• Earthquakes and Structures
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• v.25 no.6
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• pp.469-479
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• 2023

A probabilistic seismic damage analysis is an essential procedure to identify seismically vulnerable structures, prioritize the seismic retrofit, and ultimately minimize the overall seismic risk. To assess the seismic risk of multiple structures within a region, a large number of nonlinear time-history structural analyses must be conducted and studied. As a result, each assessment requires high computing resources. To overcome this limitation, we explore a deep learning-based metamodel to enable the prediction of the mean and the standard deviation of the seismic damage distribution of track-on steel-plate girder railway bridges in Korea considering the geometric variation. For machine learning training, nonlinear dynamic time-history analyses are performed to generate 800 high-fidelity datasets on the seismic response. Through intensive trial and error, the study is concentrated on developing an optimal machine learning architecture with the pre-identified variables of the physical configuration of the bridge. Additionally, the prediction performance of the proposed method is compared with a previous, well-defined, response surface model. Finally, the statistical testing results indicate that the overall performance of the deep-learning model is improved compared to the response surface model, as its errors are reduced by as much as 61%. In conclusion, the model proposed in this study can be effectively deployed for the seismic fragility and risk assessment of a region with a large number of structures.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.5
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• pp.635-643
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• 2018

In the present study, influence of earthquake intensity range on seismic fragility analysis of a RC bridge has been evaluated. For this purpose, a RC bridge damaged by a past earthquake has been selected, and analytical model of the bridge has been developed for nonlinear dynamic time-history analysis. A total of 25 recorded earthquake motions have been employed for the nonlinear analysis from which maximum lateral drift ratio of piers are obtained. Then, seismic fragility analysis has been conducted for the bridge using the nonlinear analysis results. Probability of exceeding damage has been computed in terms of using the maximum likelihood estimation, and effect of earthquake intensity range of the motions on seismic fragility curves has been assessed analytically. Analytical predictions indicate that the earthquake intensity range is of utmost significance for rationale seismic fragility analysis reflecting a physical damage state of a bridge and seismic performance evaluation of such bridge.

• International Journal of Concrete Structures and Materials
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• v.1 no.1
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• pp.29-36
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• 2007

The purpose of this paper is the assessment of the capacity of the reinforced concrete (RC) elements of an arch bridge when they are subjected to contact and near-contact explosive charges of various amounts, and the estimation of the critical charges for these components. The bridge considered is the Tenza Viaduct, a decommissioned structure south of Naples, Italy. Its primary elements, deck, piers and arches were analyzed. The evaluation was accomplished via numerical analyses that made possible to obtain the elements dynamic response when they are exposed to blast loading conditions. To evaluate the member's capacities, failure criteria for deck, piers and arches were proposed based on concrete damage parameters. Additionally, curves relating the explosive charge to the residual capacity and to damage level of the elements were also developed. The results of this work were taken into account to investigate the progressive collapse of the global structure.

• Structural Engineering and Mechanics
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• v.28 no.4
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• pp.387-410
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• 2008

The fatigue damage accumulation rates of horizontally curved thin walled box-girder bridge have been estimated from vehicle-induced dynamic stress history using rain flow cycle counting method in the time domain approach. The curved box-girder bridge has been numerically modeled using computationally efficient thin walled box-beam finite elements, which take into account the important structural actions like torsional warping, distortion and distortional warping in addition to the conventional displacement and rotational degrees of freedom. Vehicle model includes heave-pitch-roll degrees of freedom with longitudinal and transverse input to the wheels. The bridge deck unevenness, which is taken as inputs to the vehicle wheels, has been assumed to be a realization of homogeneous random process specified by a power spectral density (PSD) function. The linear damage accumulation theory has been applied to calculate fatigue life. The fatigue life estimated by cycle counting method in time domain has been compared with those found by estimating the PSD of response in frequency domain. The frequency domain method uses an analytical expression involving spectral moment characteristics of stress process. The effects of some of the important parameters on fatigue life of the curved box bridge have been studied.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.102-110
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• 2023

PSC-I girder bridges constitute the largest proportion among highway bridges in Korea. According to the precision safety diagnosis data for the past 10 years, approximately 41.3% of the PSC-I bridges have been graded as C. Furthermore, with the increase in the aging of bridges, preemptive management is becoming more important. Damage and deterioration to the deck and girder with a long replacement cylce can have considerable impacts on the service and deterioration of a bridge. In addition, the high rate of device damages, including expansion joints and bearings, necessitates an investigation into the influence of the device damage in the structural members of the bridge. Therefore, this study defined representative PSC-I girder bridges with single and multiple spans to evaluate heterogeneous damages that incorporate the damage of the bridge member and device with the deterioration of the deck. The heterogeneous damages increased a crack area ratio compared to the individual single damage. For the single-span bridge, the occurrence of bearing damage leads to the spread of crack distribution in the girder, and in the case of multi-span bridges, expansion joint damage leads to the spread of crack distribution in the deck. The research underscores that bridge devices, when damaged, can cause subsequent secondary damage due to improper repair and replacement, which emphasizes the need for continuous observation and responsive action to the damages of the main devices.

