Modeling of austenite decomposition in plain carbon steels during hot rolling

Zhang, Yutuo; Li, Dianzhong; Li, Yiyi

doi:10.1016/j.jmatprotec.2005.07.003

Cited by 12 publications

(3 citation statements)

References 6 publications

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“…The fraction X transformed in the matrix at any given temperature is a function of the proportion of the fraction X and the transformation temperature T, namely _ X ¼ f ðX ; T Þ [22,23]. The non-isothermal transformation kinetics can be described as the sum of a series of the small isothermal transformation [24,25].…”

Section: Decomposition Model Of Austenite To Pearlitementioning

confidence: 99%

Application of mathematical model for microstructure and mechanical property of hot rolled wire rods

Zhang

Wang

et al. 2009

Applied Mathematical Modelling

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A set of integrated mathematical models for predicting microstructures evolution during hot rolling and controlled cooling of high carbon wire rods has been developed through laboratory research work and industrial validation experiments. It consists of many sub-models such as critical strain, static and dynamic recrystallization of austenite, fraction of transformed austenite, interlamellar spacing of pearlite, microstructure-property relations. Based on the models, a simulating software is programmed which can run on PC computers. The physical metallurgy process during hot rolling and controlled cooling including the temperature distribution, the evolution of austenite grains, fraction of transformation austenite, final microstructure and mechanical properties were predicted. The predicted results are agree well with measured of the industrial tests.

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Section: Decomposition Model Of Austenite To Pearlitementioning

confidence: 99%

Application of mathematical model for microstructure and mechanical property of hot rolled wire rods

Zhang

Wang

et al. 2009

Applied Mathematical Modelling

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“…How to improve the accuracy of temperature control for finishing rolling is always a key issue of hot rolling temperature control [1]. The ultimate goal of temperature control for finishing rolling is that through dynamic adjustment of spraying and rolling speed among racks, the strip exactly reaches the target finished temperature after rack rolling so that the strip has good structural performance and accurate dimensional size [2]. Temperature changes of strip during finishing rolling are subject to many factors, such as thermal radiation, high pressure descaling water, low pressure cooling water, rolling deformation, rolling contact, etc.…”

Section: Introductionmentioning

confidence: 99%

Temperature Control System Modeling and Simulation of Finishing Mill

Chen

Zou

2013

AMM

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The precise control for the product strip temperature is one of the effective approaches to promote the quality in the finish rolling production. The paper presents the basic features of the control strategies, temperature feedforward control and temperature feedback control for the strip temperature control system of Baosteel 2050mm finish rolling in details. Considering the strip thickness, a differential heat transfer model is proposed to calculate the heat conduction of the strip thickness direction of each node and attain multi-stand and finishing rolling exit temperature. In addition, the proposed method combined with the model prediction and feedback control, the feedforward control to adjust the rolling speed to ensure the strip head temperature hit rate dynamically adjusted using feedback control regulating water temperature of the strip full-length. The application results show that the temperature difference model prediction and feedback control accuracy is significantly improved than the original 2050mm temperature system.

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“…A new regression model was proposed in this paper, and it has good agreements between the experimental and predicted results through comparisons among the three models mentioned above. There are several methods to describe the transformation kinetics, such as JMAK equation, ISV framework, K-M equation, modified Zener-Hillert equation, modified Magee's rule, phase field model, the cellular automaton method [8][9]. In this paper, the regression method with two models based on the Avrami equation to describe the transformation kinetics was employed.…”

Section: Introductionmentioning

confidence: 99%

Modeling the austenite-ferrite transformation in microalloyed steel P510L

Wang

Gui

et al. 2010

Int J Miner Metall Mater

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Based on experimental results, the transformation kinetics and cooling characteristics of low-carbon steel were analyzed and modeled to quantitatively link the operational parameters of a process with the properties. From the continuous cooling transformation results, comparisons of the start temperature of austenite-ferrite transformation among three models were analyzed, and the optimal lnk and n, which are the parameters in the Avrami equation, were determined by applying two regression models at different cooling rates. The transformation kinetics during continuous cooling was determined. Furthermore, reasonable agreements between experimental results and predictions were obtained, which can demonstrate the rationality of the established models.

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Modeling of austenite decomposition in plain carbon steels during hot rolling

Cited by 12 publications

References 6 publications

Application of mathematical model for microstructure and mechanical property of hot rolled wire rods

Application of mathematical model for microstructure and mechanical property of hot rolled wire rods

Temperature Control System Modeling and Simulation of Finishing Mill

Modeling the austenite-ferrite transformation in microalloyed steel P510L

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