Seismic performance of circular reinforced concrete columns subjected to compression, bending and torsion with low and moderate shear span ratio

Jiao, Chiyu; Liu, Yang; Wei, Biao; Li, Jianzhong; Hu, Zhangliang; Zhu, Gexi

doi:10.1007/s43452-021-00282-8

Cited by 4 publications

(5 citation statements)

References 18 publications

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“…The premise of the condition assessment is to accurately evaluate the post‐earthquake damage to bridge structures. For assessing post‐earthquake damage to bridges, the bridge column is the critical component that affects the safety performance of the whole bridge 27–29 . The types of post‐earthquake damage to the column can be mainly divided into shear damage, bending damage, and torsional damage.…”

Section: Methodsmentioning

confidence: 99%

“…For assessing post-earthquake damage to bridges, the bridge column is the critical component that affects the safety performance of the whole bridge. [27][28][29] The types of post-earthquake damage to the column can be mainly divided into shear damage, bending damage, and torsional damage. Therefore, it is necessary to assess the damage type of the column according to the principal direction of the damage and then evaluate the related damage.…”

Section: Post-earthquake Assessment Of the Safety Risk Level Of Bridgesmentioning

confidence: 99%

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Post‐earthquake damage recognition and condition assessment of bridges using UAV integrated with deep learning approach

Liu

et al. 2022

Structural Contr & Hlth

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Rapid and accurate assessment of the damage to bridge structures after an earthquake can provide a basis for decision-making regarding post-earthquake emergency work. However, the traditional structural damage inspection techniques are subjective, time-consuming, and inefficient. This paper proposed a framework for rapid post-earthquake structural damage inspection and condition assessment by integrating the technologies of satellite, unmanned aerial vehicle (UAV), and smartphone with the deep learning approach. The images of structural components of post-earthquake bridges can be obtained by UAVs and smartphones. Furthermore, the multi-task high-resolution net (MT-HRNet) model was adopted to recognize the structural components and damage conditions by weighting and combining the loss functions of a single-task HRNet model. The performance of the proposed MT-HRNet model and the single-task HRNet model was verified based on the Tokaido dataset, which includes 2000 images of post-earthquake bridges. The results showed that the MT-HRNet model and the HRNet model exhibited equivalent recognition accuracy, while the number of floating-point-operations (FLOPs) and the parameters of the MT-HRNet model were reduced by 46.48% and 49.58% compared with the HRNet model. In addition, a method for the determination of the safety risk level of the post-earthquake bridge structures was developed, and the evaluation indices were established by considering the damage type, the spalling area, and the width of cracks as well as the recognition statistics of all images in Tokaido dataset. This study will provide a valuable reference for the rapid determination of structural safety level and the corresponding treatment measures of post-earthquake bridges.

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Section: Methodsmentioning

confidence: 99%

Section: Post-earthquake Assessment Of the Safety Risk Level Of Bridgesmentioning

confidence: 99%

Post‐earthquake damage recognition and condition assessment of bridges using UAV integrated with deep learning approach

Liu

et al. 2022

Structural Contr & Hlth

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“…For deep‐buried stations, the soil arch effects prevented further increases in vertical compressions applied to subway stations as the buried depth increased 42 . The gravity analyses indicated that the soil arch did not form in the shallow‐buried station models, which had a maximum buried depth of 4.8 m. The medium or high shear span‐to‐depth ratio would weaken the influence of the shear effect, which led to the flexural failure rather than the shear failure of columns 43 . For safety reasons, columns of a relatively high shear span‐to‐depth ratio were designed to ensure the ductile rather than brittle failure of column specimens.…”

Section: Numerical Modeling Of Station and Soil Domainmentioning

confidence: 98%

“…42 The gravity analyses indicated that the soil arch did not form in the shallow-buried station models, which had a maximum buried depth of 4.8 m. The medium or high shear span-to-depth ratio would weaken the influence of the shear effect, which led to the flexural failure rather than the shear failure of columns. 43 For safety reasons, columns of a relatively high shear span-to-depth ratio were designed to ensure the ductile rather than brittle failure of column specimens. The shear span-to-depth ratio of tested columns was prescribed as 7.25.…”

Section: Model Descriptionmentioning

confidence: 99%

Effects of axial compression ratio on seismic behavior of shallow‐buried rectangular stations: Hybrid simulation and quasi‐static test

