• Smart Structures and Systems
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• v.16 no.5
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• pp.873-889
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• 2015

In civil engineering, probabilistic seismic risk assessment is used to predict the economic damage to a lifeline system of possible future earthquakes. The results are used to plan mitigation measures and to strengthen the structures where necessary. Instead, after an earthquake public authorities need mathematical models that compute: the damage caused by the earthquake to the individual vulnerable components and links, and the global behavior of the lifeline system. In this study, a framework that was developed and used for prediction purpose is modified to assess the consequences of an earthquake in quasi real-time after such earthquake happened. This is possible because nowadays entire seismic regions are instrumented with tight networks of strong motion stations, which provide and broadcast accurate intensity measure maps of the event to the public within minutes. The framework uses the broadcasted map and calculates the damage to the lifeline system and its component in quasi real-time. The results give the authorities the most likely status of the system. This helps emergency personnel to deal with the damage and to prioritize visual inspections and repairs. A highway transportation network is used as a test bed but any lifeline system can be analyzed.

• Geomechanics and Engineering
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• v.21 no.2
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• pp.143-152
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• 2020

Korean society experienced successive earthquakes exceeding 5.0 magnitude in the past three years resulting in an increasing concern about earthquake stability of urban infrastructures. This study focuses on the significant aspects of earthquake risk assessment for the cut-and-cover underground railway station based on two-dimensional dynamic numerical analysis. Presented are features from a case study performed for the railway station in Seoul, South Korea. The PLAXIS2D was employed for numerical simulation and input of the earthquake ground motion was chosen from Pohang earthquake records (M5.4). The paper shows key aspects of earthquake risk for soil-structure system varying important parameters including embedded depth, supported ground information, and applied seismicity level, and then draws several meaningful conclusions from the analysis results such as seismic risk assessment.

• Journal of the Korean Geotechnical Society
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• v.20 no.7
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• pp.15-24
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• 2004

This paper describes a GIS-based assessment of residential building damage caused by the 1994 Northridge earthquake in which the fractions of existing buildings damaged at various percentages of replacement cost are related to a range of seismic parameters. The assessment uses data from safety inspection reports and tax assessor records, both of which were geocoded and linked to seismic parameters derived from strong motion records at 164 different sites. The paper also describes a GIS-based pattern recognition algorithm for identifying locations of most intense building damage. The algorithm provides a framework for rapidly screening remote sensing data and dispatching emerging services.

• Earthquakes and Structures
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• v.17 no.3
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• pp.271-282
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• 2019

Knowing the response of buildings to earthquakes is very important in order to ensure that a structure is able to withstand a given level of ground shaking. Thus, nonlinear dynamic earthquake engineering analyses are unavoidable and are preferable procedure in the seismic assessment of buildings. In order to estimate seismic performance on the basis of the hazard at the site where the structure is located, the selection of appropriate seismic input is known to be a critical step while performing this kind of analysis. In this paper, seismic analysis is performed for a four-story reinforced concrete ISPRA frame structure which is designed according to Eurocode 8 (EC8). A total of 90 different earthquake scenarios were selected, 30 for each of three target spectrums, EC8 spectrum, Uniform Hazard Spectrum (UHS), and Conditional Mean Spectrum (CMS). The aim of this analysis was to evaluate the average maximum Inter-story Drift Ratio (IDR) for each target spectrum. Time history analysis for every earthquake record was obtained and, as a result, IDR as the main measure of damage were presented in order to compare with defined performance levels of reinforced concrete bare frames.

• Structural Engineering and Mechanics
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• v.91 no.5
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• pp.443-457
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• 2024

At present, the traditional concrete surface inspection methods based on artificial vision have the problems of high cost and insecurity, while the computer vision methods rely on artificial selection features in the case of sensitive environmental changes and difficult promotion. In order to solve these problems, this paper introduces deep learning technology in the field of computer vision to achieve automatic feature extraction of structural damage, with excellent detection speed and strong generalization ability. The main contents of this study are as follows: (1) A method based on DeepLabV3+ convolutional neural network model is proposed for surface detection of post-earthquake structural damage, including surface damage such as concrete cracks, spaling and exposed steel bars. The key semantic information is extracted by different backbone networks, and the data sets containing various surface damage are trained, tested and evaluated. The intersection ratios of 54.4%, 44.2%, and 89.9% in the test set demonstrate the network's capability to accurately identify different types of structural surface damages in pixel-level segmentation, highlighting its effectiveness in varied testing scenarios. (2) A semantic segmentation model based on DeepLabV3+ convolutional neural network is proposed for the detection and evaluation of post-earthquake structural components. Using a dataset that includes building structural components and their damage degrees for training, testing, and evaluation, semantic segmentation detection accuracies were recorded at 98.5% and 56.9%. To provide a comprehensive assessment that considers both false positives and false negatives, the Mean Intersection over Union (Mean IoU) was employed as the primary evaluation metric. This choice ensures that the network's performance in detecting and evaluating pixel-level damage in post-earthquake structural components is evaluated uniformly across all experiments. By incorporating deep learning technology, this study not only offers an innovative solution for accurately identifying post-earthquake damage in civil engineering structures but also contributes significantly to empirical research in automated detection and evaluation within the field of structural health monitoring.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.216-223
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• 2003

A time-domain system identification (SI) method is developed for seismic damage assessment on structures. SI algorithms for complete measurements with respect to degrees-of-freedom are proposed. To take account of nonlinear dynamic response, an equation error in the incremental dynamic governing equation is defined for complete measurement between measured and computed acceleration. Variations of stiffness and damping parameters during earthquake vibration are chased by utilizing a constrained nonlinear optimization tool available in MATLAB. A simulation study has been carried out to identify damage event and to assess damage severity by using measured acceleration time history. Mass properties are assumed as known a priori. The effects of measurement noise on the identification are also investigated.

