This work focuses on the suppression of Tollmien-Schlichting (TS) waves in a two-dimensional laminar boundary layer using optimized unsteady suction and blowing jets as an Active Flow Control (AFC) method. The suppression of TS waves via this AFC system is enabled through two artificial intelligence-based optimization methodologies: Single-Step Deep Reinforcement Learning (SDRL) and Particle Swarm Optimization (PSO). The primary aim of this research is to assess the performance of these methods in optimizing the AFC parameters with respect to convergence rate, computational efficiency, and ability to find an optimum control state. The findings demonstrate the success of both methods in finding appropriate control parameters resulting in TS wave attenuation by up to 40 dB in the maximum convective instability amplitude for the linear and nonlinear stages of development. The comparative study in this paper presents the effectiveness of the SDRL algorithm in optimizing the AFC system for TS waves’ suppression and demonstrates that it can outperform PSO in terms of convergence rate and computational efficiency alongside a better performance in finding an improved optimum for linear control cases. However, the advantage of the SDRL-based controller over the PSO-based one diminishes in multi-frequency nonlinear control cases where the controller is located downstream and attempting to control highly amplified multi-modal TS waves.@en

The current numerical study is dedicated to investigating the effect of passive, active, and combined flow control techniques on the performance of the vehicles in different maneuvers including, platoon and overtaking on critical highway velocity (70 miles per hour) for a reference bluff body vehicle called Ahmed body. The target passive flow control method is an innovative technique called Rear Linking Tunnels (RLTs), introduced previously by the group of authors. Studying the effect of the Single Dielectric Barrier Discharge Actuator (SDBD) as an active flow control method and its combined effect with RLTs on the drag and lift of controlled vehicles and surrounding vehicles in various maneuvers is one of the main aims of this research study.@en