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A Sequential Framework for Improving Identifiability of FE Model Updating using Static and Dynamic Data.

Sehoon Kim1, Namgyu Kim2, Young-Soo Park3

  • 1Research Institute for Infrastructure Performance, Korea Infrastructure Safety & Technology Corporation, Jinju 52856, Korea.

Sensors (Basel, Switzerland)
|November 27, 2019
PubMed
Summary

A new sequential framework improves finite element model updating (FEMU) for bridges by using static and dynamic data separately. This method enhances parameter identifiability and predictive performance, overcoming limitations of conventional approaches.

Keywords:
finite element model updatingheterogeneous dataparameter compensationparameter identifiabilitysequential framework

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Area of Science:

  • Structural Engineering
  • Computational Mechanics
  • Bridge Engineering

Background:

  • Finite Element Model Updating (FEMU) uses sensing techniques and heterogeneous data (static and dynamic) to refine structural parameters.
  • Conventional FEMU frameworks often dilute information from heterogeneous data and suffer from parameter compensation, hindering accurate identification.

Purpose of the Study:

  • To propose a novel sequential framework for FEMU of existing bridges.
  • To address limitations in parameter identifiability and predictive performance associated with conventional FEMU methods.

Main Methods:

  • A two-step sequential approach is introduced to utilize static and dynamic data separately.
  • This sequential utilization aims to suppress the influence of parameter compensation inherent in updating multiple parameters.

Main Results:

  • The proposed sequential FEMU method demonstrated significantly smaller variabilities in updating parameters compared to conventional methods.
  • Improved predictive performance was observed for both calibration and validation data sets.

Conclusions:

  • The sequential FEMU framework effectively improves parameter identifiability by leveraging heterogeneous static and dynamic data.
  • The proposed method offers a promising and efficient approach for the FEMU of existing bridges, enhancing accuracy and reliability.