• Structural Engineering and Mechanics
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• v.91 no.4
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• pp.369-382
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• 2024

The earthquake loss assessment framework of ductile reinforced concrete (or RC) frame using component-performance -based methodology was studied in this paper. The elasto-plastic rotation angle was used as the damage indicator of structural component, and the damage-to-loss model was proposed on the basis of the deformation indicator of structural component. Dynamic instability during incremental dynamic analysis was taken as collapse criterion, and column failure was taken as criterion that structure has to be demolished. Expected earthquake losses of low-rise, mid-rise and high-rise RC frames were discussed. The expected earthquake loss encompassed collapse loss, demolition loss and repair loss. Furthermore, component groups of RC frame were divided into structural components, nonstructural components and rugged components. The results indicate that ductile RC frame is more likely to be demolished than collapse, especially in low-rise and mid-rise RC frames. Furthermore, the less collapse margin ratio the structure has, the more demolition probability the structure will suffer under rare earthquake. The demolition share of total earthquake loss might be more prominent than repair share and collapse share in ductile RC frame.

• Earthquakes and Structures
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• v.20 no.3
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• pp.325-335
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• 2021

The majority of Turkey's geography is at risk of earthquakes. Within the borders of Turkey, including the two major active faults contain the North-Eastern and Eastern Anatolia, earthquake, threatening the safety of life and property. On January 24, 2020, an earthquake of magnitude 6.8 occurred at 8:55 p.m. local time. According to the data obtained from the stations in the region, peak ground acceleration in the east-west direction was measured as 0.292 g from the 2308 coded station in Sivrice. It is thought that the earthquake with a magnitude of Mw 6.8 was developed on the Sivrice-Puturge segment of the Eastern Anatolian Fault, which is a left lateral strike slip fault, and the tear developed in an area of 50-55 km. Aftershocks ranging from 0.8 to 5.1 Mw occurred following the main shock on the Eastern Anatolian Fault. The earthquake caused severe structural damages in Elazığ and neighboring provinces. As a result of the field investigations carried out in this study, significant damage levels were observed in the buildings since it did not meet the criteria in the earthquake codes. Within the study's scope, the structural damage cases in reinforced concrete and masonry structures were investigated. Many structural deficiencies and mistakes such as non-ductile details, poor concrete quality, short columns, strong beams-weak columns mechanism, large and heavy overhangs, masonry building damages and inadequate reinforcement arrangements were observed. Requirements of seismic codes are discussed and compared with observed earthquake damage.

• Structural Engineering and Mechanics
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• v.46 no.6
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• pp.791-808
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• 2013

The main purpose of this paper is to develop seismic fragility curves for existing reinforced concrete, RC, buildings based on the post earthquake field survey and the seismic performance using capacity design. Existing RC buildings constitute approximately 65% of the total stock in Algiers. This type of buildings, RC, was widely used in the past and chosen as the structural type for the future construction program of more than 2 millions apartments all over Algeria. These buildings, suffered moderate to extensive damage after the 2003 Boumerdes earthquake, on May 21st. The determination of analytical seismic fragility curves for low-rise and mid-rise existing RC buildings was carried out based on the consistent and complete post earthquake survey after that event. The information on the damaged existing RC buildings was investigated and evaluated by experts. Thirty four (34) communes (districts) of fifty seven (57), the most populated and affected by earthquake damage were considered in this study. Utilizing the field observed damage data and the Japanese Seismic Index Methodology, based on the capacity design method. Seismic fragility curves were developed for those buildings with a large number data in order to get a statistically significant sample size. According to the construction period and the code design, four types of existing RC buildings were considered. Buildings designed with pre-code (very poor structural behavior before 1955), Buildings designed with low code (poor structural behavior, between 1955-1981), buildings designed with medium code (moderate structural behavior, between 1981-1999) and buildings designed with high code (good structural behavior, after 1999).

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1206-1208
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• 2003

The extraction of earthquake damage from remote sensed imagery requires high spatial resolution and temporal effectiveness of acquisition of imagery. The analog photographs and visual interpretation were taken traditionally. Now it is possible to acquire damage information from many commercial high resolution RS satellites. The key techniques are processing velocity and precision. The authors developed the automatic / semiautomatic image process techniques including feature enhancement, and classification, designed the emergency Earthquake Damage and Losses Evaluate System based on Remote Sensing (RSEDLES). The paper introduced the functions of RSEDLES as well as its application to the earthquakes occurred recently.