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 has a significant influence and the value equating to the particle smoothing length is suggested.

中文翻译：

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考虑边界摩擦效应的基于质心聚合的3D-SPH形式的泥石流动力学模拟边界检测算法


泥石流与粗糙河床之间的边界摩擦相互作用的计算对于模拟泥石流动力学行为至关重要，因为它会影响最终的流速和沉积面积。到目前为止，平滑粒子流体动力学（SPH）方法中已经提出了一些边界处理方法，例如传统的动态边界条件（DBC）和边界临界层（BCL）方法，但这些方法在边界处理方面受到限制。有效考虑复杂地形上的边界摩擦。本文定义了粒子化摩擦影响​​域的概念，而不是传统方法中固定和预定义的边界临界层，并提出了一种嵌入3D-SPH框架的基于质心聚合的边界检测算法（CA-BD）建议的。该算法捕捉泥石流颗粒与粗糙边界颗粒之间的多种相互作用形式并计算相互渗透，从而确定泥石流颗粒所受的摩擦力。此外，为了提高计算效率，还实现了CPU-OpenMP并行加速框架。为了验证所提出的模型，模拟了有据可查的溃坝流实验和泥石流水槽实验，其中与实验中观察到的 DBC 和 BCL 方法相比，所提出的模型更好地再现了流动行为。计算效率比较表明，所提出的模型获得了 CPU 串行解决方案的 2.9 倍加速因子。敏感性分析还表明，摩擦影响域的预定义长度具有显着影响，并且建议使用等于粒子平滑长度的值。