• Structural Engineering and Mechanics
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• v.31 no.3
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• pp.333-347
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• 2009

Due to structural complicacy, structural health monitoring for civil engineering needs more accurate and effectual methods of damage identification. This study aims to import multi-source information fusion (MSIF) into structural damage diagnosis to improve the validity of damage detection. Firstly, the essential theory and applied mathematic methods of MSIF are introduced. And then, the structural damage identification method based on multi-mode information fusion is put forward. Later, on the basis of a numerical simulation of a concrete continuous box beam bridge, it is obviously indicated that the improved modal strain energy method based on multi-mode information fusion has nicer sensitivity to structural initial damage and favorable robusticity to noise. Compared with the classical modal strain energy method, this damage identification method needs much less modal information to detect structural initial damage. When the noise intensity is less than or equal to 10%, this method can identify structural initial damage well and truly. In a word, this structural damage identification method based on multi-mode information fusion has better effects of structural damage identification and good practicability to actual structures.

• Smart Structures and Systems
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• v.31 no.6
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• pp.573-583
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• 2023

Although unmanned aerial vehicles have been used to overcome the limited accessibility of human-based visual inspection, unresolved issues still remain. Onsite inspectors face difficulty finding previously detected damage locations and tracking their status onsite. For example, an inspector still marks the damage location on a target structure with chalk or drawings while comparing the current status of existing damages to their previous status, as documented onsite. In this study, an augmented-reality-based structural inspection system with onsite damage information marking was developed to enhance the convenience of inspectors. The developed system detects structural damage, creates a holographic marker with damage information on the actual physical damage, and displays the marker onsite via an augmented reality headset. Because inspectors can view a marker with damage information in real time on the display, they can easily identify where the previous damage has occurred and whether the size of the damage is increasing. The performance of the developed system was validated through a field test, demonstrating that the system can enhance convenience by accelerating the inspector's essential tasks such as detecting damages, measuring their size, manually recording their information, and locating previous damages.

• Journal of the Korean Society of Safety
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• v.31 no.2
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• pp.127-132
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• 2016

In this study, the plan to construct a disaster information categorization system that can be objectively and efficiently performed was suggested in order to perform disaster management task systematically. Recently, the damage of natural disasters is gradually growing larger and faster, increasing the economic loss. Especially, as for the domestic storm damage, the damage from strong wind was found to be greater than the damage from torrential rain. Also, strong wind was found to be inflicting a great damage on human life, property and agricultural crops, so the necessity to study damage restoration from strong wind is increasing. Nevertheless, the damage items categorized in the domestic disaster year book are often comprehensive or unclear in criteria, and thus fail to reflect items or matters due to actual disaster damage. It is difficult to aggregate damage accurately such that it does not correspond to the national compensation scope or the damage amount is calculated according to subjective judgment of the investigator in charge. As such, if the disaster information management is inadequate by not applying accurate categorization criteria from damage amount calculation, there can be an issue with fairness when paying the damage support aid. Therefore, this study suggested a categorization plan for objective and efficient execution of disaster information management task in order to resolve such issues. It is expected that quick and efficient execution would be possible in disaster information management and task procedure domestically by constructing systematic categorization system related to disaster information.

• Journal of the Earthquake Engineering Society of Korea
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• v.22 no.3
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• pp.121-128
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• 2018

Severe earthquakes can cause damage to society both socially and economically. An appropriate initial response can alleviate damage from severe earthquakes. In order to formulate an appropriate initial response, it is necessary to identify damage situations in societies; however, it is difficult to grasp this information immediately after an earthquake event. In this study, an earthquake damage assessment methodology for buildings is proposed for estimating damage situations immediately after severe earthquakes. A response spectrum database is constructed to provide response spectra at arbitrary locations from earthquake measurements immediately after the event. The fragility curves are used to estimate the damage of the buildings. Earthquake damage assessment is performed from the response spectrum database at the building scale to provide enhanced damage condition information. Earthquake damage assessment for Gyeongju city and Pohang city were conducted using the proposed methodology, when an earthquake occurred on September 12, 2016, and November 15, 2017. Results confirm that the proposed earthquake damage assessment effectively represented the earthquake damage situation in the city to decide on an appropriate initial response by providing detailed information at the building scale.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.81-100
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• 2020

The purpose of this study was to propose applicability of spatial data and quality check criteria for estimating damage from storm and flood. Using the data from the National Disaster Management System and National Spatial Data Infrastructure, spatial database for estimation of storm and flood damage has been mapped to each type of damage. This was proposed as the quality check criteria for damage analysis. Through this study, it is possible to utilize the spatial database for estimating storm and flood damage. The reliability of analysis results are ensured through the quality check criteria.

