# Combined CFD-Stochastic Analysis of an Active Fluid Injection System for Jet Noise Reduction
## 4 Conclusions  
This paper illustrates the use of a computational aeroacoustics approach, named SNGR (Stochastic Noise Generation and Radiation), based on CFD RANS solutions, and aimed at jet-noise prediction and reduction.  
The SNGR method, used in the present work, reconstructs the turbulent velocity fluctuations and calculates the source terms of Vortex Sound acoustic analogy equation, by using Green's free-field function.  
In the first part of this work, the [PERSON]'s test case has been reproduced to validate the coupled RANS-SNGR approach for its subsequent use as a design tool. The numerical results of aerodynamic and acoustic fields, obtained with the coupled RANS-SNGR approach, have been successfully assessed and validated against both experimental data and results of Large-Eddy Simulations (LES).  
In the second part, a technique based on injecting small jets of secondary air, drained from the turbine, into the main jet flow is proposed and assessed. The fluid injection technique, unlike fixed and passive reduction systems such as mechanical chevrons, can be used in all cases that present a real need for noise reduction, such as takeoff and landing phases when the most intense phenomenon of jet noise takes place.  
Four tests were carried out, involving gas bleed from the turbine and subsequent injections into the main flow of exhaust gas with the aim of aiding a greater mixing and breaking the large turbulent structures. The four tests have analyzed the influence on the noise reduction of several parameters, such as drained mass flow rate, the area of the injection section and the slope angle of the secondary jets at the same drained pressure and temperature. The best result was obtained in the 4 th test, characterized by \(\dot{m}_{spill}=5\%\)\(\dot{m}_{tot}\), \(P_{spill}=250{,}000\) Pa, \(T_{spill}=367.2\) K, \(A_{inj}=80\) mm\({}^{2}\), \(\gamma=80^{\circ}\) and \(u_{inj}=720\) m/s, where the maximum noise reduction was achieved, by approximately 3.5 dB compared to [PERSON]'s baseline case without injection.  
Therefore, such tests have confirmed that the fluid injection technique allows an effective jet noise reduction. Moreover, like pointed out by the parametric study discussed in the previous section, the fluid injection technique can be designed as an active and adaptive system, after a proper optimization of several parameters, like the drained mass flow rate, the related pressure and temperature, the injection section area and jet angle, depending on the flight and engine operative conditions.  
This kind of fluid injection technique will be controlled by an electronic control unit, in order to produce air outflows from the turbine, and then injections within the gas flow, only when needed. The electronic control of the fluid injection also should allow to regulate at any time the bled mass flow and the temperature and outlet pressure values, in order to optimize the noise reduction in accordance  
Figure 19: (**a**) Overall Sound Pressure Level Directivity on the inner arc; (**b**) Overall Sound Pressure Level Directivity on the outer arc.  
with the operating conditions. Finally, the efficacy of this technique can be further enhanced by azimuth control of the injections, which varies with the operating conditions.  
This work was conducted as part of the framework of DANTE project (Development of Aero-vibroacoustics Numerical and Technical Expertise), funded under the Italian Aerospace Research Program (PRORA).  
[PERSON] programmed and set the SNGR code for the numerical prediction of jet-noise and designed the noise reduction concept. [PERSON] performed the CFD simulations of the aerodynamic field and carried out the comparison with experimental data and LES results. [PERSON] determined the features of the jet-noise reduction system and organized the numerical test campaign. [PERSON] provided hints on SNGR applications and on techniques of noise reduction.  
The authors declare no conflict of interest.