2012
DOI: 10.4028/www.scientific.net/kem.504-506.1043
|View full text |Cite
|
Sign up to set email alerts
|

Analysis of Roll Gap Heat Transfers in Hot Steel Strip Rolling through Roll Temperature Sensors and Heat Transfer Models

Abstract: Analysis of roll gap heat transfers in hot steel strip rolling through roll temperature sensors and heat transfer models. Key Engineering Materials, 2012Materials, , 504-506, pp.1043Materials, -1048 Abstract. This paper presents an analysis of roll bite heat transfers during pilot hot steel strip rolling. Two types of temperature sensors (drilled and slot sensors) implemented near roll surface are used with heat transfer models to identify interfacial heat flux, roll surface temperature and Heat Transfer Coe… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
10
0

Year Published

2013
2013
2019
2019

Publication Types

Select...
9

Relationship

4
5

Authors

Journals

citations
Cited by 15 publications
(10 citation statements)
references
References 3 publications
0
10
0
Order By: Relevance
“…With the ever-increasing demands on the steel industry to lower emissions and increase efficiency comes the equally demanding requirements for a higher quality product. This is leading to an increase in the number of sensors and monitoring devices used in the steelmaking process [1][2][3], whereby particular focus has been during the rolling process, where roll force, strip thickness, and even phase transformation after rolling (austenite to ferrite) can be monitored [4][5][6][7][8]. However, the conditions for higher temperature process monitoring are more challenging, for example, during casting or thermo-mechanical processing, but there is demand for real-time feedback to allow consistent and high quality steel to be produced.…”
Section: Introductionmentioning
confidence: 99%
“…With the ever-increasing demands on the steel industry to lower emissions and increase efficiency comes the equally demanding requirements for a higher quality product. This is leading to an increase in the number of sensors and monitoring devices used in the steelmaking process [1][2][3], whereby particular focus has been during the rolling process, where roll force, strip thickness, and even phase transformation after rolling (austenite to ferrite) can be monitored [4][5][6][7][8]. However, the conditions for higher temperature process monitoring are more challenging, for example, during casting or thermo-mechanical processing, but there is demand for real-time feedback to allow consistent and high quality steel to be produced.…”
Section: Introductionmentioning
confidence: 99%
“…In the field of semi-analytical inverse methods one can mention some works (elasticity and thermal problem) adapted for rolling process developed by Weisz-Patrault et al (2011, 2012a, 2013a) in 2D and Weisz-Patrault et al (2013b, 2014b in 3D. Moreover thermal experimental studies partially dedicated to the design of the measurement system have been proposed on this basis by Weisz-Patrault et al (2012b) and Legrand et al (2012Legrand et al ( , 2013. However this paper deals with a more complicated shape (cylinder with a not centered hole).…”
Section: Introductionmentioning
confidence: 96%
“…An extension in three dimensions (with several points aligned along the roll axis) has been also developed by Weisz-Patrault et al (2013b) for stresses and Weisz-Patrault et al (2014b) for temperature. Pilot tests have been performed for thermal inverse problems dedicated to heat flux determination in the roll gap by Weisz-Patrault et al (2012b) and Legrand et al (2012a) with detailed experimental apparatus (insertion of the thermocouple under the roll surface etc...) and calibration procedures, and by Legrand et al (2013) with a specific study on thermal fatigue of rolls. More recently, Weisz-Patrault (2015) proposed a semi-analytical inverse method based on conformal mapping techniques applied for latent flatness defect detection during rolling process.…”
Section: Introductionmentioning
confidence: 99%