Rolling force for strip casting of 1Cr17 ferritic stainless steel was predicted using theoretical model and artificial intelligence.Solution zone was classified into two parts by kiss point position during casting strip.Navier-Stokes equation in fluid mechanics and stream function were introduced to analyze the rheological property of liquid zone and mushy zone,and deduce the analytic equation of unit compression stress distribution.The traditional hot rolling model was still used in the solid zone.Neural networks based on feedforward training algorithm in Bayesian regularization were introduced to build model for kiss point position.The results show that calculation accuracy for verification data of 94.67% is in the range of ±7.0%,which indicates that the predicting accuracy of this model is very high.
The formation of phosphorous surface inverse segregation (SIS) in twin-roll cast strips of low-carbon steels was studied. High phosphorous strips were fabricated by using a pilot twin-roll strip caster and a melt/substrate contacting apparatus,respectively. Solidification structures of strips were observed and analyzed,and phosphorus distributions along longitudinal sections of strips were investigated and discussed. The results showed that solidification structures of all strips were columnar grains,either integrated or coarse in the strip made by the melt/substrate contacting apparatus or damaged in some degree in cast strips; and that during cast strip solidification,enrichment of phosphorus occurred between columnar grains,and the average phosphorus concentration near the surface in the strip with 0.15% of phosphorus was measured to be about 0.27% which was obviously higher than that in the bulk.
