Bridge scour characteristic curve for natural frequency-based bridge scour monitoring using simulation-based optimization

This study addresses a key issue that prevents the wide application of the novel predominant natural frequency (PNF)-based method for bridge scour monitoring, which is also applicable to the frequency-based health monitoring of other structures with soil-structure interaction. This issue is that no theory or method is currently available to guide the prediction of scour depths based on measured PNFs. The most feasible way is to first measure a few scour depths and their corresponding PNFs for obtaining the PNF-scour depth relationship, which is termed the bridge scour characteristic curve (BSCC) in this study, and then use this BSCC to predict future scour depths with measured PNFs. This study provides a comprehensive investigation into the BSCC and proposes a simulation-based optimization approach, in which the whole BSCC, that is, from light to severe scour conditions, can be predicted with a few measured scour depth-PNF data points (e.g., 2-4) within a small scour depth range (e.g., 0.2-0.5 m). The proposed approach integrates the Winkler-based numerical model into a global optimization technique to predict the whole BSCC to avoid the use of a closed-form BSCC function, which may not exist. Additionally, the approach can be used to estimate the modulus of subgrade reaction, which is very hard to obtain at real bridges. The performance of the proposed approach was evaluated using several practical scenarios with realistic multilayered soil conditions. We found that the proposed approach is accurate for predicting the whole BSCC with four measured points or even less, regardless of the scour severity for the measurements and the number of the soil layer. For applications, the influence of random errors in the measurements of PNFs and scour depths was investigated and concluded to be negligible. This study sets a solid cornerstone for the maturation of the PNF-based scour monitoring method and other frequency-based structural health monitoring methods with soil-structure interaction.

Automated summary

This study introduces a novel method for bridge scour monitoring based on predominant natural frequency (PNF), allowing the prediction of the bridge scour characteristic curve (BSCC) using a few measured scour depth-PNF data points and estimation of the modulus of subgrade reaction. The proposed approach accurately predicts the whole BSCC in realistic scenarios and lays a solid foundation for frequency-based structural health monitoring methods.