A Methodology for Predicting the Stability Trend of Ground Collapse Under the Water Flow

Ground collapse is one of the common geological hazards in modern cities. With the development of urbanization, the risk of ground collapse increases, which has a great impact on urban public safety. Ground collapse accidents typically occur due to the presence of unstable cavities under the surface, or the generation and expansion of cavities induced by triggering factors. Investigating the stability of cavities in the strata is significant for identifying subsidence risks and mitigating the consequences of subsidence. This study proposed a method for predicting ground subsidence settlement based on the ARMA model. Firstly, CFD-DEM coupled simulation is employed to simulate the mechanism of cavity changes in the soil layers under the influence of triggering factors and to calculate the safety coefficient for ground subsidence stability. Subsequently, the safety coefficient data at different time points are fitted to predict the subsequent stability of the subsidence. We selected a subway permeable collapse accident in Foshan City, Guangdong Province for experimental verification, and compared the predicted results with the actual situation. The result shows that this method can effectively predict the changes in ground collapse safety factor and the collapse time point. With 40% of the data, high accuracy prediction can be achieved, improving the efficiency of collapse evolution prediction and providing strong support for ground collapse risk prevention and control.