• Journal of the Korea institute for structural maintenance and inspection
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• v.7 no.1
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• pp.267-277
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• 2003

The purpose of this study makes a retrofit and rehabilitation practice trough the analysis and the improvement for the underlying problem of current retrofit and rehabilitation methods. Therefore, the deterioration process, the damage cause, the condition classification, the fatigue mechanism and the applied quantity of strengthening methods for slab bridge decks were analysed. Artificial neural networks are efficient computing techniqures that are widely used to solve complex problems in many fields. In this study, a back-propagation neural network model for estimating a management on existing slab bridge decks from damage cause, damage type, and integrity assessment at the initial stsge is need. The training and testing of the network were based on a database of 36. Four different network models werw used to study the ability of the neural network to predict the desirable output of increasing degree of accuracy. The neural networks is trained by modifying the weights of the neurons in response to the errors between the actual output values and the target output value. Training was done iteratively until the average sum squared errors over all the training patterms were minimized. This generally occurred after about 5,000 cycles of training.

• Journal of Korean Society of Steel Construction
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• v.15 no.5 s.66
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• pp.475-487
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• 2003

This study developed an analysis model of estimating fatigue damage using the linear elastic fracture mechanics method. Stress history occurring to an element when a truck passed over a bridge was defined as block loading and crack closure theory explaining load interaction effect was applied. Stress range frequency analysis considering dead load stress and crack opening was done. Probability of stress range frequency distribution was applied and the probability distribution parameters were estimated. The Monte Carlo simulation of generating the probability various of distribution was performed. The probability distribution of failure block numbers was obtained. With this the fatigue reliability of an element not occurring in failure could be calculated. The failure block number divided by average daily truck traffic remains the life of a day. Fatigue reliability analysis model was carried out for the welding member of cross beam flange and vertical stiffener of steel box bridge using the proposed model. Consequently, a 3.8% difference was observed between the remaining life in the peak analysis method and in the proposed analysis model. The proposed analysis model considered crack closure phase and crack retard.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• v.4 no.1
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• pp.31-37
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• 2001

In this paper, an integrated damage identification system (IDIS) is proposed to locate and size damage in real structures. The application of the IDIS to real structures includes the measurement of modal responses, the construction of damage-detection models, and the implementation of measurements and models into the damage-detection process. Firstly, the theory of the damage identification method is outlined. Secondly, the schematic and each component of the IDIS are described. Finally, the practicality of the IDIS is verified from experiments on two different bridge-models, a model plate-grider and a model truss.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1291-1296
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• 2000

A basis for the direct use of data from nondestructive evaluation methods in bridge management systems is presented. Bridge management systems use integer-valued condition ratings to recognize conditions of bridge elements, to model progression of deterioration, and to determine repair needs. Data from nondestructive evaluation methods can inform management systems on the extent of damage, on the initiation of deterioration processes, and on the exposure of bridge elements to aggressive agents. In addition, data obtained through nondestructive evaluation methods allow the formation of models of specific deterioration process. The use of these data in bridge management systems requires redefinition of condition ratings together with the creation of procedures for automated interpretation of data. By these action, nondestructive evaluation methods are directly used to assign condition ratings, and condition ratings are made into terse form of NDE data that are compatible with present day bridge management systems. This paper reports work in progress to strategic use of nondestructive evaluation methods in bridge management system.

• Smart Structures and Systems
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• v.13 no.5
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• pp.775-796
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• 2014

This study presents a vibration-based health monitoring strategy for short span bridges utilizing an inspection vehicle. How to screen the health condition of short span bridges in terms of a drive-by bridge inspection is described. Feasibility of the drive-by bridge inspection is investigated through a scaled laboratory moving vehicle experiment. The feasibility of using an instrumented vehicle to detect the natural frequency and changes in structural damping of a model bridge was observed. Observations also demonstrated the possibility of diagnosis of bridges by comparing patterns of identified bridge dynamic parameters through periodical monitoring. It was confirmed that the moving vehicle method identifies the damage location and severity well.