Applications are invited for a 4-year UK PhD studentship for the project titled “Data-Driven Analysis for Reducing Turbulence Noise using High-Fidelity Computational Fluid Dynamics (CFD)” in the group of Dr Zhong-Nan Wang at the University of Birmingham. The research of Dr Wang’s group is focused on developing and employing high-fidelity CFD and data-driven approaches for aerodynamics and aeroacoustics. The PhD project is expected to start in October 2021 (but can be flexible). The successful applicant will receive an annual tax-free stipend of £15,514 per year and payment of home tuition fee up to 4 years. 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 other national and international leading academics and industries via established collaboration.
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 at 4.3% annually, aviation noise is 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 both passing aircraft and exhausted from its engine. Most of the current technologies are to absorb noise rather than reduce it at the source, which is inefficient. One exception is to shape the trailing edge of engine nacelles with serrations, also referred to as chevrons. The serrated trailing edge of the jet nozzle is able to reduce noise emission from engine exhausted jet flows. 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. Recently, the high-fidelity CFD opened up a new horizon by providing great opportunities to examine the processes of noise generation in great detail . In this project, the data-driven approaches will be developed within the high-fidelity CFD frame  to explore the flow processes of noise generation and seek an efficient way of shaping jet nozzles to suppress the ‘noisy’ flow processes. The application will be mainly on jet noise, but the method to be developed in the project is quite general, so it can be used to tackle a broad range of aero-acoustic problems, such as rotor/fan noise of UAVs and aircraft engines.
Please contact Dr Zhong-Nan Wang (email@example.com) for an informal query about this studentship.
The candidate will have a 1st class undergraduate or Master’s degree (or equivalent) in Mechanical Engineering, Aeronautical Engineering, Mathematics or 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 must 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. Please send a copy directly to Dr Zhong-Nan Wang (firstname.lastname@example.org).