# URANS Analysis of a Launch Vehicle Aero-Acoustic Environment
## 4 Conclusions  
In the context of designing a noise-reduction system to improve sound attenuation during space vehicles' launch, a numerical modeling framework was defined to predict  
Figure 6: Pressure temporal evolution along the fairing at (**a**) an azimuth angle of 315° and different heights, (**b**) at a constant height of 39.7 m with different azimuth angles, and (**c**) at 42.7 m and different azimuth angles. Figure 7: Pressure gradient magnitude and components. (**a**) Graphical representation at t = 0.126 s. (**b**) Plot over the fairing axial plane. acoustic loads. CFD was used to assess the noise generation and propagation mechanisms in the low-frequency regime. The reliable analysis of this type of environment involves considering many variables and physical phenomena such as the combustion of gases, the compressibility of the supersonic flow, and the lift of the launch vehicle. In addition, if we want to solve the generated turbulence and with a sufficient resolution from the acoustic point of view, the simulation of a rocket launch requires an extremely high computational and engineering cost that is out of industrial reach. In this work, the simulation was simplified to model this complex environment from the engineering point of view. The main requirements were to minimize the computational time while modeling the phenomena accurately. Thus, it was evaluated whether URANS-type modeling offered sufficient accuracy at a low computational cost. A limitation of the work was that there were no experimental data close to the rocket engine. Therefore, data on the far-field and fairing surface were used. The validation showed a better data correlation at the fairing surface than in the mass surrounding the launch pad. The apparent lack of correlation could be attributed to different sources of error as the simplification of the launch pad structures, of the exhaust gases thermodynamics, or URANS modeling. However, there was a bigger refinement of the cells at the fairing rather than at the far-field points. Hence, this was reflected in the better prediction of the results. The primary refinement was in the region where the jet develops. Upstream, the cells' size increased to reduce the computational cost. The approximate computational time to simulate 0.1 \"real-life\" s of the \(10^{6}\) element mesh with 128 processors was 33 d, which is a substantial amount. Moreover, a collateral issue was the large amount of data generated for each step. The greater the mesh, the greater the amount of data was. Further work should address the effect of the mesh size in this region on the accuracy and computational cost. The results found that the sound pressure maxima appeared due to the normal shock wave generated by the jet and its impingement with the deflector. Moreover, the shock waves present were visualized by numerical Schlieren pictures. Furthermore, the vertical directivity of the pressure over the fairing and the propagation of upstream sound waves were observed. These findings showed that the diffuse field did not represent the acoustic field that excited the fairing. Finally, these results provided insight into the phenomena during a rocket lift-off. The knowledge regarding the noise propagation paths will help design the noise reduction systems and define their positioning on the launch pad. Conceptualization, S.H. and L.M.G.-R.; methodology, S.H., M.S.E.-G. and L.M.G.-R.; software, M.S.E.-G.; validation, S.H., M.S.E.-G. and L.M.G.-R.; formal analysis, M.S.E.-G.; resources, S.H. ; writing--original draft preparation, M.S.E.-G.; writing--review and editing, S.H. and L.M.G.-R.; supervision, S.H. and L.M.G.-R.; funding acquisition, S.H., M.S.E.-G. and L.M.G.-R. All authors have read and agreed to the published version of the manuscript. This research was funded by the European Space Agency of Project REDLAUCH: Launch Sound Level Reduction under contract 4000126316/19/NL/LvH.