A novel analytical model for prediction of rolling force in hot strip rolling based on tangent velocity field and MY criterion

Li, Si; Wang, Zhigang; Guo, Yufei

doi:10.1016/j.jmapro.2019.09.037

Cited by 23 publications

(8 citation statements)

References 26 publications

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“…Based on a tangent velocity and the linear mean yield (MY) criterion, Li S et. al [15] predicted the rolling force in hot strip rolling process and compared the result with the experimental data.…”

Section: Introductionmentioning

confidence: 99%

Analysis of 3D plastic deformation in vertical rolling based on global weighted velocity field

Yang

2022

Int J Adv Manuf Technol

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Energy method is an essential theoretical approach to analyze plastic forming, which is widely used in rolling. An analysis model for vertical rolling process is established according to energy theory. By using global weighted method firstly, the 3D continuous velocity field, strain rate field and the corresponding power functional are proposed. The unknown variables are solved numerically based on the principle of minimum energy. Then, deformation parameters and rolling force are determined. The analysis on specific examples with the width reduction rate of 0.03~0.05 shows that the theoretical prediction value of weighted model is in good agreement with experimental results. Moreover, the effects of several shape and rolling parameters on rolling force, rolling power and edge deformation are studied. Both the width reduction rate and initial slab thickness have significant influences on dog-bone size and rolling force. A wider slab slightly increases the nonuniformity of dog-bone deformation. An increase of vertical roller radius can weaken the edge deformation.

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Section: Introductionmentioning

confidence: 99%

Analysis of 3D plastic deformation in vertical rolling based on global weighted velocity field

Yang

2022

Int J Adv Manuf Technol

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“…Li at al. [29] proposed novel analytical model for the prediction of rolling force in hot strip rolling based on tangent velocity field and mean yield criterion. The prediction error varied in the range of 1-5%.…”

Section: Roll Force and Torque Model Using Machine Learningmentioning

confidence: 99%

Application of Machine Learning Methods for the Prediction of Roll Force and Torque during Plate Rolling of Micro-alloyed Steel

Thakur¹,

Das

Jha³

2022

Preprint

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Machine learning technique is extensively used to establish the relationship between non-linear data sets which cannot be described mathematically and thus an exact analytic model is either intractable or too time-consuming to develop. During hot rolling, the effect of process parameters that cannot be captured in mathematical models, such as roll dimensions and its wear, the inter-pass time between rolling passes, temperature variation has been incorporated using multivariate supervised machine learning technique for accurate prediction of roll force and torque during plate rolling of micro-alloyed steel. An ensemble method was used to combine various machine learning techniques and average them to develop one final predictive model. K-cross validation of the model was carried out to validate the results and ensure the model gets the correct pattern of data. Root mean square error of ensemble roll force model was compared with roll force calculation using Sims theory. It was found that the machine learning model can predict the roll force and torque accurately as it takes care of various non-linear process variables which cannot be accounted for mathematically. The R-value of the machine learning model was > 98%, whereas it was 92.2% for roll force calculation using Sims theory.

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“…Based on the geometric equation [21] of the relationship between strain rate and displacement velocity, v yIII is obtained as follows:…”

Section: Velocity Fieldmentioning

confidence: 99%

A novel approach for the edge rolling force and dog-bone shape by combination of slip-line and exponent velocity field

Zhang

Ling

et al. 2020

SN Appl. Sci.

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This study presents a new mathematical model for edge rolling force and dog-bone shape using the combination of slip-line and exponent velocity field. The slip-line field of the dog-bone area is drawn out based on the deformation characteristics of edge rolling and the maximal depth of dog-bone zone is determined. Then a new exponent velocity field and corresponding strain rate field which satisfy kinematically admissible condition are proposed to analyze the edge rolling force based on upper bound approach. The upper bound solutions of dog-bone shape and rolling force are obtained by minimizing the total power which contains the internal plastic power, frictional and shear powers. The effects of reduction rate, initial thickness and roll radius on dog-bone shape size and edge rolling force are discussed. The results obtained by the combined solution in this paper are compared with measured data in strip hot rolling field and finite element method (FEM) simulation results, and a good agreement is found. Keywords Combined solution of edge rolling force • Slip-line field • Dog-bone shape • Exponent velocity field • Upper bound approach • FEM

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A novel analytical model for prediction of rolling force in hot strip rolling based on tangent velocity field and MY criterion

Cited by 23 publications

References 26 publications

Analysis of 3D plastic deformation in vertical rolling based on global weighted velocity field

Analysis of 3D plastic deformation in vertical rolling based on global weighted velocity field

Application of Machine Learning Methods for the Prediction of Roll Force and Torque during Plate Rolling of Micro-alloyed Steel

A novel approach for the edge rolling force and dog-bone shape by combination of slip-line and exponent velocity field

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