Predicting and inhibiting aerodynamically generated noise for fast moving vehicles such as cars, aircraft and trains is increasingly important. The tonal noise generated by the shear-layer instability of air flowing around the cavity opening is especially one of the most significant and most intense sources of aerodynamically generated noise. Computational aeroacoustics (CAA) based on the CFD simulations of compressible Navier-Stokes equations offers the most general approach to predicting those aerodynamically induced sounds. Aeroacoustics is practically always associated with turbulent flow and turbulence is the major challenge for CFD simulations. Four different turbulence modelling approaches are examined in this work. Three of them belong to the LES method category and one uses the URANS approach. Appropriate numerical discretization and iteration schemes have been identified for each of these approaches and implemented in the OpenFOAM open source CFD platform. The accuracy, computational performance and convergence reliability of those schemes have been subsequently studied during three-dimensional CFD simulations on a model of a suitable real object. The CFD simulation results are validated by a measurement. An organ pipe has been chosen as the object of this CAA research because it uses self-sustained oscillations, commonly referred as shear-layer (Rossiter) modes, as the source of its tone generation. The numerical simulation of the shear layer modes, respectively the noise generated by instability in the shear layer, is the subject of this work.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:383530 |
Date | January 2018 |
Creators | Šálený, Vratislav |
Contributors | Kozubková, Milada, Paur, František, Tippner,, Jan, Katolický, Jaroslav |
Publisher | Vysoké učení technické v Brně. Fakulta strojního inženýrství |
Source Sets | Czech ETDs |
Language | Czech |
Detected Language | English |
Type | info:eu-repo/semantics/doctoralThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
Page generated in 0.0022 seconds