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Postdoctoral vacancy (2.5 years) on multi-axial fatigue modelling and testing for 3D printed metal parts

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 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 develop suitable criteria for fatigue life prediction under multi-axial stress states, and validate them by multi-axial fatigue tests. Those criteria will be implemented in an already developed software environment. The researcher will work in close collaboration with Siemens Industry Software for this project, and will be supported by their development team. The final objective is to develop an industrial software solution that can be applied to complex AM components and predict their fatigue life. 
The position is a mix of numerical simulation and experimental testing in the field of multi-axial fatigue of 3D printed metals. The candidate should be experience in both aspects of the work. The equipment for the multi-axial fatigue testing is available in the lab of the research group, together with all instrumentation methods.

Only candidates with a PhD degree or equivalent experience should apply. The candidate should have a strong background in fatigue life prediction for metals (e.g. critical plane approaches) and have experimental experience with fatigue testing. Experience in simulation of AM metals is recommended. 

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