A New Dynamic Prediction Model for Underground Mining Subsidence Based on Inverse Function of Unstable Creep

Abstract

In this study, an improved Knothe time function model is established via analogical reasoning from a phenomenological perspective, based on an inverse “Hohai creep model” function, in accordance with the antisymmetric relationship between the unstable creep curve and surface dynamic subsidence curve. An empirical method and fitting method are proposed to determine the parameters of the improved model based on the availability of measured field data. The accuracies of the two models are compared with monitored data from eight monitoring points in the main strike profile of the Guotun coal mine subsidence basin. The results show that the improved model can more accurately reflect the dynamic process of surface subsidence. The average relative standard deviation of the improved model is only 4.9%, which is far lower than the 23.1% associated with the Knothe model. This verifies the improved model’s accuracy and reliability. The model parameters for different monitoring stations obtained using the fitting method are similar, which shows that the model parameters are regular and can be easily applied.