A numerical demonstration of dynamic stall control

TL;DR

This paper demonstrates the real-time application of two physics-based criteria, LESP and BEF, for dynamic stall mitigation using numerical simulations, showing their effectiveness and potential integration with advanced control strategies.

Contribution

It introduces a practical proof of concept for using LESP and BEF criteria in dynamic stall mitigation through numerical simulations, advancing control strategies.

Findings

Both LESP and BEF effectively mitigate dynamic stall effects.

The criteria show potential for integration with reinforcement learning control.

Numerical simulations validate the criteria's effectiveness across different motions.

Abstract

This paper presents a numerical demonstration of the real-time application of two dynamic stall onset criteria for identifying and mitigating stall. These criteria - based on the leading-edge suction parameter (LESP) and boundary enstrophy flux (BEF) - are derived from prior research. The present work establishes a proof of concept for the practical use of these indicators in mitigating dynamic stall. Two different unsteady motions that lead to dynamic stall are simulated. For each motion, both baseline cases (where dynamic stall occurs) and controlled cases (where stall is mitigated using the onset criteria) are analyzed using the unsteady Reynolds-averaged Navier-Stokes (uRANS) method. Both parameters were found to be effective in mitigating the adverse effects (large variations in aerodynamic loads) of dynamic stall. The results demonstrate the potential for these physics-based criteria to be integrated with advanced control strategies, such as reinforcement learning agents, for robust stall control across a range of operating conditions.