Research on acceleration signal of granular column collapse under dry and wet conditions

The blockage of rivers and reservoirs caused by disasters such as landslides and collapses has always been a troublesome problem. How to quickly capture this disaster information and assess the risk of disasters is of great significance for emergency rescue. With the development of environmental seismology, geological disaster monitoring and parameter inversion based on seismic signals provide new tools for studying these problems. In this paper, granular column collapse experiments under wet and dry conditions are carried out to identify disaster types and key parameters through the analysis of acceleration signals. The results show that regardless of whether the granular column collapses into water, the envelope peak value and average frequency of the acceleration signal are linearly correlated with the initial parameters of the granular column (volume, aspect ratio, granular size, and water depth). Compared with dry conditions, due to the existence of flow resistance under wet conditions, the front part of the flow is denser than under dry conditions, and the post-peak phase of the granular flow process has a shorter duration. When d2/(D × H) < 0.6%, the ratio of the duration of the post-peak phase to the pre-peak phase, k, is 0.5–0.99 under wet conditions and 1–1.8 under dry conditions. The linear relationships between the acceleration signal and the initial parameters of the granular column enable us to use the acceleration signal to determine the scale of landslide disasters. The value of k can be used to determine whether a landslide occurs in a wet environment, which provides a new method to monitor and identify landslide disasters in inaccessible areas.