Numerical Prediction of Static and Dynamic Stall Phenomena using the (Intermittency-Momentum thickness Reynolds number) Transition Model

Stall phenomenon can adversely affect the performance of fixed-wing aircraft, helicopters, and wind turbines through loss of lift, increased drag, structural fatigue, and vibrations. Accurate numerical prediction of static and dynamic stall flow physics is therefore essential for improved performance estimation, thereby enabling better designs. In this work, the role of laminar-turbulent transition modeling was investigated in numerical simulation of flows involving static and dynamic stall. The correlation-based γ — Reθt transition model was implemented into a compressible, finite-volume RANS solver and was used to simulate two-dimensional static and dynamic stall flow problems. The baseline Spalart-Allmaras turbulence model generated excessive turbulence and was unable to capture important physical processes such as the formation of a laminar separation bubble on an airfoil surface. The γ — Reθt model showed good predictive capabilities for flows with separation-induced transition. Steady flow simulations using the transition model resulted in significantly improved force, moment, and stall angle predictions. For the dynamic stall simulations at moderate reduced frequency values, the baseline turbulence model failed to obtain qualitatively acceptable downstroke behavior, whereas the transition model predictions were in reasonable agreement with experimental data.