A HYBRID NUMERICAL/EXPERIMENTAL STUDY OF THE AERODYNAMIC NOISE PREDICTION

Year 2018, Volume: 4 Issue: 4 - Special Issue 8: International Technology Congress 2017, Pune, India, 2201 - 2210, 10.04.2018

Beyza Alkan

https://doi.org/10.18186/journal-of-thermal-engineering.434037

Cited By: 2

Abstract

An accurate noise prediction
is important in order to reduce noise emission significantly and to prevent
expensive after-design treatments. This study aims to examine the aerodynamics
and aeroacoustics performance of an open system consisting of an axial fan and
a heat exchanger where hybrid method incorporating CFD (Computational Fluid
Dynamics) and CAA (Computational Aeroacoustics) is used to predict the noise
behavior. The hybrid model method used consists of three steps. Firstly, the
flow is computed by means of flow-computed fluids and the pressure fluctuations
are obtained. This is followed by the acquisition of acoustic signals from
these fluctuations and the attainment of a sound pressure level approach with
the FW-H (Ffowcs Williams & Hawkings) model.  Unsteady flow field of the air channel case
was obtained by using different turbulence models. The SAS model is capable of
resolving largescale turbulent structures without the time and grid-scale
resolution restrictions of LES (Large Eddy Simulations), often allowing the use
of existing grids created for URANS simulations. For this reason, two different
turbulence models, namely URANS (Unsteady Reynolds Averaged Navier Stokes)
model, SAS (Scale Adaptive Simulations) model have been applied. Acoustic
sources were computed based on the pressure fluctuations and sound pressure
level and frequency dependent graphics were plotted with Fast Fourier
Transform. On the other hand, acoustic measurements were performed in a
semi-anechoic chamber for both of them. When the experimental and numerical
results were compared with the previously determined receiver points, the
accuracy rate was obtained as SAS, URANS respectively.

Keywords

Aeroacoustics, Computational Fluid Dynamics, Noise Sources, SAS, Turbulence

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