Unstructured Overset Hybrid RANS/LES Simulations for Jet Noise Prediction

The objective of this proposal is the development and demonstration of an efficient scale-resolving aeroacoustic approach for the prediction of noise generated by installed engine configurations. The development of new engine concepts has traditionally relied on inexpensive low and mid-fidelity methods combined with expensive experimental campaigns. Scale-resolving simulations offer a cost-effective alternative to model testing. In this Phase 1 proposal we seek to demonstrate the efficiency and accuracy of our dual-mesh, dual-solver overset strategy for jet-noise aeroacoustics. An efficient unstructured mesh solver is used to resolve the flow near the nozzle, while our high-order, adaptive, Cartesian mesh DG solver is used to resolve the acoustic waves in the jet-plume region. The DDES approach is used to model the turbulent jet flow. The temporal evolution of the nozzle flow is used as input tonbsp;a source-time-dominant implementation of the Ffowcs-Williams Hawkings (FW-H) equation to determine the jetrsquo;s noise spectra at far-field observers. The acoustic integration will be performed on a permeable surface that encloses the noise-generating turbulent structures in the jet. Additionally, the feasibility of the volume integration of the quadrupole term in the FW-H equation will be investigated. This Phase-1 work will target the prediction of the noise generated by an isolated round jet. The accurate prediction of the noise spectra atnbsp;far-field observers will demonstrate the feasibility of our high-order, adaptive, overset noise-prediction strategy. The established noise-prediction methodology will be further refined and used in the second phase of this project to predict the noise generated by complex, installed engines configurations. Our overset mesh paradigm is well suited for complex geometries, and our successful implementation of the quadrupole term will resolve the uncertainties in choosing suitable FWH integration surfaces.