high performance computing on graphics processing units: hgpu.org

The vortex core shed from rotorcraft blades maintains coherency-and thus dynamic relevance-many blade turns after its creation. This presents a challenge to traditional Eulerian computational methods, as fine grids are required to suppress numerical diffusion which would weaken the vortex cores after a small number of revolutions. Vortex methods have been used in the past to overcome these problems, as they require computational elements only in vorticity-containing regions, but suffer from greater computational cost per element. In the present work, we will solve these problems with a hybrid EulerianLagrangian method for modeling rotor wakes. An Eulerian OVERFLOW overset grid method computes the near-body flow, while a Lagrangian particle vortex method tracks the wake. The vortex method uses an anisotropic LES model to handle subgrid-scale dissipation explicitly. The computational cost of vortex methods is alleviated by using a parallel adaptive treecode on a cluster of machines each with multi-core CPUs and multiple costeffcient graphics processing units (GPUs). Simulations of a low-Re sphere, finite wing, and 4-bladed rotor model are presented and are validated by comparisons with computational and experimental data.