Updating BEM for Yawed Flows: A Multi-Fidelity Assessment

In this work, we improve the Blade Element Momentum (BEM) method for yawed horizontal-axis wind turbines (HAWTs). Skewed inflow, where the wind direction is not normal to the rotor, is crucial for wake steering and off-design conditions. Current BEM methods use Glauert's redistribution model, which shows limitations in recent comparisons with experiments. This motivates us to use higher-fidelity simulations as reference datasets. We use a multi-fidelity approach, comparing BEM with 1) OpenFAST's vortex code, 2) a skewed vortex cylinder model, and 3) the blade-resolved ExaWind CFD tool.

We guide BEM improvements by identifying where its assumptions break down and investigate wake deflection, blade number effects, wake rigidity, and radial annuli independence. We propose a new redistribution model for axial induction under skewed conditions that account for magnitude and phase offset. The model is calibrated through nonlinear curve fitting and agrees well with high-fidelity results while keeping low cost.

In future work, we will refine the model by adding vorticity-based corrections to the redistribution model.