Strategies for energy-efficient flow control leveraging deep reinforcement learning

TL;DR

This paper uses deep reinforcement learning to develop energy-efficient flow control strategies for two-dimensional flows around cylinders, optimizing jet placement and control actions to reduce drag and energy consumption effectively.

Contribution

It introduces a DRL-based approach for active flow control that identifies optimal jet placement and multi-action strategies to enhance energy efficiency and aerodynamic performance.

Findings

Optimal jet placement at flow separation points reduces drag significantly.

Multi-action control decreases initial energy consumption and improves efficiency.

Flow interaction with synthetic jets creates vortices that enhance flow control effectiveness.

Abstract

This study investigates active flow control in two-dimensional flows at a Reynolds number of 100 using Deep Reinforcement Learning (DRL). We utilize DRL to develop flow control strategies that enhance energy efficiency and minimize energy consumption, thereby addressing the limitations of traditional methods. We find that the optimal jet placement for both square and circular cylinders is at the main flow separation point, achieving the best balance between energy efficiency and control effectiveness. For the circular cylinder, positioning the jet at approximately 105{\deg} from the stagnation point requires only 1% of the inlet flow rate and achieves an 8% reduction in drag, with energy consumption one-third of that at other positions. For the square cylinder, placing the jet near the rear corner requires only 2% of the inlet flow rate, achieving a maximum drag reduction of 14.4%, whereas energy consumption near the front corner is 27 times higher, resulting in only 12% drag reduction. In multi-action control, the convergence speed and stability are lower compared to single-action control, but activating multiple jets significantly reduces initial energy consumption and improves energy efficiency. Physically, the interaction of the synthetic jet with the flow generates new vortices that modify the local flow structure, significantly enhancing the cylinder's aerodynamic performance. Our control strategy achieves a superior balance between energy efficiency and control performance compared to previous studies, underscoring its significant potential to advance sustainable and effective flow control.