Model For Hot Rolling Research Articles

Investigation of Si, Mn, and C interactions during coiling of hot rolling model alloys

Model alloys were developed to investigate the interaction of Mn, Si, and C during hot rolling. The alloy samples prepared by the method of vacuum-sealed tube heat treatment exhibited unique microstructural features: surface reduced Fe layer, interface reduced Fe layer and internal oxidation layer. The experimental results revealed that scale reduction is mainly controlled by the effect of Si and decarburization behavior, as well as the contribution of Si is more significant. The competing reactions of decarburization substantially reduce the depth of internal oxidation of the alloy. Additionally, combination of Mn and Si greatly facilitated the process of internal oxidation, with Si playing a role in inducing the inward oxidation of Mn. These insights will contribute to a better understanding of hot rolling coiling process, especially the complex interactions of Mn, Si, and C.

Integration of a void healing criterion in multi-scale modeling of hot rolling

After closure, voids need to be healed through bonding and interface dissolution to restore the mechanical properties and produce a sound product. For the prediction of void healing and the respective process optimization, a void healing criterion, spanning all three phases is needed. While hot rolling is generally suited for void healing, with large deformations at hydrostatic pressure as well as high temperatures, not all regions in the workpiece offer the same void healing conditions. Due to gradients of these metrics e. g. along the normal direction, a space-resolved approach is needed. Previously, a practical void healing criterion combining void closure and subsequent recrystallization has been proposed and applied to exemplary hot rolling processes. Besides a broader application of the criterion, adding the process parameters roll diameter and temperature, the present paper mainly aims for the experimental validation of this criterion. In bonding trials, a positive influence of temperature and strain on the bond strength has been found. While no clear correlation of the holding time on the bond strength was detectible without concurrent contact pressure the experiments suggested a saturation strain as an indicator for void healing instead. Accordingly, the criterion has been revised and a strain-based criterion proposed, applied, and compared to the previously introduced recrystallization-based void healing criterion.

Finite Element Modeling of Hot Rolling of 1075 Carbon Steel Process with Variable Cross Section

Currently, it is common to use steel poles for applications in livestock and agriculture. In this work, finite element analysis of five hot rolling passes for the manufacture of farm poles using 1075 carbon steels from recycled railway material was developed. The steel industry in Mexico imports products from other countries or from companies specialized in metallurgy at an excessive cost. To be more competitive and save costs, companies seek the reutilization of existing resources such as the railway 1075 steel, which has good mechanical properties. SFTC DEFORM-3D software was used to model five hot rolling passes considering a variable cross section railway profile. The effect of rolling speed and temperature were considered to analyze flow behavior. Rolling loads were also determined.

Theoretical Model and Experimental Study of Dynamic Hot Rolling

At present, the commonly used hot rolling model is only applicable to the static rolling process. However, to study the dynamic rolling process, a dynamic rolling model with roll vertical movement velocity parameters is required. In this study, the influence of the vertical movement velocity of the rolls on the rolling process is considered, and a dynamic rolling process model is proposed when the roll gap is reduced during the hot rolling dynamic rolling process. Mathematically, the model is based on the upper limit method. The model considers the influence of the dynamic rolling process on the length of the deformation zone, establishes a dynamic velocity field model and an average deformation rate model, and then solves the total power of the rolling process. Finally, the dynamic rolling force equation is given. Compared with the experimental results, the dynamic rolling model in this paper has high accuracy with an average error of 4%. In addition, the influence of roll vertical velocity on rolling parameters is discussed, which provides a basis for the study of the dynamic rolling process.

Dynamic rolling model based on uniform deformation

Abstract Accurate prediction of rolling force is a core point during the hot-rolled strip production. In-depth research on static rolling processes has been carried out in the past. Most models, however, can only be used under static conditions. Therefore, it is challenging to research the dynamic rolling process. This paper presents a dynamic rolling model for hot rolling. Firstly, the strip dynamic velocity model and the dynamic boundary condition model are established, and then the total power equation of the dynamic rolling process is solved based on the energy method. Furthermore, by minimizing the total power function, the dynamic rolling force equation can be obtained. Finally, the effectiveness of the proposed dynamic model is verified by hot strip rolling plant experiments and finite element simulations. The results show that the dynamic model of this paper has higher prediction accuracy and can be applied to the research on the dynamic hot rolling process. Besides, the influence of the vertical velocity of the rolls on the dynamic rolling force and influencing factors of dynamic rolling force are discussed.

