Abstract

By virtue of the advances in sensing techniques, finite element (FE) model updating (FEMU) using static and dynamic data has been recently employed to improve identification on updating parameters. Using heterogeneous data can provide useful information to improve parameter identifiability in FEMU. It is worth noting that the useful information from the heterogeneous data may be diluted in the conventional FEM framework. The conventional FEMU framework in previous studies have used heterogeneous data at once to compute residuals in the objective function, and they are condensed to be a scalar. In this implementation, it should be careful to formulate the objective function with proper weighting factors to consider the scale of measurement and relative significances. Otherwise, the information from heterogeneous data cannot be efficiently utilized. For FEMU of the bridge, parameter compensation may exist due to mutual dependence among updating parameters. This aggravates the parameter identifiability to make the results of the FEMU worse. To address the limitation of the conventional FEMU method, this study proposes a sequential framework for the FEMU of existing bridges. The proposed FEMU method uses two steps to utilize static and dynamic data in a sequential manner. By using them separately, the influence of the parameter compensation can be suppressed. The proposed FEMU method is verified through numerical and experimental study. Through these verifications, the limitation of the conventional FEMU method is investigated in terms of parameter identifiability and predictive performance. The proposed FEMU method shows much smaller variabilities in the updating parameters than the conventional one by providing the better predictions than those of the conventional one in calibration and validation data. Based on numerical and experimental study, the proposed FEMU method can improve the parameter identifiability using the heterogeneous data and it seems to be promising and efficient framework for FEMU of the existing bridge.

Highlights

  • Structural deterioration under external conditions degrades the performance of the bridge along with time

  • The main contributions of this study are summarized as follows: (1) this study shows the limitation of using all heterogeneous data at once under parameter compensation in FE model updating (FEMU) of the bridge and (2) a sequential FEMU method using two-step is proposed to overcome the limitation and improve parameter identifiability

  • The main contributions of this study are summarized as follows: (1) this study shows the limitation of using all heterogeneous data at once parameter compensation in FEMU of the bridge and (2) a sequential FEMU method using

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Summary

Introduction

Structural deterioration under external conditions (e.g., traffic loading) degrades the performance of the bridge along with time. The main contributions of this study are summarized as follows: (1) this study shows the limitation of using all heterogeneous data at once under parameter compensation in FEMU of the bridge and (2) a sequential FEMU method using two-step is proposed to overcome the limitation and improve parameter identifiability. Inis the numerical study and experimental study using field data, compensation in FEMU can be addressed and the useful information from the heterogeneous data proposed. In thewas numerical study andthe experimental studyfor using field data, the proposed proposed method evaluated with existing FEMU heterogeneous data The results of the FEMU are significantly improved with consistent method was evaluated with the existing for heterogeneous data (modal and static data).

Research
Heterogeneous
Measurementprocedures procedures for for aa dynamic
Conventional
Validity evaluation of the updated FE model using validation data
Proposed FE Model Updating Using Sequential Framework
Numerical Verification
Preliminary Work for FE Model Updating
Numerical using the the FE
FE Model Updating for Numerical Verification
Target Bridge and Field Experiment
Rotation angles and deflections
Preliminary Work for Experimental Verification
FE Model Updating for Field Experimental Verification
Findings
Conclusions
Full Text
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