Mathematical Modelling of the Flow in High-Turbulence Roll Cooling (HTRC)
Mathematical Modelling of the Flow in High-Turbulence Roll Cooling (HTRC)
批准号:
515497-2017
负责人:
Kocaefe, Duygu
金额:
$1.82万
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2017
资助国家:
加拿大
项目状态:
已结题
起止时间:
2017-01-01 至 2018-12-31
中文摘要
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英文摘要
ArcelorMittal Dofasco is one of the North America's advanced steel manufacturers working with the topautomotive, energy, packaging, and construction brands to develop lighter, stronger, and more sustainableproducts - from cans to cars. Founded in 1912, ArcelorMittal Dofasco is Hamilton's (ON) largest private sectoremployer with more than 5,000 employees shipping 5 million short tons of high quality flat carbon steelannually.Hot rolling is one of the key steps of steel manufacturing. In this process, hot metal slabs pass between rollswith the objective of decreasing their size and obtaining a strip with uniform thickness. During this process,rolls have to be cooled continuously. High roll temperatures result in early wear/tear and breakdown of rollsdue to the thermal stresses as well as the degradation of product surface quality. Nowadays, mills are trying toincrease their throughput. However, increasing throughput results in higher roll temperatures with theconventional cooling system. In order to increase the cooling efficiency, CRM (Centre RechercheMétallurgique-Gent, Belgium) and ArcelorMittal Gent developed an innovative technology called HighTurbulence Roll Cooling (HTRC). Utilization of this system significantly improved the cooling. However, allthe design and operational parameters of this system are not yet optimized.In this project, a 3D, two-phase, steady-state model of the flow in HTRC will be developed with the objectiveof investigating the effects of different design and operational parameters (number, size, and distribution ofnozzles, water flow rate, header spacer thickness, roll diameter, etc.) on HTRC operation and, consequently,identifying the best parameters which will lead to better cooling conditions and product quality at lower cost.The model will be validated with the mill data.
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