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Modeling and exploiting the strip tension influence on surface imprinting during temper rolling of cold-rolled steel

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TLDR
In this paper, the influence of strip tension on the imprinting of surface roughness during temper rolling is analyzed based on a multi-scale FE modeling concept to explore new ways for surface Roughness control.
Abstract
To produce cold-rolled steel strips with specific mechanical properties and surface roughness typically temper rolling is adopted. In most cases, a uniform roughness pattern on the strip surface is mandatory. Due to the wear of the textured work rolls, their surface roughness ( R a ) continuously reduces during the process, which should be accounted for process control. However, conventional temper rolling systems fail to guarantee a uniform surface roughness. In this work, the influence of strip tension on the imprinting of surface roughness during temper rolling is analyzed based on a multi-scale FE modeling concept to explore new ways for surface roughness control. This is done in simulation where, a macroscopic rolling model incorporating strip tension is coupled to a mesoscopic imprinting model and both models are validated using copper rolling trials. The influence of different thickness reductions, strip tensions and incoming strip's surface roughness on imprinting is modeled and compared. The numerical results reveal that a higher strip tension decreases the roughness transfer, which presents potential to control the roughness transfer ratio without changing other process parameters like the prescribed thickness reduction in the future.

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Citations
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Assessment of steel surface roughness and waviness in relation with paint appearance.

TL;DR: In this paper, the functional behavior of the surface texture according to paint appearance was investigated. And the results showed that Fourier analysis might be the best approach to predict the appearance after painting, and this independently of the texturing process.
Posted ContentDOI

A multi-task prediction method for acid concentration based on attention-CLSTM

TL;DR: In this article , a multi-task attention convolutional long short-term memory (MACL) neural network model was proposed to predict hydrogen ion and ferrous ion concentrations simultaneously.
References
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Journal ArticleDOI

Prediction of Surface Roughness on Rolled Sheet by Texture Roll

TL;DR: In this paper, the surface roughness of a textured 2D textured surface was predicted by means of numerical simulation, which is based on the microscopic metal flow on the surface during texture rolling.
Journal ArticleDOI

Experimental and numerical investigations of the steel sheets formability with hydroforming

TL;DR: In this paper, a finite element model has been developed from data obtained through tensile tests and forming limit curves, and a newly developed hydroforming press has been used to carry out the forming experiments.
Proceedings ArticleDOI

Model Predictive Control of an Overactuated Roll Gap with a Moving Manipulated Variable

TL;DR: A complexity reduction strategy for a linear MPC used for the control of an over-actuated roll gap with two different actuator types in a cold rolling mill, which reduces the number of optimization variables as well as constraints and thus enables control of faster processes.