Dynamic numerical simulation of ice-propeller milling based on GPU parallel computing

Abstract

To integrate high-performance GPU parallel computing with the peridynamics method and enhance the computational efficiency of numerical simulations for ice-propeller milling, thus providing better data support for the design of propellers in ice-covered areas, a GPU-based parallel peridynamics computational approach was developed on CUDA in this study. The approach was built upon the bond-based peridynamics theory and CUDA programming framework, and its validity was confirmed using test cases involving an airfoil cutting ice and an ice ball impacting a rigid wall. A corresponding three-dimensional GPU parallel computational program was created for the ice-propeller milling process, and the computational code was optimized, resulting in a 24-fold increase in computational efficiency. Utilizing the high-performance computational code, the influence of sea ice elastic modulus and propeller pitch on the mechanical performance of the blades was investigated. The computational results revealed that the ice loads on the blades increased with rising elastic modulus and decreased with increasing pitch, and a larger pitch led to more sea ice being milled away.