The Bainite Transformation Behavior Of Ultra-low Carbon Microalloyed Steels

Ultra-low carbon bainitic steel eliminates the adverse effects of carbon againstbainite toughness, It will obtain a tissue material with a high density dislocations afterTMCP process. This material is known as one of the most promising steel in21stcentury. Study of the ultra-low carbon microalloyed steels bainite transformationbehavior can get ultra-low carbon bainitic microstructure evolution, be used to guidethe actual production, establish microstructure prediction model, accurately predictproperties of steel and effectively improve the quality of steel production. In thispaper, the ultra-low carbon microalloyed bainitic microstructure evolution is studied,finally BP artificial neural network model are established,which predict the phase thegrain size of the ultra-low carbon bainite after transition and even promote theapplication in forecasting bainite.Firstly,The different ultra-low carbon baintic structure under the differenttechnologcial conditions were gained by isothermal compression test on Q550Dultra-low carbon baintic steel with the Gleeble-3500thermal simulation testingmachine. The ultra-low carbon bainitic microstructure evolution is obtained bymetallographic analysis and scanning electron microscopy analysis (SEM), theevolution is follows:(1)The faster the cooling rate, the baintic lath refinement is more obvious. Thenumber of granular baintic will reduce; The grain refining effect is better when thedeformation temperature is850℃; The effect of relaxation time will become certaincycle with the extension of the relaxation time.(2) The Q550D ultra-low carbon bainitic steel grain refining effect is better whenthe distortion temperature is850℃, the cooling rate is30℃/s and the relaxation timeis60s.Then EBSD test sample is produced by electrolytic polishing technology inDPF-1type electrolytic polishing and etching instrument. When the test condition isVethanol: Vperchloric acid: Vglycerol=7:2:1, voltage is7mv and polishing time250s-350scan produce Q550D ultra-low carbon bainitic steel EBSD test sample.Finally, the ultra-low carbon bainite grain size is measured accurately by EBSDtechnical, the low carbon microalloyed steels bainite transformation model is established by the use of BP neural network. Simulation results show that: The testingerror less than8%for this BP artificial neural network that between the actual grainsize and the simulate grain size, the examination testing error within5%, and thenetwork’s training is high precision. So this BP neural network can be used to predictthe ultra-low carbon bainite grain size after the phase transition, and it will helpimprove the actual production quality for the low carbon bainitic steel.