Hybrid Model of Mathematical and Neural Network Formulations for Rolling Force and Temperature Prediction in Hot Rolling Processes

Steelmaking requires precise calculation at several steps of the manufacturing processes. We focus on the hot rolling process using Steckel mills, almost the end step in steel coil manufacturing. The rolling process is a type of plastic working in which a slab passes between two rolls and is stretched to reach the target thickness. It is necessary to predetermine the exact rolling force to obtain a coil with an accurate thickness after the rolling process. First, we introduced a machine learning model for calculating the rolling force, which can be used in-line in real plants. However, a direct calculation of the rolling force can cause stability problems, because the model output directly affects the process. In order to avoid such a problem, we determined a special temperature of the coil by inverse calculation of the classical mechanical model of hot rolling and set it as the model output value. As learning models, deep neural networks (DNN) and gradient boosting-based decision tree models were used. We preprocessed the collected process history data and added artificial features to the model input by creating physical variables used in the classical models. Moreover, to supplement the black-box nature of DNN, feature importance was analyzed from the decision tree model, and utilization and interpretation of each feature in the process are presented. Thus, our methods take advantage of both the classical mathematical model and the deep neural network model.

Model and Algorithm for Planning Hot-Rolled Batch Processing under Time-of-Use Electricity Pricing

Batch-type hot rolling planning highly affects electricity costs in a steel plant, but previous research models seldom considered time-of-use (TOU) electricity pricing. Based on an analysis of the hot-rolling process and TOU electricity pricing, a batch-processing plan optimization model for hot rolling was established, using an objective function with the goal of minimizing the total penalty incurred by the differences in width, thickness, and hardness among adjacent slabs, as well as the electricity cost of the rolling process. A method was provided to solve the model through improved genetic algorithm. An analysis of the batch processing of the hot rolling of 240 slabs of different sizes at a steel plant proved the effectiveness of the proposed model. Compared to the man–machine interaction model and the model in which TOU electricity pricing was not considered, the batch-processing model that included TOU electricity pricing produced significantly better results with respect to both product quality and power consumption.

P.691 Impairment of the process of thinking on different stages of schizophrenia in connection with the magnocellular and the parvocellularneural systems

Accurate prediction of rolling force is a core point during the hot-rolled strip production. In-depth research on static rolling processes has been carried out in the past. Most models, however, can only be used under static conditions. Therefore, it is challenging to research the dynamic rolling process. This paper presents a dynamic rolling model for hot rolling. Firstly, the strip dynamic velocity model and the dynamic boundary condition model are established, and then the total power equation of the dynamic rolling process is solved based on the energy method. Furthermore, by minimizing the total power function, the dynamic rolling force equation can be obtained. Finally, the effectiveness of the proposed dynamic model is verified by hot strip rolling plant experiments and finite element simulations. The results show that the dynamic model of this paper has higher prediction accuracy and can be applied to the research on the dynamic hot rolling process. Besides, the influence of the vertical velocity of the rolls on the dynamic rolling force and influencing factors of dynamic rolling force are discussed.

Reheat Furnace Thermodynamic, Kinetic and Combustion Considerations for TMCP Processing

