Smart Structures and Systems

Volume 33, Number 1, 2024, pages 17-26

DOI: 10.12989/sss.2024.33.1.017

A long-term tunnel settlement prediction model based on BO-GPBE with SHM data

Yang Ding , Yu-Jun Wei , Pei-Sen Xi , Peng-Peng Ang , Zhen Han

Abstract

The new metro crossing the existing metro will cause the settlement or floating of the existing structures, which will have safety problems for the operation of the existing metro and the construction of the new metro. Therefore, it is necessary to monitor and predict the settlement of the existing metro caused by the construction of the new metro in real time. Considering the complexity and uncertainty of metro settlement, a Gaussian Prior Bayesian Emulator (GPBE) probability prediction model based on Bayesian optimization (BO) is proposed, that is, BO-GPBE. Firstly, the settlement monitoring data are analyzed to get the influence of the new metro on the settlement of the existing metro. Then, five different acquisition functions, that is, expected improvement (EI), expected improvement per second (EIPS), expected improvement per second plus (EIPSP), lower confidence bound (LCB), probability of improvement (PI) are selected to construct BO model, and then BO-GPBE model is established. Finally, three years settlement monitoring data were collected by structural health monitoring (SHM) system installed on Nanjing Metro Line 10 are employed to demonstrate the effectiveness of BO-GPBE for forecasting the settlement.

Key Words

Bayesian emulator; Bayesian optimization; Gaussian prior; settlement probability prediction; structural health monitoring

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