Safety assessment and Long short-term memory-Attention-based deformation prediction for existing tunnels during shield tunnelling undercrossing

Abstract

As underground space continues to be developed, tunnels are inevitably affected by new tunnel construction, threatening operational safety. This study adopts numerical simulation to study the longitudinal response of existing tunnels under different spatial positions and evaluate the tunnel safety of bearing capacity. Then, based on measured data, a long short-term memory (LSTM)-Attention model was developed as a predictive model for safety control throughout the construction process. The importance of tunnelling parameters was quantified, and their dynamic nonlinear influence mechanisms revealed. Results show that there are complex coupling effects during the construction of the new twin tunnels, and the LSTM-Attention model achieves 96.42% prediction accuracy for invert deformation prediction. The main tunnelling parameters (chamber pressure (CY), propulsion speed (SP), and synchronous grouting volume (ZJ)) exhibit strong interaction effects (0.8), while the distance between the tunnel face and the monitoring point (DS) exhibits weaker interaction effects (0.3). The total sensitivity index for input parameters is approximately 0.8, with the order DS > CY > ZJ > SP. In practical tunnel undercrossing projects, the CY should be prioritized during the construction stage, with coordinated adjustments to other parameters to ensure tunnel safety.

Graphical abstract

Keywords

shield tunnel undercrossing / structural safety / LSTM-Attention-based model / tunnel deformation prediction / tunnelling parameters

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The Author(s). This article is published with open access at link.springer.com and journal.hep.com.cn