Toegepaste Mechanica en Energieconversie (TME), Leuven (Arenberg)
KU Leuven
5 dagen geleden

The Thermal and Fluids Engineering research group headed by Prof. M. Baelmans focuses on modeling, numerical simulation, and optimization of thermal, fluid and kinetic transport phenomena.

Embedded in KU Leuven’s Mechanical Engineering Department, Applied Mechanics and Energy Conversion Section, applications range from thermal management in electronic components, over heat transfer and storage devices to thermal networks and nuclear fusion reactors.

Starting from dedicated component and system models, existing designs are critically reviewed and implicit design assumptions are challenged.

This leads to innovative concepts and designs for electronic devices, coolers, heat exchangers and integrated energy systems.

Due to a wide range of applications, a unique combination of expertise in CFD and advanced optimization techniques is available within the research group.

Its close collaboration with renowned research institutions in the region such as IMEC, EnergyVille, SCK-CEN and Forschungszentrum Juelich, as well as the expertise available in our comprehensive university, add on to the unique and inspiring research environment we create.

We are looking for a highly motivated, enthusiastic and communicative researcher with a Master of Science degree in Engineering, or a related field, from a reputable institute.

Candidates with a background in e.g. numerical optimization and computer science are also encouraged to apply. Strong analytic skills are required, as evidenced by excellent study results.

The candidate should have a strong background in fluid dynamics and computational fluid dynamics (finite-element methods) and a sound background in mathematical optimization.

Experience with coding languages such as python and C++ is considered a strong advantage. Applicants should also have good English communication skills.

Whereas shape optimization techniques based on computational fluid dynamics have revolutionized the design of aerodynamic surfaces and channel surfaces over the last three decades, the development of these techniques for finned heat transfer devices is still a very new research domain.

Nevertheless, shape optimization techniques can drastically improve the compactness and energy efficiency of finned heat transfer devices.

The reason is that they enable us to optimize the entire fin shape according to the most detailed physical models available for heat convection, i.

e. the Navier-Stokes flow and temperature equations.

So far, shape optimization has been applied to heat transfer surfaces in just a limited number of studies. Most of the work is focused on two-dimensional flows in pipes, channel cross sections, or arrays of long tubes.

In the literature, mostly gradient-free methods have been applied, which are only suitable for optimizing a small number of design parameters, so that often just a marginal design improvement is achieved.

On the contrary, the gradient-based shape optimization methods that are currently applied for aerodynamic design of wings and vehicles allow easily to optimize several hundred surface parameters or more.

Especially, the application of such gradient-based shape optimization methods to three-dimensional fin surfaces for enhanced flow and heat transfer in micro devices is a very new and yet unexplored research track.

Therefore, the first aim of this PhD research is to develop such methods for finned heat transfer surfaces operating under steady laminar flow.

In the second stage of the PhD project, the methodology will be extended to unsteady flows. Unsteady flow is often encountered in finned heat transfer devices at higher mass flow rates, due to the onset of (time-periodic or chaotic) vortex shedding or due to pulsating inlet condition.

In particular, this PhD focuses first on the implementation of accurate and computationally efficient algorithms for large-scale shape optimization under the steady Navier-Stokes flow and temperature equations.

In addition, also optimal heat transfer surface design for transient flow conditions will be considered, building on the heavily parallelized unsteady flow solvers and steady adjoint flow solvers in our (DOLFIN / FEniCS) software framework.

To achieve large-scale design for both steady and transient conditions, exploration of suitable large-scale gradient-based optimization algorithms will be a core task in this PhD project.

The final goal is to arrive at an automated design framework for micro-channel heat sinks with large fin arrays.

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