Evaluation of Seismic Performance of a Circular Reinforced Concrete Bridge Column Designed in Accordance With the Current Design Code Based on E-Defense Excitation

Kawashima, Kazhiko; Sasaki, Tomohiro; Ukon, Hiromichi; Kajiwara, Koichi; Unjoh, Shigeki; Sakai, Jyunichi; Kosa, Kenji; Takahashi, Yoshikazu; Yabe, Masaaki; Matsuzaki, Hisao

doi:10.2208/jsceja.66.324

Cited by 3 publications

(5 citation statements)

References 12 publications

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“…Te advantages of this study exist in the localization and quantifcation of nonlinear damages. Te DF reported in the previous study was about 5.6 based on the displacement of the pier top [44]. Tat DF was global.…”

Section: Pop-outmentioning

confidence: 72%

“…In practice, f m is not available because measuring forces is more difcult than measuring other physical quantities. Te applicability of load cells to high-frequency dynamic responses is not clear [44]. Strains may be converted to forces assuming dynamic properties of materials.…”

Section: Estimating Restoring Momentsmentioning

confidence: 99%

“…DF in this study is the ratio between the experienced maximum angle using the reproduced responses and yield angle using the estimated elastic stifness and yield moment. As a rule of thumb, the previous study indicated that DF < 1.2 is "intact," 1.2 < DF < 1.5 is "suspicious," and 1.5 < DF is "damaged" for the largest Japanese design seismic waves [3,44,45]. Tis study adopts the criteria.…”

Section: Evaluating the Condition Of A Piermentioning

confidence: 99%

“…All the responses were resampled to 100 Hz. Following the reference, the responses in horizontal directions were extracted and converted to responses in a principal direction [44]. Principal direction θ p � 196 °in case 1 and θ p � 196 °in case 2, almost directing west.…”

Section: Validation By Experimentsmentioning

confidence: 99%

“…Tis study adopts experimental data publicly ofered by Kawashima et al [44]. Te unique feature of this experiment, called E-Defense, is full-scale shaking table tests using an RC bridge pier following the recent Japanese standard (Figure 1).…”

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confidence: 99%

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A Physics‐Informed Neural Network for the Nonlinear Damage Identification in a Reinforced Concrete Bridge Pier Using Seismic Responses

Yamaguchi,

Mizutani

2024

Structural Control and Health Monitoring

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The condition assessment of reinforced concrete (RC) bridge piers after an earthquake using measured responses is important for ensuring the safety of road and railway users. The problem is nonlinear, and the locations and extents of damages are various. However, previous research works focused on linear structural identification or model updating assuming a limited number of nonlinear materials for reasonable estimates. Leveraging the ability of deep learning (DL) for robustly estimating a large number of unknown parameters, this study proposes an ALL nonlinear spring multi-degree-of-freedom (MDOF) damage identification algorithm based on a physics-informed neural network (PINN). The algorithm is applied to a stacked bilinear rotational spring and damper model of a pier. The number of unknown parameters reaches about 50. The errors of estimated elastic stiffnesses, damping coefficients, and ductility factors (DFs) using simulated responses added with noises are 0.4%, 0.6%, and 3.1%, respectively. Using full-scale RC bridge pier shaking table experiments, the algorithm revealed the distributions of elastic stiffnesses and DFs along the pier height and their deteriorations. The effects of different types of local damages are quantitatively evaluated and visualized on the distributions.

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Section: Pop-outmentioning

confidence: 72%

Section: Estimating Restoring Momentsmentioning

confidence: 99%

Section: Evaluating the Condition Of A Piermentioning

confidence: 99%

Section: Validation By Experimentsmentioning

confidence: 99%

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confidence: 99%

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