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  High-fidelity CFD and data-driven modelling of aerodynamic noise sources

   School of Metallurgy & Materials

  Dr Zhong-Nan Wang  Applications accepted all year round  Funded PhD Project (Students Worldwide)

About the Project

Applications are invited for one funded 3.5-year PhD studentship for the project titled “High-fidelity CFD and data-driven modeling of aerodynamic noise sources” in the group of Dr Zhong-Nan Wang at the University of Birmingham. The research of Dr Wang’s group is focused on developing high-fidelity CFD and data-driven approaches for aerodynamics and aeroacoustics. The PhD project is expected to start within 2024 (but can be flexible). The successful applicant will be able to work within a vibrant and multidisciplinary aerospace team under the College of Engineering and Physical Sciences at the University of Birmingham and also have opportunities to engage with researchers at other national and international leading academic institutions, e.g. Cambridge and MIT, and industries, such as Rolls-Royce and Airbus, via established collaboration.

Project details:

Noise pollution is a growing environmental issue and becomes the second-largest environmental cause of health problems in Europe, just after air pollution. As the volume of air traffic keeps growing, aviation noise becomes of great concern to society. Thus, noise is now an important factor in certificating newly developed civil aircraft as well as future urban unmanned air vehicle (UAV).

Aviation noise is primarily generated by unsteady turbulent flows. Most of the current technologies are to absorb noise rather than reduce it at the source, which is inefficient. One example of reducing noise at the source is to serrate jet nozzle or airfoil leading/trailing edges. The serrated edge is able to reduce noise emissions. However, the design is largely trial-and-error and heavily depends on expensive rig testing, because the mechanisms of turbulence noise generation are not fully clear yet. In this project, we will employ high-fidelity CFD to provide full details of noise generation processes in unsteady turbulent flows. The data-driven method will be developed to explore noise-generation dynamics and inform low-order modeling, which will eventually lead to optimal control of reducing noise emissions. The application will be initially focused on jet noise, but the method to be developed in the project is general, so it can be used to tackle a broad range of aero-acoustic problems.

Please contact Dr Zhong-Nan Wang () for an informal query about this studentship.


The candidate will have a 1st class undergraduate or Master’s degree (or equivalent) in Mechanical Engineering, Aerospace Engineering, Mathematics, Physics, Computer Science, or a related discipline. You would be highly motivated, and able to work independently as well as collaborate with others with effective written/oral communication skills. Knowledge of fluid mechanics or CFD is essential. Experience in programming (Fortran/C++/Python) would be an advantage. 

How to apply:

The application will be made through the university’s online application system ( Please provide a cover letter summarizing your research interests and suitability for the position, the contacts of two referees and a curriculum vitae. It is recommended to contact Dr Zhong-Nan Wang () with your CV before you apply.

Engineering (12) Mathematics (25)

Funding Notes

Funding amount: £18,622 p.a. with generous funding for conference and training use.

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