Postdoctoral fellow

Last application date
Sep 01, 2021 00:00
TW11 - Department of Materials, Textiles and Chemical Engineering
Limited duration
PhD in mechanical engineering, mechanics, materials science, computational mechanics, civil engineering or equivalent
Occupancy rate
Vacancy type
Research staff

Job description

The use of 3D printed metal structures is taking a very fast ramp-up in industry. General Electric has demonstrated the possibility of printing titanium fuel injectors for their LEAP engine, EADS has printed a nacelle hinge bracket for the Airbus A320, Boeing is printing plastic inlet ducts for high-altitude aircrafts, hip implants and other prosthetics are exploiting the design freedom of additive manufacturing (AM),...

Additive manufacturing of titanium, stainless steel and inconel superalloys yields great potential for the aerospace industry (and others) as it allows the generation of geometrically complex structures with high specific strength, low density and high corrosion and creep resistance at high temperatures. However the fatigue life prediction of such components cannot be done with traditional fatigue models for traditionally manufactured metals, because the fatigue life is influenced by various factors that are specific for 3D printing: process parameters, induced voids and defects, microstructure, surface roughness, etc.

In this Postdoctoral position, it is the purpose to further develop multi-scale models for multi-axial fatigue of AM metals, taking into account the presence of voids and the microstructure of the material. Those models will be implemented in an already developed software environment. The final objective is to develop an industrial software solution that can be applied to complex AM components and predict their fatigue life under multi-axial fatigue loads. The position is a fully numerical position, requiring advanced knowledge in numerical simulations (finite element method, material models), fatigue mechanics and multi-axial fatigue indicators, and notions of plasticity and probabilistic fatigue.

The project will be carried out in close collaboration with a large number of industrial companies in the field of additive manufacturing (Siemens, Materialise, Sabca, ESMA,…).

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Job profile

Only candidates with a PhD degree in Computational Mechanics, Mechanical Engineering, Materials Science, Civil Engineering, (Applied) Physics or similar should apply. You have a strong background in computational mechanics and have strong programming skills (preferably in C++ and/or Python), you are interested to perform numerical research and to interact and collaborate with industry.

How to apply

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