Experimental Investigation of Particle Impacts Using Distributed Acoustic Sensing

Geophysical granular flows, such as rock avalanches, debris flows, and bedload transport, generate intense impact forces on the channel bed during downslope movement. These forces produce high-frequency seismic and acoustic waves, which can be detected by seismometers and acoustic sensors. The resulting vibration signals provide valuable insights into flow characteristics; however, quantitatively measuring granular flow processes remains challenging due to the complex mechanisms of particle impacts and the variability in particle locations, motion modes, and impact velocities. Distributed Acoustic Sensing (DAS) offers a promising approach for monitoring such granular flows, leveraging its ability to provide high-resolution, real-time spatial and temporal data across extensive areas. In this study, as a pre-experimental test, particle drop experiments were conducted using spherical objects (5 kg) with varying impact locations and drop heights to investigate the dynamic signal response of a DAS system deployed laterally over 50 m. The DAS system operated with a sampling frequency of 1000 Hz and a spatial resolution of 0.4 m. For each particle impact, key parameters including the number of signal impulses, amplitude, centroid frequency, and power spectral density (PSD) were extracted from the raw DAS data. Virtual shot gathers were analyzed and utilized for wave speed analysis, while beamforming techniques were applied to locate particle impact events spatially. The experimental results demonstrated how signal impulses, amplitudes, and PSDs vary with changes in particle size and impact location. These findings highlight the potential of DAS for monitoring granular flow processes, such as bedload transport, in natural settings.