Shm-based probabilistic fatigue life prediction for bridges based on fe model updating

Young Joo Lee, Soojin Cho

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

Abstract

Fatigue life prediction for a bridge should be based on the current condition of the bridge, and various sources of uncertainty, such as material properties, anticipated vehicle loads and environmental conditions, make the prediction very challenging. This paper presents a new approach for probabilistic fatigue life prediction for bridges using finite element (FE) model updating based on structural health monitoring (SHM) data. Recently, various types of SHM systems have been used to monitor and evaluate the long-term structural performance of bridges. For example, SHM data can be used to estimate the degradation of an in-service bridge, which makes it possible to update the initial FE model. The proposed method consists of three steps: (1) identifying the modal properties of a bridge, such as mode shapes and natural frequencies, based on the ambient vibration under passing vehicles; (2) updating the structural parameters of an initial FE model using the identified modal properties; and (3) predicting the probabilistic fatigue life using the updated FE model. The proposed method is demonstrated by application to a numerical model of a bridge, and the impact of FE model updating on the bridge fatigue life is discussed.

Original languageEnglish
Article number317
JournalSensors
Volume16
Issue number3
DOIs
StatePublished - 2 Mar 2016

Keywords

  • Bridge fatigue
  • Fatigue life prediction
  • Finite element model updating
  • Probabilistic fatigue life
  • Structural health monitoring

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