This was a cooperative project involving Betriebsforschungsinstitut, Comdicast AB, voestalpine Stahl, RIVA Acciaio, Scuola Superiore di Studi Universitari e di Perfezionamento Sant’Anna, RWTH Aachen, Arcelor España and Kungliga Tekniska Högskolan.
The focus was to develop innovative improvement measures for clogging prevention or minimisation.
The developments are based on results from the analysis of operational praxis and on new basic knowledge concerning clogging mechanism.
Various data bases were generated and proper statistical analysis on influence of operational and metallurgical parameters on clogging were performed. Investigations on clogging mechanisms were done by theoretical studies and use of a Confocal Scanning Laser Microscopy. Clogging rate deposition measurements were carried out by a clogging simulator. Basic information on possible influences of physical processes on clogging was studied by means of physical modelling and numerical simulation.
Investigation concerning new feeding systems designs and gas injection strategies were performed.
Methods for prediction of clogging by suitable defined clogging indices basing on operational parameters as well as a neural network based predictor for steel castability and a clogging prediction model were developed. Operational trials were performed for validation of optimisation measures. Important findings are provided which can be directly used by other European steel producers or at least can be used as an offset for activities adjusting methods and measures to their individual operational situation.