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CFD Jobs Database - Job Record #16806

Job Record #16806
TitlePhD Studentship - CFD of supersonic jet noise
CategoryPhD Studentship
EmployerUniversity of Leicester, School of Engineering
LocationUnited Kingdom, Leicester
InternationalYes, international applications are welcome
Closure DateMonday, November 23, 2020
Description:
Predicting jet noise is currently a challenge even for subsonic jet engines.
State-of-the-art Computational Fluid Dynamics (CFD) methods, such as
Large-Eddy Simulation, can accurately capture the noise sources in the jet
near-field, but using the same methods to compute the noise propagation to the
far-field is still prohibitively expensive. Computational Aero-Acoustics (CAA)
methods, specifically designed for noise propagation, are therefore usually
coupled with the CFD solution in a hybrid approach, in which the noise sources
are generated within the CFD simulation and then exchanged with the CAA code
for propagation to the far-field.

Supersonic jets present even further challenges compared to subsonic ones, due
to more complex noise sources and most importantly to non-linear propagation
effects, which can distort the acoustic waves and shift the peak frequencies.
A thorough comparison of CAA methods, such as Acoustic Perturbation Equations
(APE), Linearized Euler Equations (LEE) and full Euler equations, is therefore
necessary to evaluate their effectiveness and limitations in capturing these
supersonic effects.

The aim of this research is to provide an analysis of the importance of these
aspects for the study of future passenger flights. The PhD student will
implement a new efficient hybrid CFD-CAA code with open-source software,
capable of accurately solving noise generation and propagation in supersonic
cases, with the goal of increasing our understanding of supersonic noise and
of providing best practice for the scientific community and for the industry,
while testing the limits of state-of-the-art computational techniques.
Contact Information:
Please mention the CFD Jobs Database, record #16806 when responding to this ad.
NameDr Matteo Angelino
Emailm.angelino@leicester.ac.uk
Email ApplicationNo
URLhttps://www.findaphd.com/phds/project/an-efficient-coupling-of-computational-fluid-dynamics-and-aeroacoustics-methods-for-supersonic-flows/?p124424
Record Data:
Last Modified11:41:26, Friday, October 16, 2020

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