An adaptive smoothed particle hydrodynamics for metal cutting simulation

Normally large amounts of particles are required to accurately simulate the metal cutting process, which consumes a lot of computing time and storage. Adaptive techniques can help decrease the number of particles, hence reducing the runtime. This paper presents a novel adaptive smoothed particle hydrodynamics (SPH) method for the metal cutting simulation. The spatial resolution changes adaptively according to the distance to the tool tip by the particle splitting and merging. More particles are selected in the region where the workpiece and the tool are in contact. Since the contact region constantly changes during the cutting process, two quadrilateral frames are adopted in the adaptive algorithm to dynamically change the distribution of particles. One frame for the refinement, the other for the coarsening. These frames move at the same speed as the tool. To test the computational efficiency, the metal cutting process is simulated by using SPH with three different adaptive approaches. Numerical results show that the proposed adaptive algorithm with dynamic refinement and coarsening can significantly optimize the runtime.