A hybrid artificial intelligence control of a turbulent jet: Reynolds number effect and scaling

This work aims to investigate experimentally the effect of the Reynolds number Re, based on the nozzle diameter D , on jet mixing manipulation using an unsteady radial minijet. A novel artificial intelligence (AI) control system has been developed to manipulate the jet over Re = 5800–40 000. The system may optimize simultaneously the control law and a time-independent parameter, which dictate the actuation ON/OFF states and amplitude, respectively. The control parameters include the mass flow rate, excitation frequency and diameter ratios ( C m , f e / f 0 and d / D ) of the minijet to the main jet as well as the duty cycle ( α ) of minijet injection. Jet mixing is quantified using K e and K 0 , where K is the decay rate of the jet centreline mean velocity, and subscripts e and 0 denote the manipulated and unforced jets, respectively. It has been found that the maximum K e achievable does not vary with Re. Scaling analysis of the huge volume of experimental data obtained from the AI system reveals that the relationship K e = g 1 ( C m , f e / f 0 , α , d / D, Re, K 0 ) may be reduced to K e / K 0 = g 2 $(\zeta )$ , where g 1 and g 2 are different functions and the scaling factor $\zeta = ({C_m}/\alpha ){(D/d)^{1 - n}}(1/Re){({f_e}/{f_{e,opt}})^m}$ , m and 1 − n are the power indices, and subscript opt denotes the value at which K e is maximum. The scaling law is discussed in detail, along with the physical meanings of the dimensionless parameters K e / K 0 , ζ , $({C_m}/\alpha ){(D/d)^{1 - n}}(1/Re)$ and ${({f_e}/{f_{e,opt}})^m}$ .