High-order propagation of jet noise on a tetrahedral mesh using large eddy simulation sources
conference contributionposted on 2020-09-04, 13:46 authored by Miguel Moratilla-Vega, Vishal Saini, Hao XiaHao Xia, Gary PageGary Page
Jet noise is an important area of research in commercial aviation due to its high contribution to the overall noise generated by an aircraft. Conventionally, CFD combined with surface integral methods is used to study jet noise because of its low cost. However, it is not always trivial to define integration surfaces around complex geometries. This study employs a different two-step approach that can handle complex geometries. It combines a large-eddy simulation (LES) to obtain the acoustic sources from the flow field, and an acoustic perturbation equations (APE) solver to propagate the sound to the far field. The LES is performed with an industrial 2nd-order finite volume solver. The APE code is a high-order discontinuous Galerkin (DG) spectral/hp solver of the Nektar+ + framework. The APE solver is validated on a canonical test case. A study on different polynomial expansion orders and meshes is further performed to estimate the mesh size for noise propagation in the high-order spectral/hp DG context. Finally, a three-dimensional jet noise case (Re = 10, 000 and Mach = 0.9) is simulated using unstructured tetrahedral mesh for the APE solver and improved noise results for high frequencies are obtained. The results demonstrate that the present approach is capable of predicting noise in complex geometry scenarios, such as installed jets under the aircraft wings.
EPSRC for the UK supercomputing facility ARCHER via the UK Turbulence Consortium (EP/L000261/1).
CSE programme of the ARCHER UK National Supercomputing Service.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering
Published inSpectral and High Order Methods for Partial Differential Equations ICOSAHOM 2018
Pages325 - 335
- VoR (Version of Record)
Rights holder© The Authors
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Book seriesLecture Notes in Computational Science and Engineering; vol 134