The reheat furnace process step has a profound effect on the TMCP performance, final hot rolled steel quality and mechanical property consistency during the production of hot rolled steels. The uniformity of heating applied across the entire width and length of the slab or billet is critical in the achievement of customer properties regardless of the chemistry. The resultant ferrite grain size in the final hot rolled product is significantly governed by the initial prior austenite grain size. Numerous reheat furnace process metallurgy and combustion parameters in actual operation affect mill productivity, microstructure, austenite grain size, scrap rate and diverts. This reheating step in the steelmaking process often receives low priority in the evaluation of product quality and mechanical property performance, especially the toughness through the plate thickness. Heat transfer conditions of radiation, convection and conduction affect furnace heating efficiency. In laboratory studies, the furnace heating step is typically quite uniform resulting in a homogeneous and fine prior austenite grain size. During production, it is much more difficult to control the uniformity of heating and heat transfer consistency along the entire length and through the thickness of the work piece. The furnace conditions are correlated to product quality via furnace process variables such as the air to gas ratio, furnace burner condition, furnace pressure, energy efficiency, adiabatic flame temperature (AFT) and furnace refractory condition. Operational practice recommendations are presented to minimize inhomogeneous heating which results in inferior product quality, hot rolling model anomalies and toughness variations in the through-thickness-direction.

Modeling and Simulation of Dynamic Recrystallization Behavior in Alloyed Steel 15V38 during Hot Rolling

Dynamic recrystallization (DRX) occurring during hot rolling significantly affects the microstructural evolution and final mechanical properties of steel. In this study, single hot compression tests are performed at temperatures between 1000 and 1300 °C with strain rates between 0.01 and 15 s−1 to investigate dynamic recrystallization behavior of a 15V38 steel. Critical strains for initiation of dynamic recrystallization and peak strains are identified through the analysis of work hardening rate from the measured stress–strain results. Dynamic recrystallization is identified by the softening in the flow stress during plastic deformation and quantified as the difference between a calculated dynamic recovery curve and the measured stress–strain curve. Dynamic recrystallization is modeled using calculated critical strain, peak strain, Zener‐Hollomon (Z) parameter, and volume fraction of dynamic recrystallization. Subroutines accounting for dynamic recrystallization are developed and implemented into a three‐dimensional finite element model for hot rolling of a round bar. Simulation results show that dynamic recrystallization is distributed throughout the bar and exhibits a positive relationship with equivalent plastic strain. Temperature effects on dynamic recrystallization are also investigated using different rolling temperatures, and results show that the fraction of dynamic recrystallization is significantly increased as rolling temperature increases.

Effect of Internal Stress of Incoming Strip on Hot Rolling Deformation Based on Finite Element and Infinite Element Coupling Method

Limited by the deficiency of the finite element method (FEM) to deal with infinite domain problems, the traditional FEM rolling model is not suitable enough to study the effect of the complex internal stress of the incoming strip on hot rolling deformation. To solve this problem, the finite element and infinite element (FE-IE) coupling method is adopted, where the finite element is for the rolling area of the strip and the infinite element is for the elastic constraint of the strip end. Based on the improved rolls-strip coupling model, several internal stresses with typical distribution forms are applied to the strip by a programmed user subroutine, and the effect of the internal stress of the incoming strip on hot rolling deformation is evaluated. The results show that under the same average stress, the various distribution forms of internal stress have little effect on the total roll force, mainly because of the average effect. The uniform internal stress decreases the central thickness and quadratic crown of the strip. Under the symmetric stress and asymmetric stress, the thickness of each fiber along the strip width direction is closely related to the magnitude and distribution of the stress deviation (subtract the average stress from the longitudinal stress). Under the quadratic wave stress, the central thickness and quadratic crown vary almost linearly with the amplitude of the stress deviation. The efficiency coefficients obtained can be treated as a theoretical basis for the further development of an accurate prediction model of hot rolling.

Physical Modelling of Hot Rolling for Low-Density Alloy of the Al–Mg–Li–Zr–Zn–Sc System

Results are given for physical modeling of hot rolling of alloy with reduced density of the Al–Mg–Li–Zr–Zn–Sc system (1424) in the temperature range 420–480° and deformation rate 1–40 sec–1. It is established that with a constant strain rate deformation stresses decrease with an increase in test temperature. An increase in strain rate leads to an increase in deformation stress at constant temperature. As a result of dynamic recovery and dynamic recrystallization, there is partial weakening of specimens accompanied by a reduction if deformation stress. Constants are determined for a rheological model of hot deformation, increase the Zener–Hollomon parameter and the rule of a hyperbolic sine: α = 0.023 MPа–1, n = 1.96, Q = 101.04 kJ/mole, А = 1.22·106 sec–1. It is shown that alloying with scandium reduces activation energy which leads to weak strain hardening and this means it provides good alloy 1424 production properties.

