iii) ultimate state of the axial compressive stress of rubber bearings under dead loads, (iv) prediction of the overturning moment at the base for seismic loading. In particular, a new recursive analysis method of axial deformation of rubber bearings is presented taking into account the nonlinear tensile behavior of rubber bearings and it is shown that the relaxation of the constraint on the ultimate state of the tensile stress of rubber bearings increases the limiting aspect ratio.

• Computational Structural Engineering
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• v.1 no.1
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• pp.103-112
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• 1988

In this study, the earthquake response of building structures with foundation uplift was investigated. The Winkler foundation model and two-spring model are widely used to represent the interaction between foundation mat and soil. While the analysis using the Winkler foundation model results in more accurate prediction, it requires a complex procedure and longer computation time. In this study, an equivalent two-spring model(S model) is proposed. The S model can represent the Winkler foundation model more accurately and the analysis using the S model is simpler and more effective. The S model is derived by simplifying the nonlinear moment-rotation relationship of foundation mat. The dynamic responses predicted by the S model gave a good agreement to those of the Winkler foundation model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.5
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• pp.1107-1112
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• 2008

Since vibration properties of a building structure were not easy to find out through a test, it was very difficult to in advance evaluate an influence of earthquake or other excitations on the building structure. However, currently, along with the development of the vibration analysis technique, it is possible to predict the structural performances of the buildings. The prediction of the vibration properties of the building structure has mainly employed a two-dimensional plane analysis so far, but not a three-dimensional analysis. The two-dimensional plane analysis encounters a reliability problem when the building is asymmetrical. This study has performed a three-dimensional modeling and vibration analysis on residential buildings when a subway passes below.

• Earthquakes and Structures
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• v.8 no.5
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• pp.1017-1038
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• 2015

This paper presents a strengthening method that involves the use of ferrocement jackets and chamfers to relocate plastic hinge for non-seismically designed reinforced concrete exterior beam-column joints. An experimental study was conducted to assess the effectiveness of the proposed strengthening method. Four half-scale beam-column joints, including one control specimen and three strengthened specimens, were prepared and tested under quasi-static cyclic loading. Strengthening schemes include ferrocement jackets with or without skeleton reinforcements and one or two chamfers. Experimental results have indicated that the proposed strengthening method is effective to move plastic hinge from the joint to the beam and enhance seismic performance of beam-column joints. Shear stress and distortion within the joint region are also reduced significantly in strengthened specimens. Skeleton reinforcements in ferrocement provide limited improvement, except on crack control. Specimen strengthened by ferrocement jackets with one chamfer exhibits slight decrease in peak strength and energy dissipation but with increase in ductility as compared with that of two chamfers. Finally, a method for estimating moment capacity at beam-column interface for strengthened specimen is developed. The proposed method gives reasonable prediction and can ensure formation of plastic hinge at predetermined location in the beam.