Hot Ductility of Ti/Nb-added 800MPa Grade Weathering Steel

Zhao, Xue; Gan, Bin; Zhang, Mei; Zhong, Yong; Hou, Menglian; Lin, Li Hsiang

doi:10.2991/icaemt-15.2015.162

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…[3][4][5][6][7][8][9][10][11][12][13][14][15][38][39][40][41][42] Zhang et al indicated that hot ductility trough resulted from the formation of pro-eutectoid ferrite films along prior austenite grain boundaries. [38,39] The distribution of the impurities [40] or precipitation [39,41] containing Ti, Nb, B, etc. at prior-austenite grain boundaries is another major reason for the obvious loss of hot ductility.…”

Section: A Factors Influencing the Hot Ductilitymentioning

confidence: 99%

Hot Ductility and Compression Deformation Behavior of TRIP980 at Elevated Temperatures

Zhang

Gan

et al. 2017

Metall Mater Trans B

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The hot ductility tests of a kind of 980 MPa class Fe-0.31C (wt pct) TRIP steel (TRIP980) with the addition of Ti/V/Nb were conducted on a Gleeble-3500 thermomechanical simulator in the temperatures ranging from 873 K to 1573 K (600°C to 1300°C) at a constant strain rate of 0.001 s À1 . It is found that the hot ductility trough ranges from 873 K to 1123 K (600°C to 850°C). The recommended straightening temperatures are from 1173 K to 1523 K (900°C to 1250°C). The isothermal hot compression deformation behavior was also studied by means of Gleeble-3500 in the temperatures ranging from 1173 K to 1373 K (900°C to 1100°C) at strain rates ranging from 0.01 s À1 to 10 s À1 . The results show that the peak stress decreases with the increasing temperature and the decreasing strain rate. The deformation activation energy of the test steel is 436.7 kJ/mol. The hot deformation equation of the steel has been established, and the processing maps have been developed on the basis of experimental data and the principle of dynamic materials model (DMM). By analyzing the processing maps of strains of 0.5, 0.7, and 0.9, it is found that dynamic recrystallization occurs in the peak power dissipation efficiency domain, which is the optimal area of hot working. Finally, the factors influencing hot ductility and thermal activation energy of the test steel were investigated by means of microscopic analysis. It indicates that the additional microalloying elements play important roles both in the loss of hot ductility and in the enormous increase of deformation activation energy for the TRIP980 steel.

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Section: A Factors Influencing the Hot Ductilitymentioning

confidence: 99%

Hot Ductility and Compression Deformation Behavior of TRIP980 at Elevated Temperatures

Zhang

Gan

et al. 2017

Metall Mater Trans B

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Deep Learning to Predict Deterioration Region of Hot Ductility in High-Mn Steel by Using the Relationship between RA Behavior and Time-Temperature-Precipitation

Jeong

Hong

Yim

2022

Metals

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Reduction of area (RA) measurement in a hot ductility test is widely used to define the susceptibility of surface crack of cast steel, but the test is complex because it entails processes such as specimen fabrication, heat treatment, tensile testing, and analysis. As an alternative, this study proposes a model that can predict RA. The model exploits the relationship between precipitation and RA behavior, which has a major effect on hot ductility degradation in high-Mn steels. Hot ductility tests were performed using four grades of high-Mn steels that had different V-Mo compositions, and the RA behavior was compared with the precipitation behavior obtained from a time-temperature-precipitation (TTP) graph. The ductility deterioration of high-Mn steels shows a tendency to start at the nose temperature TN at which precipitation is most severe. Using this relationship, we developed a model to predict the hot ductility degradation temperature of high-Mn steels. TN was calculated using J-matpro software (version 12) for 1500 compositions of high-Mn steels containing the precipitating elements V, Mo, Nb, and Ti, and by applying this to a deep neural network (DNN), then using the result to develop a model that can predict TN for various compositions of high-Mn steel. The model was tested by comparing its predicted RA degradation temperature with RAs extracted from reference data for five high-Mn steels. In all five steels, the temperature at which the RA decreases coincided with the value predicted by the DNN model. Use of this model can eliminate the cost and time required for hot ductility testing to measure RA.

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Hot Ductility of Ti/Nb-added 800MPa Grade Weathering Steel

Cited by 2 publications

References 8 publications

Hot Ductility and Compression Deformation Behavior of TRIP980 at Elevated Temperatures

Hot Ductility and Compression Deformation Behavior of TRIP980 at Elevated Temperatures

Deep Learning to Predict Deterioration Region of Hot Ductility in High-Mn Steel by Using the Relationship between RA Behavior and Time-Temperature-Precipitation

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