Hot Rolling of a Non-heat Treatable Aluminum Alloy: Thermo-Mechanical and Microstructure Evolution Model

A transient thermo-mechanically coupled Finite Element Method based model for single pass hot rolling of AA 5083 aluminum alloy is developed. The formulation is based on thermo-viscoplastic behavior expressed by the Perzyna constitutive equation and rolling under plane-strain conditions. The finite element model is integrated with a microstructural model where dynamic recrystallization through particle stimulated nucleation and static recrystallization is considered. The dynamic recrystallization model is an adoption of discontinuous dynamic recrystallization model while static recrystallization model is based on Avrami equation. The simulation results indicate that accurate estimates of constitutive behavior of the alloy, efficiency of conversion of plastic deformation to heat, and heat transfer at the roll/metal interface are critical for precise hot rolling model.

Flow behavior and deformation of Nb micro-alloyed steel during strip hot rolling

In this paper, the material parameters of the Johnson Cook material model were determined and analyzed. Then, the flow curves were obtained by thermal simulation machine during the hot compression deformation process. The experimental data over a wide range of temperatures (1173 K–1373 K), strain (0.1–0.5) and strain rates (0.001–10 s-1) were employed to evaluate the material constants of Johnson Cook constitutive models. The flow stress predicted by the Johnson Cook equation was the same as the experimental result. Afterward, the new verification testing and 3D finite element compression model was established, which showed the reliability of the constitutive equation. The finite element simulation results show that the calculated deformed shape and the compressive stress-strain curves of the specimens were consistent with the experiment. The effectiveness and feasibility of the constitutive equations in the finite element calculations were proved. The equation supplied a flow stress model for rolling simulation calculation. Then, the 3-pass vertical-horizontal hot rolling model was established by Abaqus/Explicit. The simulation results agree with the measured values of the hot strip rolling.

Conventional and Multiscale Modeling of Microstructure Evolution During Laminar Cooling of DP Steel Strips

Abstract Physical and numerical simulations of the hot rolling and laminar cooling of DP steel strips are presented in the paper. The objectives of the paper were twofold. Physical simulations of hot plastic deformation were used to identify and validate numerical models. Validated models were applied to simulate the manufacturing of DP steel strips. Conventional flow stress model and microstructure evolution model were used in the hot deformation part. The approach to the complex systems analysis based on global thermodynamic characterization and detailed microstructure characterization was applied to determine equilibrium state at various temperatures. Finally, two numerical models were used to simulate kinetics of austenite decomposition at varying temperatures: the first, conventional model based on the Avrami equation, and the second, the discrete Cellular Automata approach. Plastometric tests and stress relaxation tests were used for identification of the hot rolling model for the DP steel. Dilatometric tests were performed to identify the phase transformation models. Verification confirmed good accuracy of all models. Validated models were applied to simulate the manufacturing of DP steel strips. Influence of technological parameters (e.g., strip thickness and velocity, active sections in the laminar cooling, and water flux in the sections) on the DP microstructure was analyzed. The cooling schedules, which give required microstructures were proposed. The numerical tool, which simulates manufacturing chain for DP steel strips is the main output of the paper.

Mathematical Modelling of Hot Rolling: A Practical Tool to Improve Rolling Schedules and Steel Properties

