Assessment of a Hybrid Eulerian–Lagrangian CFD Solver for Wind Turbine Applications and Comparison with the New MEXICO Experiment

Abstract

In this paper, the hybrid Lagrangian–Eulerian solver HoPFlow is presented and evaluated against wind tunnel measurements from the New MEXICO experiment. In the paper, the distinct solvers that assemble the HoPFlow solver are presented, alongside with details on their mutual coupling and interaction. The Eulerian solver, MaPFlow, solves the compressible Navier–Stokes equations under a cell-centered finite-volume discretization scheme, while the Lagrangian solver uses numerical particles that carry mass, pressure, dilatation and vorticity as flow markers in order to represent the flow-field by following their trajectories. The velocity field is calculated with the use of the decomposition theorem introduced by Helmholtz. Computational performance is enhanced by utilizing the particle mesh (PM) methodology in order to solve the Poisson equations for the scalar potential ϕ and the stream function ψ→. The hybrid solver is tested in 3-D unsteady simulations concerning the axial flow around the wind turbine (WT) model rotor tested in the New MEXICO experimental campaign. Simulation results are presented as integrated rotor loads, radial distribution of aerodynamic forces and moments and pressure distributions at various span-wise positions along the rotor blades. Comparison is made against experimental data and computational results produced by the pure Eulerian solver. A total of 5 PM nodes per chord length of the blade section at 75% have been found to be sufficient to predict the loading at the tip region of the blade with great accuracy. Discrepancies with respect to measurements, observed at the root and middle sections of the blade, are attributed to the omission of the spinner geometry in the simulations.