Applicants should express their interest by sending an email to prof. Martine Baelmans and her team via the dedicated email address firstname.lastname@example.org. The email should *strictly* contain the following information in the text body, in bullets:NameMaster degree (Master specification, University + Country, Year obtained, Promotor)Master thesis titleA one paragraph (up to half an A4 page) statement explaining the motivation for applying for this vacancy at KU Leuven. Please also indicate here which project you apply for.
Please also attach an academic CV to your email. Do not directly apply in the online system as referred to below, nor in the VITO application system. This will be only necessary for selected candidates in a second stage. Note that if you do not receive a response to your email within three weeks, this means you have not been selected for the second stage. Decision: as soon as a suitable candidate applies (so do not wait till the closing date to apply). For more information please contact prof Martine Baelmans and her team via email@example.com.
You can apply for this job no later than December 31, 2018 via the online application tool
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The task of the PhD candidate is to develop a tool that automatically proposes efficient and affordable thermal network designs and with that contributes to providing an affordable solution to decarbonizing building heating supplies.
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.
Thermal networks are an important means to decarbonizing building heating supplies. When designing such thermal networks, several competing objectives arise. At the one hand, investment costs are decisive for the achievability of the project, while also energy-efficiency and dimensioning of pump capacity, at the other hand, are important elements in the design process. With the transition to 4th generation district heating networks, the design challenge becomes ever more challenging. That is, to achieve the best energetic efficiency, a balanced combination of heat storage, energy conversion units, and a diverse collection of (waste) heat sources at different temperatures should be pursued. In scientific literature and within our own research in the EnergyVille framework, automated design methods based on numerical optimization are therefore developed.
Using these methods the configuration (topology) of the entire network is hereby fully parametrized and optimized for the above mentioned goals, leading to a complex optimization problem with many design variables. The state-of-the-art in district heating network design therefore resorts to linearized models to optimize the network configuration. These model assumptions sincerely restrict the applicability of these methods to true 4th generation networks. Moreover, design of large-scale networks is not possible due to the exponential scaling of the computational cost with the network dimension.
Recent research in our group has shown that adjoint-based optimization techniques can provide a solution to this problem. In short, the adjoint method is an approach that enables sensitivity calculation of an objective function to large amounts of design variables at a fixed computational cost of about only two simulations. In addition, its applicability ranges well beyond linear problems and is used within our research group for the optimization of complex flow and heat transport problems. As such, it potentially enables automated large-scale thermal network design, including an accurate nonlinear network model.
The task of the PhD candidate is to elaborate this research track and develop a tool that automatically proposes efficient and affordable thermal network designs and with that contributes to providing an affordable solution to decarbonizing building heating supplies.
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 interest in flow and heat transfer modelling for energy systems, and a sound background in numerical methods. Knowledge of numerical optimization methods is also a plus, as well as experience with MATLAB or similar coding languages. Applicants should also have good English communication skills.
KU Leuven is among the top European universities. The Thermal and Fluids Engineering group under the lead of Prof. Martine Baelmans has a long and well-proven track record in numerical research on combined flow and heat transfer problems.Through i.a. collaborations within EnergyVille, a research collaboration on sustainable energy between KU Leuven, VITO, imec and Uhasselt, the group keeps a close link to the application side.