Seismic fragility analysis of shear-critical concrete columns considering corrosion induced deterioration effects

Xu, Ji‐Gang; Wu, Gang; Feng, Decheng; Cotsovos, Demetrios M.; Lu, Yong

doi:10.1016/j.soildyn.2020.106165

Cited by 34 publications

(21 citation statements)

References 50 publications

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“…Fan et al [ 12 ] established a fragility analysis framework for RC bridge structures subjected to the multi-hazard effect of vessel collisions and corrosion. Meanwhile, the modeling and analysis of the time-dependent seismic fragility due to the corrosion effects of RC bridges has received significant attention [ 13 , 14 , 15 , 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

“…According to China’s Ministry of Transportation, the aging and deterioration phenomenon of MSC concrete girder bridges are commonly found in seismic zones, such as northern China, because deicing salts are extensively used on highway bridges [ 24 ]. The existing contributions [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ] also indicated that RC bridges subjected to the mechanisms of corrosion deterioration might be more vulnerable to earthquake hazards. Moreover, since previous studies [ 25 , 26 ] demonstrated that chloride from deicing salts can cause more degradation of bridges than that in a marine environment, the impacts of corrosion degradation due to chloride-laden deicing salts should be researched in detail.…”

Section: Introductionmentioning

confidence: 99%

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Time-Dependent Seismic Fragility of Typical Concrete Girder Bridges under Chloride-Induced Corrosion

et al. 2022

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Recent studies highlighted the importance of the combined effects of prestress loss and corrosion deterioration for concrete girder bridge structures when the effect of damage on the performance level is estimated. The multi-deterioration mechanisms connected with chloride erosion include the cross-sectional area loss of longitudinal bars and stirrups, the reduction in the ductility, the decrease in the strength of steels and the strength loss of concrete in RC columns. For the corroded RC columns and corroded elastomeric bridge bearings, analytical models of the material degradation phenomena were employed for performing the probabilistic seismic performance analysis, which could obtain the system seismic fragility of aging bridges by considering the failure functionality of multiple correlated components (e.g., columns, bearings). The combined effects of prestress loss and cracking were also considered when developing time-dependent system seismic fragility functions. Here, a typical multi-span reinforced concrete girder bridge was used as a case study for studying the time-variant seismic performance. The results revealed the importance of the joint effects of the multi-deterioration mechanisms when modeling the time-dependent seismic fragility of aging bridge systems, as well as the significance of considering the combined effects of prestress loss and cracking.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Time-Dependent Seismic Fragility of Typical Concrete Girder Bridges under Chloride-Induced Corrosion

et al. 2022

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“…Traditional seismic fragility curves based on a scalar intensity measure (IM) have been widely used to generate fragility estimates in earthquake events (Hwang et al, 2001;Baker and Cornell, 2005;Cimellaro et al, 2010;Xu et al, 2020a). Although they are affected by geometry and material uncertainties, seismic fragility estimates are dominated by the earthquake uncertainty (Kwon and Elnashai, 2006;Padgett and DesRoches, 2007;Jalayer et al, 2014;Mangalathu et al, 2018;Xie et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Encoding Time-Series Ground Motions as Images for Convolutional Neural Networks-Based Seismic Damage Evaluation

Yuan

Tanksley

Jiao

et al. 2021

Front. Built Environ.

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Traditional methods for seismic damage evaluation require manual extractions of intensity measures (IMs) to properly represent the record-to-record variation of ground motions. Contemporary methods such as convolutional neural networks (CNNs) for time series classification and seismic damage evaluation face a challenge in training due to a huge task of ground-motion image encoding. Presently, no consensus has been reached on the understanding of the most suitable encoding technique and image size (width × height × channel) for CNN-based seismic damage evaluation. In this study, we propose and develop a new image encoding technique based on time-series segmentation (TS) to transform acceleration (A), velocity (V), and displacement (D) ground motion records into a three-channel AVD image of the ground motion event with a pre-defined size of width × height. The proposed TS technique is compared with two time-series image encoding techniques, namely recurrence plot (RP) and wavelet transform (WT). The CNN trained through the TS technique is also compared with the IM-based machine learning approach. The CNN-based feature extraction has comparable classification performance to the IM-based approach. WT 1,000 × 100 results in the highest 79.5% accuracy in classification while TS 100 × 100 with a classification accuracy of 76.8% is most computationally efficient. Both the WT 1,000 × 100 and TS 100 × 100 three-channel AVD image encoding methods are promising for future studies of CNN-based seismic damage evaluation.

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“…The degradation of the mechanical properties of both steel bars and concrete comprises several corrosion effects that reduce the seismic performance levels of the corroded reinforced concrete (RC) members. Therefore, analytical and empirical models have been widely developed to predict the mechanical properties of corroded bars, 1,2 time to cracking of concrete, [3][4][5] bond-slip relationships, [6][7][8] probabilistic service life prediction of corroded RC members, [9][10][11] effects of corrosion on the structural capacity of concrete members by considering either uniform or pitting corrosion, [12][13][14][15] and corrosion repair techniques. 16,17 However, in situ data collections by considering all the effects of corrosion are complex.…”

Section: Introductionmentioning

confidence: 99%

An experimental study on seismic performance levels of highly corroded reinforced concrete columns

Çelik

Yalçıner

Kumbasaroğlu

et al. 2021

Structural Concrete

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In the literature, only one empirical model is available as a nondestructive method for the prediction of seismic performance levels of corroded reinforced concrete (RC) columns as a function of the initial corrosion crack width at lower corrosion levels. Because of the ruptured transverse reinforcement bars at higher corrosion levels, the structural behavior may turn brittle in terms of shear failure. Therefore, in this study, higher corrosion levels for a different concrete strength level from that empirical model were studied. To do this, four RC columns were subjected to accelerated corrosion, and the widths of initial corrosion cracks were measured. The corroded RC columns were then tested under combined constant axial load and cyclic lateral displacement excursions. After the cyclic loading test, the actual corrosion levels at each reinforcement bar were obtained by extracting the reinforcement bars from the concrete. Test results showed that the prediction of seismic performance levels of corroded RC columns based on initial corrosion crack widths were limited owing to the nonlinear increase in the crack width with the increase in the corrosion levels. New empirical models were developed to predict the remaining energy capacities and seismic performance levels of the corroded RC columns.

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Seismic fragility analysis of shear-critical concrete columns considering corrosion induced deterioration effects

Cited by 34 publications

References 50 publications

Time-Dependent Seismic Fragility of Typical Concrete Girder Bridges under Chloride-Induced Corrosion

Time-Dependent Seismic Fragility of Typical Concrete Girder Bridges under Chloride-Induced Corrosion

Encoding Time-Series Ground Motions as Images for Convolutional Neural Networks-Based Seismic Damage Evaluation

An experimental study on seismic performance levels of highly corroded reinforced concrete columns

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