EIT Cortools - Machine learning steel corrosion simulation survey

The EIT Raw Materials Cortools project develops corrosion on-line monitoring and prediction software tools. The project consortium includes Boliden, DMS, Tecnalia, Ferritico, Outokumpu, Outotec, VTT and ZAG.

This survey investigates the market demand for machine learning steel properties simulation support, focusing on corrosion, and is hosted by Cortools machine learning partner Ferritico.

Do you have questions? Please email contact@ferritico.com

Question Title

* 1. What is your role(s) in the steel industry?

Steel development

Steel product design

Steel manufacturing

Post-processing, implementation and assembly of products containing steel components

End-user of steel products

Steel research

Developing software for the steel industry, e.g. FEM software

Other (please specify)

Question Title

* 2. Are you doing simulations in your work, i.e. approximate imitation or prediction of the behaviour of a process or a material, based on steel properties (chemical, mechanical, physical or thermodynamical) or degradation mechanisms?

Yes

Don't know