Centroid aggregation-based boundary detection algorithm in 3D-SPH form for simulating debris-flow dynamics considering boundary frictional effect

The computation of boundary frictional interaction between debris-flow and rough channel beds is crucial for simulating debris-flow dynamic behavior, owing to its impact on the resulting flow velocity and deposition area. Until now, some boundary treatment methods have been proposed in the Smoothed-Particle-Hydrodynamics (SPH) method, such as the conventional Dynamic-Boundary-Conditions (DBC) and Boundary-Critical-Layer (BCL) methods, which are limited in the effective consideration of boundary friction over complex topography. In this paper, instead of the fixed and predefined boundary critical layers in conventional methods, a concept of particlized frictional influence domain is defined, and a novel centroid aggregation-based boundary detection algorithm (CA-BD) embedded in the 3D-SPH framework is proposed. The algorithm captures the diverse interaction forms and computes mutual penetration between debris-flow particles and rough boundary particles, so that the frictional forces exerting on the debris-flow particles can be determined. Additionally, to enhance the computational efficiency, a CPU-OpenMP parallel acceleration framework is implemented. To validate the proposed model, a well-documented dam-break flow experiment and a debris-flow flume experiment are simulated, wherein the proposed model better reproduces the flow behavior compared to the DBC and BCL methods as observed in the experiments. Comparison on the computational efficiency indicates that the proposed model attains a 2.9 times acceleration factor than the CPU serial solution. Sensitivity analysis also reveals that the predefined length of the frictional influence domain $l_f$ has a significant influence and the value equating to the particle smoothing length $h$ is suggested.