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Application and optimisation of experimental methods and development of physical models
This PhD project forms part of the Digitally Enhanced New Steel Product Development (DENS) program, in which Tata Steel Europe, Materials innovation institute (M2i) and several academic partners collaborate to enable the development of new generations of advanced materials for e.g. the automotive industry.
Digitally Enhanced New Steel Product Development (DENS) program
Significant progress has been made in the past decades in the development of advanced models that describe the behavior of steel during processing and subsequent applications. However, the quantitative application of through process models in new steel product development still lacks predictivity. In modern steel grades, parameters of the steel production process have a significant influence on the final material properties. Furthermore, the trend towards complex multi-phase microstructures requires very sophisticated models to describe their mechanical properties in a predictive manner. The main scientific challenge addressed in this program is to integrate state-of-the-art models in a single through process model framework that can be applied in practice for new steel product development.
During plastic deformation of metals, work hardening is caused by dislocations introduced into the metallic microstructure, which plays a significant role in the formation of dislocations. The Taylor equation and several existing models give a good prediction of the dislocation behaviour, but lack accurate experimental validation of the physical concepts resulting in limited assumptions.
The primary aim is to understand and describe the evolution of the grain structure and the dislocation structure during rolling. The starting-point will be in existing models but will be validated and extended based on experimental determination. The model should be set up for use in DAMASK simulations on deformation behaviour. Resulting dislocation structures will be applied in the CA-SIPT model for phase transformations and recrystallisation. A simplified model, including the essential features, is to perform as an in-line model in the production process, predicting work hardening and yield-point elongation also for multi-phase microstructures.
The project will therefore involve a combination of application and optimisation of experimental methods and development of physical models.
We are searching for enthusiastic candidates holding an MSc degree in physics, chemistry, materials science or a similar field. The candidate must have knowledge of physics of materials, solid state physics, solid-solid phase transformations, and mechanical behaviour. Moreover, the candidate should have:
• affinity for computational simulations as well as a solid background in mathematics and numerical methods.
• a critical academic attitude with excellent analytical skills, initiative, inventiveness, curiosity, and critical thinking about the research approach and results.
• strong communication skills (high degree of English proficiency), ability to integrate, and good social behaviour.
The TU Delft offers a customisable compensation package, a discount for health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. An International Children’s Centre offers childcare and an international primary school. Dual Career Services offers support to accompanying partners. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities.
As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment; an excellent team of supervisors, academic staff and a mentor; and a Doctoral Education Programme aimed at developing your transferable, discipline-related and research skills. Please visit graduateschool.tudelft.nl/ for more information.
For more information about this position, please contact Professor J. (Jilt) Sietsma, e-mail: firstname.lastname@example.org.
Minds for Innovation is the recruitment partner for this project. For more information regarding recruitment please contact Jolanda de Roo. E: email@example.com, T: + 316 572 913 50.
To apply, please visit the website www.m4i.nl/vacancies/ and use M4i's online application tool by 31 July 2018. When applying for this position, please refer to vacancy number 3ME17-80 in the subject of your motivation letter.
Jolanda de Roo
Technische Universiteit Delft
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