Structural Identification of a 52-Story High-Rise in Downtown Los Angeles Based on Short-Term Wind Vibration Measurements

Abdelbarr, Mohamed; Kohler, Monica D.; Masri, Sami F.

doi:10.1061/jsendh.steng-11111

Cited by 3 publications

(7 citation statements)

References 46 publications

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“…39 To identify stable modes, the stabilization diagram is frequently adopted and has evolved into a general post-processing procedure in the modal analysis. 40 Various validation indexes have been proposed to separate spurious modes in the stabilization diagram, 41,42 in which two indicators with good distinguishing performance, that is, modal complexity index (MCI) 43,44 and consistent mode indicator (CMI), 6,45,46 are adopted in this study as the validation criteria:…”

Section: Modal Estimation With Uncertainty By Improved Eramentioning

confidence: 99%

“…Field observations on prototype large‐scale civil structures have been recognized as the sole dependable means to determine the dynamic properties of such structures under operational conditions because actual dynamic behaviors are retrieved directly from existing structures 3,4 . Although several field measurement studies on high‐rise buildings under ambient excitations have been performed recently, such investigations are rarely redundant but valuable since they can provide insights into the dynamic performance of large‐scale structures such as supertall buildings under various excitation and operating states 5,6 …”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, the RDT usually requires a long enough response measurement duration to obtain reliable RDS since a sufficient number of segments are needed for its sample averaging step, while the NExT can realize this with a relatively short response duration 1,19 . Thus, the NExT‐driven method is typically used to evaluate the time‐variant features of large‐scale structures subjected to extreme events by applying it to each short time window and sliding the time window to traverse the measured data 6,20,21 . While, for large‐scale structures subjected to harsh excitations like typhoons or earthquakes, their structural modal properties usually exhibit time‐varying features and amplitude‐dependent nonlinearities 2,4 .…”

Section: Introductionmentioning

confidence: 99%

“…ambient excitations have been performed recently, such investigations are rarely redundant but valuable since they can provide insights into the dynamic performance of large-scale structures such as supertall buildings under various excitation and operating states. 5,6 Various attempts have been made to infer the dynamic properties of engineering structures from field measurements of structural responses, thus yielding a series of operational modal analysis (OMA) techniques. [7][8][9][10] Among these techniques, the eigensystem realization algorithm (ERA)based methods have been frequently applied to evaluate the modal properties of civil structures on account of their excellent noise robustness and accuracy.…”

mentioning

confidence: 99%

“…1,19 Thus, the NExT-driven method is typically used to evaluate the time-variant features of large-scale structures subjected to extreme events by applying it to each short time window and sliding the time window to traverse the measured data. 6,20,21 While, for large-scale structures subjected to harsh excitations like typhoons or earthquakes, their structural modal properties usually exhibit time-varying features and amplitude-dependent nonlinearities. 2,4 Thus, it is necessary to combine the advantages of the NExT and RDT techniques to develop a hybrid modal identification method, aiming to effectively evaluate the modal parameters of large-scale structures and their variations under severe excitation conditions (e.g., typhoons) from multiple perspectives.…”

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confidence: 99%

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Modal identification with uncertainty quantification of large‐scale civil structures via a hybrid operation modal analysis framework

Sun,

2024

Structural Design Tall Build

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SummaryIn operational modal analysis (OMA), only structural responses are typically available. In this context, bias and variance (uncertainty) errors may exist in modal estimates (especially damping estimates), resulting in inaccurate determination of the modal properties of large‐scale structures under harsh excitations. To this end, a hybrid OMA framework based on the modal decoupling, the natural excitation technique, the random decrement technique (RDT), and improved eigensystem realization algorithm (ERA) with the automated stabilization diagram is presented to perform high‐accuracy modal estimates with uncertainty quantification for large‐scale structures under normal and severe ambient excitations. The accuracy and effectiveness of the hybrid framework for identifying the modal parameters are validated by numerical simulation study of a framework structural model. Furthermore, the hybrid framework is applied to analyze recorded acceleration responses of a supertall building with 600‐m height under normal excitations and typhoon condition to verify its applicability in field measurements. The numerical simulation and field measurement studies demonstrate that the hybrid framework can not only perform precise modal estimations with uncertainty quantification through a single ambient vibration measurement but also effectively reveal the variations of modal properties of supertall structures under harsh excitations from multiple perspectives. This paper aims to enhance the reliability and accuracy of modal estimation for engineering structures and further provide insight into the variations of dynamic properties of large‐scale civil structures under severe excitations.

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Section: Modal Estimation With Uncertainty By Improved Eramentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Modal identification with uncertainty quantification of large‐scale civil structures via a hybrid operation modal analysis framework

Sun,

2024

Structural Design Tall Build

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Bayesian Operational Modal Analysis with Interactive Optimization for Model Updating of Large-Size UHV Transmission Towers

Zhu,

Sun,

Zhao

et al. 2023

J. Struct. Eng.

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LSTM‐Based Approach for Stable Identification of Modal Damping Ratio in Building Structures

Yun,

Oh,

Park

et al. 2024

Structural Control and Health Monitoring

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Modal parameters are used as safety assessment indicators for evaluating the structural integrity of buildings in various ways. In particular, the modal damping ratio plays a crucial role in accurately predicting the serviceability and safety of buildings, starting from the initial design stage. However, the identification results of the modal damping ratio can become unstable due to measurement time, initial configuration conditions used in the analysis, and nonstationary responses included in the structural response. To address the instability issue, this study proposes a long short-term memory-based frequency domain decomposition (FDD-LSTM) method. The FDD-LSTM method utilizes the acceleration response of the building as input data and the modal damping ratio obtained from the FDD method as output data, constructing an LSTM network model for the relationship between the acceleration response and modal damping ratio. The FDD-LSTM method exhibited a discrepancy of less than 0.02% compared to the reference value of the modal damping ratio obtained through free vibration response. Furthermore, when applied to data acquired from an actual building, the method demonstrated a variance of approximately 5%. The proposed FDD-LSTM method is validated for stability performance using a three-degree-of-freedom numerical analysis model, a 3-story steel frame structure model, and a 117-story high-rise building. The FDD-LSTM method, trained on a large dataset, enables generalized estimation and addresses instability issues related to modal damping ratio.

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Structural Identification of a 52-Story High-Rise in Downtown Los Angeles Based on Short-Term Wind Vibration Measurements

Cited by 3 publications

References 46 publications

Modal identification with uncertainty quantification of large‐scale civil structures via a hybrid operation modal analysis framework

Modal identification with uncertainty quantification of large‐scale civil structures via a hybrid operation modal analysis framework

Bayesian Operational Modal Analysis with Interactive Optimization for Model Updating of Large-Size UHV Transmission Towers

LSTM‐Based Approach for Stable Identification of Modal Damping Ratio in Building Structures

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