The application discloses a
soil arching effect degradation rate prediction method based on a stratum characteristic curve, and aims at solving the problem that the
soil arching effect degradation caused by double-line tunnel excavation is difficult to quantitatively characterize. S1, discrete and parameter vectorization are carried out on the
monitoring data of the double active door test; S2, an analytical expression of the stratum characteristic curve above the left and right active
doors is constructed, and initial boundary conditions and limit stable boundary conditions are determined; S3, a physical guide neural network is constructed, the
network parameter iterative optimization is guided through a comprehensive
loss function, and optimal fitting parameters and an optimal analytical expression of the stratum characteristic curve are output; S4, the
soil arching effect degradation rate η is calculated and constructed, and the quantitative prediction of the degradation degree is completed. The dual guarantee of data fitting accuracy and physical
interpretability is realized, and the non-dimensional index of the output degradation rate fills the blank of the unified quantitative index of the soil arching effect degradation under secondary unloading, and can serve the stratum disturbance
risk assessment and
safety control of the double-line tunnel underpass project.