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Artificial Neural Network Modelling of the Effect of Vanadium Addition on the Tensile Properties and Microstructure of High-Strength Tempcore Rebars
Authors:Woonam Choi  Sungbin Won  Gil-Su Kim  Namhyun Kang
Affiliation:1.R&D Center, Dongkuk Steel, 70 Geonposaneop-ro, 3214beon-gil, Nam-gu, Gyeongsangbuk-do, Pohang 37874, Korea; (W.C.); (S.W.); (G.-S.K.);2.Department of Materials Science and Engineering, Pusan National University, Busan 46241, Korea
Abstract:In high-strength rebar, the various microstructures obtained by the Tempcore process and the addition of V have a complex effect on the strength improvement of rebar. This study investigated the mechanism of strengthening of high-strength Tempcore rebars upon the addition of vanadium through artificial neural network (ANN) modelling. Various V contents (0.005, 0.072 and 0.14 wt.%) were investigated, and a large amount of bainite and V(C, N) were precipitated in the core of the Tempcore rebar in the high-V specimens. In addition, as the V content increased, the number of these fine precipitates (10–30 nm) increased. The precipitation strengthening proposed by the Ashby–Orowan model is a major contributing factor to the yield-strength increase (35 MPa) of the Tempcore rebar containing 0.140 wt.% V. The ANN model was developed to predict the yield and tensile strengths of Tempcore rebar after the addition of various amounts of V and self-tempering at various temperatures, and it showed high reproducibility compared to the experimental values (R-square was 93% and the average relative error was 2.6%). ANN modelling revealed that the yield strength of the Tempcore rebar increased more significantly with increasing V content (0.01–0.2 wt.%.) at relatively high self-tempering temperatures (≥530 °C). These results provide guidelines for selecting the optimal V content and process conditions for manufacturing high-strength Tempcore rebars.
Keywords:Tempcore   high strength rebar   V-alloyed rebar   CCT diagram   V(C   N) precipitation   artificial neural network   yield strength
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