• Journal of IKEEE
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• v.18 no.1
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• pp.45-56
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• 2014

Recently, damages from disasters such as downpours, earthquakes and typhoons are increasing throughout the world. The downpour days of Korean Peninsula are also increasing every year due to rapid climate change. According to statistics over the last 30 years of the earthquakes in Korean Peninsula, the probability of a future earthquake is very high. In addition, super typhoons will hit Korean Peninsula due to the temperature rise in the nearby sea caused by the deepening of global warming. Thus, damage costs of the waterfront structures by natural disasters are also growing. But damage information system for integrated management of waterfront structures are insufficient. In this paper, we designed and implemented a damage information system for integrated management of waterfront structures. First, we classified damage information caused by natural disaster. Then we designed the databases of damage information and implemented damage information system. Lastly, we checked operations and the feasibility by testing queries on the proposed system.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.505-509
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• 2020

Twitter is a useful medium to grasp various damage situations that have occurred in society. However, it is a laborious task to spot damage-related topics according to time in the environment where information is constantly produced. This paper proposes a methodology of constructing a knowledge structure by combining the BERT-based classifier and the community detection techniques to discover the topics underlain in the damage information. The methodology consists of two steps. In the first step, the tweets are classified into the classes that are related to human damage, infrastructure damage, and industrial activity damage by a BERT-based transfer learning approach. In the second step, networks of the words that appear in the damage-related tweets are constructed based on the co-occurrence matrix. The derived networks are partitioned by maximizing the modularity to reveal the hidden topics. Five keywords with high values of degree centrality are selected to interpret the topics. The proposed methodology is validated with the Hurricane Harvey test data.

• Smart Structures and Systems
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• v.25 no.2
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• pp.169-181
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• 2020

Sensor placement is a crucial aspect of bridge health monitoring (BHM) dedicated to accurately estimate and locate structural damages. In addressing this goal, a sensor placement framework based on the deflection influence line (DIL) analysis is here proposed, for the optimal design of damage detection-oriented BHM system. In order to improve damage detection accuracy, we explore the change of global stiffness matrix, damage coefficient matrix and DIL vector caused by structural damage, and thus develop a novel sensor placement framework based on the Fisher information matrix. Our approach seeks to determine the contribution of each sensing node to damage detection, and adopts a distance correction coefficient to eliminate the information redundancy among sensors. The proposed damage detection-oriented optimal sensor placement (OSP) method is verified by two examples: (1) a numerically simulated three-span continuous beam, and (2) the Pinghu bridge which has existing real damage conditions. These two examples verify the performance of the distance corrected damage sensitivity of influence line (DSIL) method in significantly higher contribution to damage detection and lower information redundancy, and demonstrate the proposed OSP framework can be potentially employed in BHM practices.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.443-458
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• 2012

The structural health monitoring (SHM) benchmark study on optimal sensor placement problem for the instrumented Canton Tower has been launched. It follows the success of the modal identification and model updating for the Canton Tower in the previous benchmark study, and focuses on the optimal placement of vibration sensors (accelerometers) in the interest of bettering the SHM system. In this paper, the sensor placement problem for the Canton Tower and the benchmark model for this study are first detailed. Then an information entropy based sensor placement method with the purpose of damage detection is proposed and applied to the benchmark problem. The procedure that will be implemented for structural damage detection using the data obtained from the optimal sensor placement strategy is introduced and the information on structural damage is specified. The information entropy based method is applied to measure the uncertainties throughout the damage detection process with the use of the obtained data. Accordingly, a multi-objective optimal problem in terms of sensor placement is formulated. The optimal solution is determined as the one that provides equally most informative data for all objectives, and thus the data obtained is most informative for structural damage detection. To validate the effectiveness of the optimally determined sensor placement, damage detection is performed on different damage scenarios of the benchmark model using the noise-free and noise-corrupted measured information, respectively. The results show that in comparison with the existing in-service sensor deployment on the structure, the optimally determined one is capable of further enhancing the capability of damage detection.

• Journal of Environmental Science International
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• v.19 no.3
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• pp.353-363
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• 2010

The most efficient measures to reduce damage from natural disasters include activities which prevent disasters in advance, decrease possibility of disasters and minimize the scale of damage. Therefore, developing of the risk assessment model is very important to reduce the natural disaster damage. This study estimated a typhoon damage which is the biggest damage scale among increased natural disasters in Korea along with climate change. The results of 3-second gust at the height of 10m level from the typhoon 'Maemi' which did considerable damage to Korean in 2003, using the wind data at the height of 700 hPa. September 12th 09 LST~13th 12 LST period by the time a typhoon Maemi approached to the Korean peninsula. This study estimate damage amount using 'Fragility curve' which is the damage probability curve about a certain wind speed of the each building component factors based on wind load estimation results by using 3-second gust. But the fragility curve is not to Korea. Therefore, we use the fragility curves to FPHLM(FDFS, 2005). The result of houses damage amount is about 11 trillion 5 million won. This values are limit the 1-story detached dwelling, $62.51\sim95.56\;m^2$ of total area. Therefore, this process is possible application to other type houses.