Year: 2025
Type: article
Abstract: Traditional position-based fluid (PBF) methods often suffer from interpolation inaccuracies and limited computational efficiency due to their fixed smoothing length. To address these limitations, this paper proposes an adaptive smoothing length model and implements full-pipeline parallel acceleration on GPUs. By incorporating both local neighbor count and density variation, the model dynamically adjusts particle smoothing length. This adaptation effectively mitigates two issues: surface distortion due to insufficient interpolation in sparse regions, and performance degradation caused by computational redundancy in dense regions. To resolve neighbor search asymmetry introduced by dynamic smoothing lengths, we designed a symmetry handling technique based on maximum smoothing length and an efficient spatial hashing search algorithm. Experimental results across multiple scenarios (including dam break and droplet impact) demonstrate that our method maintains simulation stability comparable to the fixed smoothing length approach while improving computational efficiency and enhancing local particle distribution uniformity. The improved uniformity is evidenced by a significant reduction in the variance of neighbor particle counts. Visually, the method yields more natural results for dynamic details such as splashing and fragmentation, thereby ensuring the visual realism of the simulations.
Source: Computers
Authors: Changjun Zou, Xirun Li
Institution: East China Jiaotong University
Language: English
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,172
Award: G1175904147
OpenAlex ID: W7117706767