
Internship Engineer-Development of a thermo-kinetic model for Paint-bake hardness prediction F/H/X (Voreppe, FR, 38341) at Constellium
Constellium · Voreppe, France · Onsite
- Office in Voreppe
C-TEC RECRUTE
INTERNSHIP - R&D ENGINEER F/H/X
Constellium is a global leader designing and manufacturing innovative and high value-added aluminum products and solutions for a broad range of applications dedicated primarily to aerospace, automotive and packaging markets. Constellium Technology Center (C-TEC) based in Grenoble (Voreppe - 38) is Constellium’ s European research center with 246 employees and 20 nationalities.
PROJECT TITLE : « AA6xxx aluminum alloys for Automotive Body Sheets: Development of a thermo-kinetic model for Paint-bake hardness prediction »
6xxx alloys is a family of aluminum alloy widespread in automotive industry (sheets for Body in White, structural parts) and more generally in industry for their good compromise of formability, strength and corrosion resistance while at an affordable cost.
Constellium is one of the worldwide leading companies in the development and production of AA6xxx alloys for automotive market, transportation and industry. Automotive Body Sheets are produced in plants both in Europe and also in the US and these plants do product development supported by our 2 R&D centers based in Voreppe (France) and Plymouth (US-Michigan).
Heat treatable 6xxx alloys follow an age hardening treatment during which they gain their final strength. The particularity for Automotive Body Sheets is that it happens at customer’s plant during paint curing. The in-service temper is thus both cold worked and underaged. There is a great stake in having an accurate prediction of the material strength after this artificial ageing treatment depending on the thermomechanical ageing conditions.
A C++/Python ageing model for AA6xxx alloys has been developed with such a target. The objective of the internship is to participate in improving this model based on extended literature survey of models and observable phenomena together with data learning on a wide internal database. In parallel dedicated trials and characterizations will have to be led to challenge the physical hypothesis of the model.
The project has several components :
- Literature survey about AA6xxx ageing modelling and characterization: draw a benchmark of existing formalisms for various steps (impact of quench, prestrain, natural ageing) compared to current internal model, make a database of reliable microstructural observations about the nanosized hardening precipitates either by TEM or by 3DAPT (precipitates size, density, stoechiometry).
- Design and run specific trials relevant to check the accuracy of modelling choices. Besides strength, assessment of several characterization techniques available at CTEC that could be employed such as DSC, electrical conductivity.
- Expend the database of observable results (strength, microstructural observations).
- Be proactive in suggesting model improvements. Implement them in the C++/Python code. Fit the relevant parameters on the database. Make an overall assessment of the model evolution proposed.
- Participate in some more state-of-the-art CTEC activities of microstructural characterization for quantifying these hardening precipitates (TEM, 3DAPT).
Without taking literature survey into account the main part of the intern’s work will be numerical (modelling and data analysis), about 75%. The other part will be to launch, follow trials and possibly run some characterizations.
Education level : Master’s degree
Engineering school / option required : materials science
Competencies & technical & soft skills requirement :
- Scientific skills : materials science, knowledge of metallurgy appreciated
- Motivation for modelling / data analysis
- Computer skills : Python, Office
- Soft skills : rigorous, autonomous, teamwork
- Languages : English/French
- Good level of the English language (both written and spoken)