Impact of Angle Optimization on Jet Control by Initial Velocity Distribution

Abstract

Jets are used in various fluidic devices, and it is necessary to understand jet control to enhance its performance for different purposes. Initial velocity optimization is one of the methods for jet control. Considering the feasibility, it is essential to clarify the impact and importance of optimizing the ejection angle, because it is relatively easy to change the magnitude of the velocity, but precise angle modification is very challenging. Therefore, this study aims to clarify the impact of angle component of initial velocity optimization by using deep reinforcement learning together with computational fluid dynamics simulation. Two-dimensional incompressible fluid simulations were performed. The streamwise (x) and vertical (y) lengths are 15d and 20d, respectively. Here, d is the width of the jet exit and d=20mm. The fluid is the air and initial flow rate q₀ was fixed to 0.004 m²/s. In this case, the Reynolds number based on the mean initial velocity and jet width is 2700. As the jet temperature, T, was set to 303.15K while the initial ambient temperature T₀ was set to 298.15K. Figure 1 shows that the distributions are close to uniform in the cases of temperature maximization and velocity minimization. In contrast, in the other three cases, the distributions are significantly different from uniform. It is worth noting that the first two cases correspond to the optimization to suppress entrainment, and the rest correspond to the optimization to promote entrainment(1). With respect to the spatial distribution of the velocity, in the cases for entrainment promotion, although the number of peaks and positions are not the same among the three cases, the large velocity generally directs inward (toward the centerline) in the case with angle optimization. On the other hand, when it is aimed at suppressing the entrainment, the velocity at the edges is large and tends to direct outward.