Dynamic Stall Precursors and Prediction

Developing a physically interpretable, data-driven framework for forecasting dynamic stall by combining space-time proper orthogonal decomposition with conditional statistics to identify precursors in high-fidelity unsteady flow simulations and convert precursor similarity into probabilistic early-warning predictions.