Most of the commercial metallic materials undergo at least one hot deformation stage during fabrication. Hot deformation processing leads to the production of plates, strips, rods, pipes and other shapes at lower overall cost when compared to the cold deformation/annealing route. Comprehensive study of the metallurgical phenomena during hot deformation has enormous potential application in the control of industrial rolling processes. Understanding of the microstructural and mean flow stress evolution lead to sound steel developments and innovative rolling schedules. The models predict parameters such as grain size, fractional softening (static and dynamic) and strain induced precipitation which are useful to improve rolling schedules. Effects such as incomplete softening and strain accumulation can be easily detected as well as their consequences on the final grain size and mechanical properties. In this regard, special attention must be given to steels, the most important metallic material in terms of history, present and future. In this paper, three hot rolling routes will be analyzed in order to produce high strength linepipe steels. Examples were selected on how the use of modelling during development stage can help to meet mechanical properties, mainly toughness and drop weight tear test. Firstly, it is presented a brief overview on mathematical models applied to hot rolling. Thin slab casting/direct rolling, hot strip mill and plate mill are exemplified in the present work. The development of new steel grades can greatly accelerated with the aid of modelling, which is an useful, low-cost technique.

Microstructure evolution modeling of titanium alloy large ring in hot ring rolling

Exploration of microstructure evolution is of significance for manufacturing the large ring with high performance and high reliability in hot ring rolling. In the study, the microstructure evolution model and the rate-/temperature-/microstructure-dependent constitutive model of titanium alloy are implemented in ABAQUS/Explicit through the user material subroutine VUMAT. The developed subroutine is validated by single-element models and isothermal upsetting experiments of Ti–6Al–4V cylinder. The subroutine is imbedded into a coupled thermomechanical three-dimensional finite element (3D-FE) model for hot rolling of Ti–6Al–4V large ring. The evolution characteristics of β phase volume fraction and grain size of Ti–6Al–4V during the process are revealed, and the final microstructures of the large ring under different processing conditions are explored. The results obtained show that (1) microstructure evolution follows the trend with the process progressing: the fine grain zone transfers from the surface layer (SL) to the middle layer (ML) of the ring; the poor β zone extends from the outside of the SL to the end-plane of the ML, and the rich β zone always locates at the SL. (2) decreasing the rotational velocity of the driver roll n1, or increasing the feed rate of the idle roll v or the initial temperature of the ring T0 contributes to more uniform distributions of β phase and its grain size, but results in the increase of the β phase volume fraction and grain size.

FE Analysis of Spread in Hot Rolling of Large Rings with Different Sizes

How to effectively reduce spread is an important subject in the area of ring rolling. In the paper, a reliable coupled thermo-mechanical three-dimensional (3D) finite element (FE) model for hot rolling of large rings is developed. The relationship between spread and the equivalent shape parameters of the deformation zone is discussed. Variations of spread with relative reduction Rr during hot rolling of titanium alloy large rings with different sizes are analyzed and compared using FE simulation. The main results reveal that (1) the spread in a ring exhibits an axisymmetric distribution after the first revolution of the ring. (2) the peak spread appears in the inside or outside layer of a ring, and the minimum spread is found in the middle layer. (2) as Rr increases, the spread increases and the end-plane quality of the ring reduces.

Axial Spread Evolution during Hot Rolling of Large Rings with Different Sizes

For ring rolling without axial rolls, how to effectively suppress axial spread has become an important subject. In the paper, a reliable coupled thermo-mechanical three-dimensional (3D) finite element (FE) model for hot rolling of large rings is developed. Spread evolution of titanium alloy large rings with different sizes are explored and compared based the developed model. The main results show that (1) the spread in a ring takes on an axisymmetric distribution after the first revolution of the ring. (2) with the equivalent ratio of feed amount per revolution decreasing, the peak spread transfers from the outer layer to the inner layer for rings with different sizes.

Rolling force prediction for strip casting using theoretical model and artificial intelligence

Rolling force for strip casting of 1Cr17 ferritic stainless steel was predicted using theoretical model and artificial intelligence. Solution zone was classified into two parts by kiss point position during casting strip. Navier-Stokes equation in fluid mechanics and stream function were introduced to analyze the rheological property of liquid zone and mushy zone, and deduce the analytic equation of unit compression stress distribution. The traditional hot rolling model was still used in the solid zone. Neural networks based on feedforward training algorithm in Bayesian regularization were introduced to build model for kiss point position. The results show that calculation accuracy for verification data of 94.67% is in the range of ±7.0%, which indicates that the predicting accuracy of this model is very high.