At KU Leuven, the departments of Materials Engineering and Computer Science have established a new strategic research initiative on Computational Materials Science, led by Prof. Martin Diehl. The aim is to develop advanced computational tools and new materials, giving an extra dimension to the ongoing research in the two departments. The Department of Materials Engineering (MTM) performs research on material properties and behaviour, materials design and materials production and recycling. At the Department of Computer Science, the research unit NUMA performs research on numerical methods, algorithms and software for simulation and data analysis, with applications in many fields in science and engineering. The research in the unit NUMA on materials engineering focusses on multi-scale simulation, high performance computing and model order reduction. The departments have an extensive national and international network, both in the academic and industrial world. URLs: https://www.mtm.kuleuven.be/English/ResearchGroups and https://wms.cs.kuleuven.be/groups/NUMA
Microstructural features such as the geometry and distribution of phases, grains, subgrains, and inclusions determine the mechanical performance of metallic materials. Both computational and experimental approaches can be used to study the relation between the microstructural features and the resulting mechanical response. The coupling of both approaches requires the generation of a “digital twin”, i.e., an accurate computer model of the experimentally characterized microstructure.
The aim of this Ph.D. project is the combined experimental–computational investigation of the micro-mechanical behavior of a secondary Aluminum-Silicon alloy manufactured by gravity die casting. The hard inclusions found in such alloys, which are an artifact of the aluminum recycling process, have a detrimental effect on the material’s lifetime in fatigue loading. To systematically study the effects of these inclusion, a model Al-Si alloy is produced which is complex enough to include all relevant features such as the eutectic Al-Si phases but simple enough to be characterized and modeled.
We are looking for a Ph.D. candidate who is interested in computational crystal plasticity and the combination of experimental and computational materials science. The proposed tasks include:
You must have an Master degree and a solid background in one of the following areas: computational materials science and engineering, computational mechanics, mathematical engineering, scientific computing, applied mathematics. You should be willing to acquire complementary knowledge from other research areas relevant to the project.
Excellent proficiency in English is required, both oral and written.
We offer a full time position as a PhD researcher. Funding is secured for four years. The initial offer will be a one-year appointment, of which the renewal will only depend on the progress in the PhD research.
For more information please contact Prof. Martin Diehl, mail: firstname.lastname@example.org, Prof. Martine Wevers, mail: email@example.com or Prof. Dirk Roose, mail: firstname.lastname@example.org.
You can apply for this job no later than July 15, 2020 via the online application tool
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|Title||Development of a Digital Twin for an Aluminum Casting Alloy|
|Job location||Oude Markt 13, 3000 Leuven|
|Published||April 15, 2020|
|Application deadline||July 15, 2020|
|Job types||PhD  |
|Fields||Materials Engineering,   Applied Mathematics,   Computational Physics,   Materials Physics,   Mechanical Engineering,   Mechanics,   Computational Mathematics,   Computational Engineering  |