Data‐driven identification and modeling of earthquake‐excited building structures regarding soil‐structure interaction

Gong, Nan; Li, Peizhen; Shan, Jiazeng; Ouyang, Yuting

doi:10.1002/tal.1808

Cited by 5 publications

(5 citation statements)

References 45 publications

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“…As mentioned by Shan et al, 14 a non-uniform assumption may lead to a better fitting result, but it may overfit the model. 1,16 Moreover, the energy dissipation inherent in the building is captured by the Rayleigh damping, which can be characterized by the damping ratios of ξ 1 and ξ 2 at certain specified frequencies. Overall, the model vector that parameterizes the FE model can be denoted as p ¼ EI GA s ξ 1 ξ 2 ½ : 14 For the sake of simplicity, this study assumes that the FE model is initially at rest prior to earthquake excitations.…”

Section: A Lumped-mass Timoshenko-beam Rayleigh Damping Fe Modelmentioning

confidence: 99%

“…With this assumption, the flexural rigidity

italicEI

and the shear rigidity

G A_{s}

of the Timoshenko beams could be reasonably considered as constants along the building height. As mentioned by Shan et al, 14 a non‐uniform assumption may lead to a better fitting result, but it may overfit the model 1,16 . Moreover, the energy dissipation inherent in the building is captured by the Rayleigh damping, which can be characterized by the damping ratios of

ξ_{1}

and

ξ_{2}

at certain specified frequencies.…”

Section: Model Updatingmentioning

confidence: 99%

“…The accuracy and robustness of the updated FE model are affected by the modeling method, the spatial distribution of sensor allocation, the measurement noise, and the selection of an objective function 15,16 . The modeling method determines how well the FE model can simulate the real behavior of the structure.…”

Section: Introductionmentioning

confidence: 99%

“…14 The accuracy and robustness of the updated FE model are affected by the modeling method, the spatial distribution of sensor allocation, the measurement noise, and the selection of an objective function. 15,16 The modeling method determines how well the FE model can simulate the real behavior of the structure. There are always modeling errors due to a lack of understanding of the exact boundary conditions and the geometrical and material nonlinearity of the structure.…”

mentioning

confidence: 99%

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Model updating of a shear‐wall tall building using various vibration monitoring data: Accuracy and robustness

Shan,

Zhuang,

Chao

et al. 2024

Structural Design Tall Build

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SummaryAcceleration measurements are often used for model updating of civil engineering structures, especially in the case of seismic monitoring. It is yet unclear if accelerations alone would generate an accurate and robust finite‐element (FE) model. This study examines this notion and analyzes the possibility of using other vibration monitoring data for model updating of shear‐wall tall buildings. This study compares the accuracy and robustness of the FE models being optimized via accelerations, roof displacement, wall rotations, interstory drift ratios, and the linear combination of these measurements. A numerical case study is analyzed using Timoshenko beams for modeling the lateral vibration of a benchmark 42‐story building under seismic excitations. Results show that the acceleration response of the examined building is mostly governed by its higher vibration modes. Depending on the characteristics of ground motions, using accelerations alone may generate an FE model biased towards higher‐order modes without effectively capturing the lower‐order modes. For instance, the first modal frequency of the updated FE model could be 12.0% lower than the true value, and the reconstructed displacement and rotation responses are noticeably inaccurate. Employing multi‐source monitoring data for model updating, for example, the combinations of roof displacement and acceleration measurements, could reduce the normalized root‐mean‐square errors in displacements by more than 70%. This study also quantifies the robustness of the FE model under various measurement noise levels and 50 pairs of earthquake records. Finally, the effects of multi‐source data on FE model updating are validated via experiments on a 7‐story shear wall building. Analysis reveals that a more accurate and robust FE model can be determined via a combination of accelerations and top displacement than via acceleration alone.

show abstract

Section: A Lumped-mass Timoshenko-beam Rayleigh Damping Fe Modelmentioning

confidence: 99%

“…With this assumption, the flexural rigidity

italicEI

and the shear rigidity

G A_{s}

ξ_{1}

and

ξ_{2}

at certain specified frequencies.…”

Section: Model Updatingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Model updating of a shear‐wall tall building using various vibration monitoring data: Accuracy and robustness

Shan,

Zhuang,

Chao

et al. 2024

Structural Design Tall Build

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the last decades, modal identification techniques have achieved considerable development. Modal parameters (natural frequencies, mode shapes, and damping ratios), which completely capture the dynamic properties of a vibration system, can be extracted from measured data through modal identification techniques 1 . Some traditional modal identification methods require both the input and output information of the system.…”

Section: Introductionmentioning

confidence: 99%

Modal identification of non‐classically damped structures using generalized sparse component analysis

Yao,

Yi,

et al. 2024

Structural Design Tall Build

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SummaryModal identification method based on blind source separation (BSS) technique has gained extensive attentions for civil structures. Developing the complex modes estimation method is important in practical applications because the assumption of proportional damping is not always satisfied. Sparse component analysis (SCA) performs well in underdetermined BSS problems. However, SCA is confined to the situation of proportional damping. In this study, a generalized SCA method is proposed to extend the original SCA method to both real and complex modes identification. First, the general formulation of complex modes is extended by the analytic form to eliminate the complex conjugate part in the BSS model. A new single‐source‐point detection method that is available to handle real and complex modes is proposed. Local outlier factor method is adopted to remove the outliers in single source points. Subsequently, complex‐valued modal matrix is calculated by the clustering technique. Then, modal responses are recovered using the complex version of smoothed zero norm method, where modal frequencies and damping ratios can be extracted. Finally, the effectiveness of the proposed method is demonstrated for identification of real and complex modes, close modes, and underdetermined problem. The application to a benchmark structure demonstrates the effectiveness for practical applications.

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Parametric identification of Timoshenko-beam model for shear-wall structures using monitoring data

Shan

Zhuang

Loong

2023

Mechanical Systems and Signal Processing

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Data‐driven identification and modeling of earthquake‐excited building structures regarding soil‐structure interaction

Cited by 5 publications

References 45 publications

Model updating of a shear‐wall tall building using various vibration monitoring data: Accuracy and robustness

Model updating of a shear‐wall tall building using various vibration monitoring data: Accuracy and robustness

Modal identification of non‐classically damped structures using generalized sparse component analysis

Parametric identification of Timoshenko-beam model for shear-wall structures using monitoring data

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