Prediction of Combustion Noise in a Model Combustor Using a Network Model and a LNSE Approach

Abstract

The reduction of pollution and noise emissions of modern aero engines represents a key concept to meet the requirements of the future air traffic. This requires an improvement in the understanding of combustion noise and its sources, as well as the development of accurate predictive tools. This is the major goal of the current study where the low-order thermo-acoustic network (LOTAN) solver and a hybrid computational fluid dynamics/computational aeroacoustics approach are applied on a generic premixed and pressurized combustor to evaluate their capabilities for combustion noise predictions. LOTAN solves the linearized Euler equations (LEE) whereas the hybrid approach consists of Reynolds-averaged Navier–Stokes (RANS) mean flow and frequency-domain simulations based on linearized Navier–Stokes equations (LNSE). Both solvers are fed in turn by three different combustion noise source terms which are obtained from the application of a statistical noise model on the RANS simulations and a post-processing of incompressible and compressible large eddy simulations (LES). In this way, the influence of the source model and acoustic solver is identified. The numerical results are compared with experimental data. In general, good agreement with the experiment is found for both the LOTAN and LNSE solvers. The LES source models deliver better results than the statistical noise model with respect to the amplitude and shape of the heat release spectrum. Beyond this, it is demonstrated that the phase relation of the source term does not affect the noise spectrum. Finally, a second simulation based on the inhomogeneous Helmholtz equation indicates the minor importance of the aerodynamic mean flow on the broadband noise spectrum.

Effect of Film Cooling on Entropy Noise Generation in a Stator Blade Row

“…3D URANS) is in the research field of enhancing the understanding of fundamental physical processes. In real industrial design environments, there is an additional need for less computational-time consuming prediction tools [9,37]. The available and widely used low order model of Cumpsty and Marble [5] accounts for the propagation of acoustic, vorticity, and entropy waves through a blade row.…”