PhD in Modeling and optimization of thermal fields in thin film fluid layers

Computational mechanics achieved a tremendous progress in the last two decades, leveraging mainly the development in computing power and mathematical algorithms. Stabilization techniques are constantly being improved and computing facilities are on the rise. However, despite the progress achieved, several challenges are still not addressed efficiently, such as the thin film problem appearing in small gaps between two large plates or cylinders. This problem is faced for example in cooling of contactless bearings with small gaps in between cylinders.

In the framework of the SKF research chair at Arts et Métiers institute of technology, the problem of cooling, of thin contactless bearing or electric motors, is studied to achieve high cooling rates at low energy cost. Thus, the expected work will focus on the use of advanced computational fluid dynamics techniques, possibly combined with model reduction and machine learning algorithms, to tackle the thin film fluid problem. The simulation will be coupled to an optimization algorithm, in the aim to achieve an optimization of the fluid injection velocity, the injector shapes, the air gaps, and the interface shape. The optimal point would offer the best thermal heat exchange profile, maximizing cooling and minimizing the fluid friction within the air gap. The project will therefore reduce the energy cost involved in the use of these devices and maximizes their profitability.

The work will use an open source CFD simulation code, mainly Open Foam, as well as a possible use of Julia, Python and Matlab programming codes. A use of C/C++ is also expected for some pointy tasks. The successful candidate should be knowledgeable in CFD computing techniques, programming tools and optimization algorithms. The work is expected to start by the beginning of September 2023.