A Method of Integrating Spatial Division Strategy with Parallelized Boolean Operation to Speed-Up Machining Process Simulation

For workpieces made from expensive materials that incur high machining costs, machining simulation has become a crucial tool for pre-machining inspection. However, achieving high-precision simulations requires extensive Boolean operations, which are computationally demanding. For years, software developers have faced the challenge of balancing precision with computational efficiency in machining simulation. To address this issue, this paper proposes a method integrating spatial division with parallelized Boolean operations. Firstly, parallelization is applied at the application level, using a KD-tree to partition polyhedral and quickly identify intersecting parts. To solve the low computational speed of traditional Boolean operations, parallelization is further applied at the algorithmic level. Experiments results demonstrate that the proposed method outperforms the Cork algorithm by nearly 4 times and the Libigl algorithm by almost 8 times, significantly improving the computational efficiency of complex machining simulations.