BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
BEGIN:VEVENT
ORGANIZER;CN=ESTAD 2023:mailto:info@metec-estad.com
LOCATION:Room 19b
SUMMARY:High speed video observations of the fascinating melt behaviour in the RH plant
DESCRIPTION:In the upcoming years, the steel industry faces major challenges due to the demands of CO2 reduction and a shift towards circular economy. These developments lead to a larger diversity in crude steel compositions and thus to increased demands for secondary metallurgy including the RHplant.  
To meet these increased demands the efficiency of the RH process needs to be improved. Such an improvement can be based on better process understanding, enhanced process models and improved measurement data. The results presented in this paper target the improvement of the process understanding by providing advanced analysis of high-quality images of the melt surface in the chamber.
These images show a complex two-phase flow situation ranging from highly dynamic steel foam to the generation of small drops. Different situations can be linked to different process conditions. During oxygen blowing the generation of small drops is more likely, while during calmer degassing steps a coarse steel foam layer of significant thickness can be observed, emitting singular or lumps of liquid steel bubbles completely detached from the melt surface. 
In addition to these phase distribution phenomena a pulsating behaviour of the melt can be identified during foamy states showing regular eruptions. This dominant frequency has been detected based on the velocity of the visible objects in the chamber. 
These observations provide the basis for better process understanding and better process monitoring. The presence of a foam layer implies that the interfacial area between gas and liquid is much larger than expected while the dominant frequency of the velocity evaluation might be used to validate simulation models for the two-phase flow in the chamber. The visible difference between the different states in the chamber can be exploited for video-based process monitoring. These findings are a first step towards improving the RH process and its reliability. 
CLASS:PUBLIC
DTSTART:20230615T090000
DTEND:20230615T092000
END:VEVENT
END:VCALENDAR