An early warning method for tunneling-induced ground surface settlement considering accident precursors and consequences

Guo, Yifan; Zheng, Jian; Liu, Hui

doi:10.1016/j.tust.2023.105214

Cited by 1 publication

(1 citation statement)

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“…Based on the research results in the literature [31,61,62], the tunnel displacement monitoring criterion is constructed through the ∆α and ∆ f (α) parameters derived from the tunnel displacement monitoring data in order to realize the tunnel displacement warning level classification. The specific criteria are set as shown in Table 3.…”

Section: Tunnel Deformation Warning Level Classification Criteriamentioning

confidence: 99%

Analysis and Warning Prediction of Tunnel Deformation Based on Multifractal Theory

Yang,

Huang,

Liu

et al. 2024

Fractal Fract

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To better analyze the fluctuation characteristics and development law of tunnel deformation data, multifractal theory is applied to tunnel deformation analysis. That is, the multifractal detrended fluctuation analysis (MF-DFA) model is first utilized to carry out the multifractal characterization of tunnel deformation data. Further, Mann–Kendall (M–K) analysis is utilized to construct the dual criterion (∆α indicator criterion and ∆f(α) indicator criterion) for the tunnel deformation early warning study. In addition, the particle swarm optimization long-short-term memory (PSO-LSTM) prediction model is used for predicting tunnel settlement. The results show that, in reference to the tunnel warning level criteria and based on the Z-value results of the indicator criterion, the warning level of all four sections is class II. At the same time, through the analysis of tunnel settlement predictions, the PSO-LSTM model has a better prediction effect and stability for tunnel settlement. The predicted results show a slow increase in tunnel settlement over the next 5 days. Finally, the tunnel warning level and the predicted results of tunnel settlement are analyzed in a comprehensive manner. The deformation will increase slowly in the future. Therefore, monitoring and measurement should be strengthened, and disaster preparedness plans should be prepared.

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Section: Tunnel Deformation Warning Level Classification Criteriamentioning

confidence: 99%