Mathematical Model of Static and Dynamic Recrystallization, Roll Force and Mean Flow Stress of the Nb-Microalloyed Steels for Plain Steel Hot Roughing Mill

2019 ◽  
Author(s):  
M. Machado ◽  
J. dos Santos
Keyword(s):  
Mathematical Model ◽  
Flow Stress ◽  
Dynamic Recrystallization ◽  
Microalloyed Steels ◽  
Roll Force ◽  
Mean Flow ◽  
Roughing Mill ◽  
Mean Flow Stress

Application of Deformation to Improve Hot Ductility in the Peritectic Steel

2005 ◽  
Vol 500-501 ◽  
pp. 203-210 ◽  
Author(s):  
Ahmad Rezaeian ◽  
Faramarz Zarandi ◽  
D.Q. Bai ◽  
Steve Yue
Keyword(s):  
Flow Stress ◽  
High Strength ◽  
Microalloyed Steels ◽  
Hot Strip Mill ◽  
Mean Flow ◽  
Hot Strip Rolling ◽  
Strip Rolling ◽  
Slip Ratio ◽  
Hot Strip ◽  
Mean Flow Stress

The hot strip rolling of advanced microalloyed high strength steels still represents a new task to many mills due to the lack of data on the hot deformation resistance. With the aid of processing data from the Ispat-Inland hot strip mill, the “measured mean flow stresses” are calculated from the mill force using the Sims analysis and taking into account roll flattening, slip ratio and the redundant strain. A modification of the Misaka mean flow stress equation is proposed for C – Mn – Si – Al steels microalloyed with up to 0.02 % Nb. The effects of alloying and microalloying are then estimated. A new fitting parameter shows excellent agreement with the mean flow stress data from industrial processing of advanced high strength microalloyed steels. However, during the second half of the rolling schedule (lower temperature region), indications of austeniteto- ferrite transformation were found.

Modeling of the Resistance to Hot Deformation and the Effects of Microalloying in High-Al Steels under Industrial Conditions

2005 ◽  
Vol 500-501 ◽  
pp. 195-202 ◽  
Author(s):  
Fulvio Siciliano ◽  
Evgueni I. Poliak
Keyword(s):  
Flow Stress ◽  
Hot Deformation ◽  
High Strength ◽  
Microalloyed Steels ◽  
Hot Strip Mill ◽  
Mean Flow ◽  
Hot Strip Rolling ◽  
Strip Rolling ◽  
Hot Strip ◽  
Mean Flow Stress

The hot strip rolling of advanced microalloyed high strength steels still represents a new task to many mills due to the lack of data on the hot deformation resistance. With the aid of processing data from the Ispat-Inland hot strip mill, the “measured mean flow stresses” are calculated from the mill force using the Sims analysis and taking into account roll flattening, slip ratio and the redundant strain. A modification of the Misaka mean flow stress equation is proposed for C – Mn – Si – Al steels microalloyed with up to 0.02 % Nb. The effects of alloying and microalloying are then estimated. A new fitting parameter shows excellent agreement with the mean flow stress data from industrial processing of advanced high strength microalloyed steels. However, during the second half of the rolling schedule (lower temperature region), indications of austeniteto- ferrite transformation were found.

Modeling of the Microstructural Evolution and Mean Flow Stress during Thin Slab Casting/Direct Rolling of Niobium Microalloyed Steels

2005 ◽  
Vol 500-501 ◽  
pp. 221-228 ◽  
Author(s):  
Fulvio Siciliano ◽  
L.L. Leduc
Keyword(s):  
Flow Stress ◽  
Microalloyed Steels ◽  
Hot Strip Mill ◽  
Thin Slab ◽  
Mean Flow ◽  
Thin Slab Casting ◽  
Slab Casting ◽  
Mean Flow Stress ◽  
Direct Rolling ◽  
The Mean

Mill logs obtained from the Hylsa CSPTM (thin slab casting/direct rolling – TSC/DR) mill were examined so that the mean flow stresses at each pass were calculated using the Sims equation modified to take into account the forward slip ratio, the redundant strain and the work roll flattening. The mean flow stresses were then compared to predicted values obtained from a model. The microstructures during the CSP process were predicted by a mathematical model which was initially derived for conventional slab/roughing mill/hot strip mill (HSM) processing route. The adapted model takes into account the deformation of the as-cast structure in the finishing CSP mill, by using particular microstructural equations to calculate the softening kinetics and grain sizes. The main metallurgical features such as the occurrence of Nb(C,N) precipitation, the softening mechanism which takes place (static or metadynamic recrystallization) as well as the strain accumulation between passes were calculated. The mean-flow-stress results obtained from the calculations are in good agreement with the mill data. The present analysis indicates that it is possible to produce fine-grained microalloyed steels with homogeneous microstructure in thin slab casting/direct rolling processing.

scholarly journals Convective Pattern Deformations under Mean Flow Stress

1987 ◽  
Vol 4 (2) ◽  
pp. 253-253 ◽  
Author(s):  
A Pocheau ◽  
V Croquette ◽  
P. Le Gal ◽  
C Poitou
Keyword(s):  
Flow Stress ◽  
Mean Flow ◽  
Mean Flow Stress ◽  
Convective Pattern

MATHEMATICAL-ARTIFICIAL NEURAL NETWORK HYBRID MODEL TO PREDICT ROLL FORCE DURING HOT ROLLING OF STEEL

2013 ◽  
Vol 02 (01) ◽  
pp. 1350004 ◽  
Author(s):  
S. RATH ◽  
P. P. SENGUPTA ◽  
A. P. SINGH ◽  
A. K. MARIK ◽  
P. TALUKDAR
Keyword(s):  
Neural Network ◽  
Mathematical Model ◽  
Artificial Neural Network ◽  
Flow Stress ◽  
Mathematical Models ◽  
Hybrid Model ◽  
Data Driven ◽  
Roll Force ◽  
Hot Strip ◽  
Artificial Neural

Accurate prediction of roll force during hot strip rolling is essential for model based operation of hot strip mills. Traditionally, mathematical models based on theory of plastic deformation have been used for prediction of roll force. In the last decade, data driven models like artificial neural network have been tried for prediction of roll force. Pure mathematical models have accuracy limitations whereas data driven models have difficulty in convergence when applied to industrial conditions. Hybrid models by integrating the traditional mathematical formulations and data driven methods are being developed in different parts of world. This paper discusses the methodology of development of an innovative hybrid mathematical-artificial neural network model. In mathematical model, the most important factor influencing accuracy is flow stress of steel. Coefficients of standard flow stress equation, calculated by parameter estimation technique, have been used in the model. The hybrid model has been trained and validated with input and output data collected from finishing stands of Hot Strip Mill, Bokaro Steel Plant, India. It has been found that the model accuracy has been improved with use of hybrid model, over the traditional mathematical model.

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