Cai,

Yang,

Liu

et al. 2024

Earthq Engng Struct Dyn

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In the absence of experimental investigations on column members of underground structures, full‐scale column specimens were tested to explore the seismic behavior of shallow‐buried subway stations at various depths. The axial compression ratios of internal column specimens were set as 0.16, 0.33, and 0.40. Both hybrid simulations and quasi‐static tests were performed on the station columns. The hybrid simulations illustrated the drift demands of internal columns, while the load‐carrying capacity and deformation capacity were obtained from the quasi‐static tests. Hybrid simulations at low, moderate, and high‐intensity levels were conducted to study the seismic responses of shallow‐buried rectangular stations. The hybrid simulations suggest that the most severe damage occurred in the station when the axial compression ratio of the tested column reached 0.40. Central columns suffered severe stiffness deterioration under high‐level earthquake excitation, especially in stations at greater depths. Meanwhile, the quasi‐static test results indicate that the ultimate load of the central columns increases with increasing axial compression, but this leads to a significant decrease in the ductility of columns. Besides, the sectional analysis results show that the central columns are prone to tension‐controlled failure, and the safety margin for flexural response deteriorates with an increasing axial compression ratio. The test results indicate that shallow‐buried rectangular stations are susceptible to flexure‐controlled structural failure when their central columns possess a relatively low axial compression ratio and a high shear span‐to‐depth ratio. The failure mechanism of station columns is revealed by both the hybrid simulations and quasi‐static tests, and the findings from the full‐scale tests are beneficial for the practical design of shallow‐buried rectangular stations.

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“…Many methodologies and applications regarding the seismic assessment of existing RC buildings can be found in the national and international literature, aiming to investigate the different problematic aspects of this task, such as the choice of the proper modeling strategy and analysis methodology [1][2][3][4][5] and the consideration of the different source of uncertainties in the modeling phase [6][7][8]. Moreover, different studies evaluate the structural damage in the existing RC structures as consequence of displacements induced by landslides [9][10][11][12][13] or other hazard sources, such as subsidence [14,15], ground consolidation [16], mining activities [17], excavations [18], and variations in the temperature distribution in the structural elements [19], monitored through satellite data for consistent time intervals.…”

Section: Introductionmentioning

confidence: 99%

Potential of remote sensing data to support the seismic safety assessment of reinforced concrete buildings affected by slow-moving landslides

Mele

Miano

Martire

et al. 2022

Archiv.Civ.Mech.Eng

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Different forms of hazard can affect structures throughout their existence. The occurrence of a seismic event in areas exposed to different risks or already affected by other phenomena is highly likely, especially in countries characterized by high seismicity and equally high hydrogeological risk, as Italy. Nevertheless, the seismic safety assessment of reinforced concrete (RC) structures is commonly carried out considering the seismic action only, generally applied to an analytical model, neglecting the stress–strain state induced by previous ongoing phenomena. The aim of this work is to highlight the importance of the seismic safety assessment in a multi-hazard analysis, cumulating the action coming from two different hazards: landslide and earthquake. An existing RC building, located in an area affected by an intermittent landslide phenomenon with slow kinematics, that may also be subjected to strong earthquakes, is used as case study. The Differential Synthetic Aperture Radar Interferometry (DInSAR) approach is used to monitor the evolution in time of the landslide. DInSAR deformation data are used to detect surface ground movements applied to building foundations. A non-linear static analysis procedure is implemented for the code-based seismic safety assessment, in two different scenarios. The seismic assessment of the case-study building is implemented in a condition of structure deformed only for gravity loads, and, then, in a state of known landslide-induced deformed configuration. A comparison is proposed between the building seismic safety assessment performed in both cases, with or without the consideration of the landslide-induced displacements, showing the importance of a multi-hazard evaluation.

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Seismic performance of circular reinforced concrete columns subjected to compression, bending and torsion with low and moderate shear span ratio

Cited by 4 publications

References 18 publications

Post‐earthquake damage recognition and condition assessment of bridges using UAV integrated with deep learning approach

Post‐earthquake damage recognition and condition assessment of bridges using UAV integrated with deep learning approach

Effects of axial compression ratio on seismic behavior of shallow‐buried rectangular stations: Hybrid simulation and quasi‐static test

Potential of remote sensing data to support the seismic safety assessment of reinforced concrete buildings affected by slow-moving landslides

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