Flow Field and Heat Transfer of an Impinging Synthetic Jet in the Presence of Cross-Flow: Application of SAS and DES Approaches

Nowadays, synthetic jets have various applications such as cooling enhancement and active flow control. In the present paper, the capability of two turbulence modelling approaches in predicting thermal performance of an impinging synthetic jet is investigated. These two approaches are scale adaptive simulation (SAS) and detached eddy simulation (DES). Comparisons between numerical data and experimental studies reveal that the ability of DES in predicting the asymmetrical trend of heat transfer profiles is better than SAS in almost all the study cases. Although, near the stagnation zone, the performance of SAS is superior. Results show that the effects of parameters such as frequency, cross-flow velocity and suction duty cycle factor are well predicted by both approaches. An increase of cross-flow velocity from 1.81 m/s to 2.26 m/s results in an improvement of [Formula: see text] near the stagnation point by almost 16.3% and 9.2% using DES and SAS, respectively.

Reinforcement-learning-based control of confined cylinder wakes with stability analyses

This work studies the application of a reinforcement learning (RL)-based flow control strategy to the flow past a cylinder confined between two walls to suppress vortex shedding. The control action is blowing and suction of two synthetic jets on the cylinder. The theme of this study is to investigate how to use and embed physical information of the flow in the RL-based control. First, global linear stability and sensitivity analyses based on the time-mean flow and the steady flow (which is a solution to the Navier–Stokes equations) are conducted in a range of blockage ratios and Reynolds numbers. It is found that the most sensitive region in the wake extends itself when either parameter increases in the parameter range we investigated here. Then, we use these physical results to help design RL-based control policies. We find that the controlled wake converges to the unstable steady base flow, where the vortex shedding can be successfully suppressed. A persistent oscillating control seems necessary to maintain this unstable state. The RL algorithm is able to outperform a gradient-based optimisation method (optimised in a certain period of time) in the long run. Furthermore, when the flow stability information is embedded in the reward function to penalise the instability, the controlled flow may become more stable. Finally, according to the sensitivity analyses, the control is most efficient when the probes are placed in the most sensitive region. The control can be successful even when few probes are properly placed in this manner.

Schlieren Flow Visualization and Analysis of Synthetic Jets

This work explores several low-cost methods for the visualization and analysis of pulsed synthetic jets for cooling applications. The visualization methods tested include smoke, Schlieren imaging, and thermography. The images were analyzed using Proper Orthogonal Decomposition (POD) and numerical methods for videos. The results indicated that for the specific nozzle studied, the optimal cooling occurred at a frequency of 80 Hz, which also corresponded to the highest energy in the POD analysis. The combination of Schlieren photography and POD is a unique contribution as a method for the optimization of synthetic jets.