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Job Record #16727
TitleAdvanced automated meshing for complex aeronautical geometries
CategoryPhD Studentship
EmployerCranfield University
LocationUnited Kingdom, Cranfield
InternationalYes, international applications are welcome
Closure Date* None *
*** Description of the Project ***

The digital wind tunnel, situated within the Airbus and Rolls-Royce co-funded Aerospace Integration Research Centre (AIRC) at 
Cranfield, aims to synergise the advantages of classical wind tunnel testing and Computational Fluid Dynamics (CFD), aiming to 
increase productivity, robustness and turnaround times of computer-based simulations.

This requires a rethinking of automated mesh generation approaches that are robust, provide high-quality meshes and are versatile 
enough to be applied to a range of different flow scenarios. In this PhD, novel meshing strategies will be developed that can 
reliably and automatically mesh complex geometries that are of interest for the aerospace industry.

The digital wind tunnel aims to redefine the way CFD is being used in the aerospace sector. Traditionally, the weak form of the 
Navier-Stokes equations is discretised when simulating fluid dynamics which results in a range of valid mathematical solutions, not 
all of which are physical. This requires expert knowledge in a given application area in order to set up valid simulations, which has 
to be validated against reference data. This expertise is then commonly captured in best practice guidelines. The digital wind tunnel 
aims to provide an interface for so called flow scenarios, which are documents specifying best practices that can be understood by a 
CFD solver. Based on these best practices / flow scenarios alone, CFD calculations can be performed without any additional input from 
the user, other than variables that can be measured or influenced in a real wind tunnel (e.g. inflow velocity, ambient density, 
pressure, temperature, turbulent intensity, etc.).

This requires rethinking the way we handle pre-processing in CFD calculations, which is to date still a largely manual labour part 
and consumes most of the set-up time for one-off simulations. This PhD aims to evaluate the current state of the art of automated 
mesh generation using the Cartesian cut-cell technique and devise a new algorithm that is robust and can produce high-quality meshes, 
including inflation layers and the ability to locally refine the mesh. The mesh generation will be entirely driven by the flow 
scenarios without additional user input and has to be versatile enough to produce meshes for a range of different applications that 
are of interest to the aerospace industry. Although commercial and open-source solvers already provide this functionality, these 
methods still suffer from either poor mesh quality metrics, incorrect geometry representation, lack of robustness for complex 
geometries or manual user input.

To demonstrate the effectiveness of the generated automatic mesh generator algorithm, challenging geometries of the aerospace sector 
will be selected and used to validate the meshing strategy. Manually created meshes by skilled professionals for the same geometry 
will be used to demonstrate the advantages of the automated mesh generation approach through CFD simulations. The successful 
applicant will work within the Airbus and Rolls-Royce co-funded Aerospace Integration Research Centre (AIRC), driving the development 
of state-of-the-art pre-processing algorithms that will be fundamental to the success of the digital wind tunnel development at 
Cranfield. Furthermore, there is a potential to collaborate within other projects planned for the digital wind tunnel, both with 
industrial partners and researchers at Cranfield.

*** Entry requirements ***

Applicants should have a first or second class UK honours degree or equivalent in a related discipline (e.g. aerospace, automotive, 
mechanical, applied mathematics, computer science). Furthermore, the applicant should:

- Have a good understanding of high-level programming languages (C++ / Python preferred)
- Be self-motived and organised
- Have excellent communication skills and be willing to publish their findings in conferences and journal articles
The following is considered beneficial but not essential:

- Be familiar with general software development (build systems, unit testing, code review, quality assurance, etc.)
- Be familiar with a Linux operating system 
- Have knowledge of open source / commercial mesh generators

*** About Cranfield's Doctoral Network ***

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued 
members of the Cranfield Doctoral Network. This network brings together both research students and staff, providing a platform for 
our researchers to share ideas and collaborate in a multi-disciplinary environment. It aims to encourage an effective and vibrant 
research culture, founded upon the diversity of activities and knowledge. A tailored programme of seminars and events, alongside our 
Doctoral Researchers Core Development programme (transferable skills training), provide those studying a research degree with a 
wealth of social and networking opportunities.

*** Funding ***

Please note that this is a self-funded opportunity. A letter of support can be provided upon request for funding applications.

*** How to apply / Contact ***

For more information about the position and Cranfield University, please visit the official PhD position advertisement at

To apply, please send your CV and cover letter to the email shown below. The successful applicant is still required to submit their 
application through the online system of the university.
Contact Information:
Please mention the CFD Jobs Database, record #16727 when responding to this ad.
NameTom-Robin Teschner
Email ApplicationYes
AddressCollege Road
MK43 0AL
Record Data:
Last Modified11:44:18, Friday, September 04, 2020

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