Development of a bench-scale liquid metal wiping pilot system for understanding and optimizing the jet wiping process during hot dip galvanizing

开发小型液态金属擦拭试点系统,用于了解和优化热浸镀锌过程中的喷射擦拭过程

基本信息

  • 批准号:
    565310-2021
  • 负责人:
  • 金额:
    $ 1.82万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Alliance Grants
  • 财政年份:
    2022
  • 资助国家:
    加拿大
  • 起止时间:
    2022-01-01 至 2023-12-31
  • 项目状态:
    已结题

项目摘要

In the case of hot-dip galvanizing, a continuously-moving steel strip is coated with a thin layer of zinc in orderto resist to oxidization. The protective metal is applied in its liquid state, by dipping the substrate into a bath ofcoating. However, at common strip speeds, the liquid layer dragged by the moving web is far too thick anduneven for the applications considered. The final coating thickness is therefore controlled by an air knife,which impinges a two-dimensional high-speed gas jet on the liquid layer. The forces imposed in the liquid bythe air knife jet results in the formation of a runback flow down to the bath, leaving a more uniform andconstant coating thickness dowsntream on the substrate. Nevertheless, operational constraints and processparameter variation can still result in significant coating non-uniformity and excess zinc consumption. Thisresearch program will focus on developing a bench scale galvanizing pilot where a low melting point liquidmetal will be used as an analogue to zinc and a rotating belt arrangement will be combined with an air knife tovisualize the jet wiping process in more detail. State of the art imaging techniques developed at the applicant'slaboratory will be used to visualize the wiping process, coating waviness and solution strategies will beproposed for optimizing the wiping system in terms of process parameters and air knife design. With manyexisting problems at the hot dip galvanizing lines it is difficult to meet the market demands. The results of thisproject are expected to help galvanized strip producers like AM Dofasco to determine, and control theoptimum coating properties that will allow them obtaining the highest productivity and simultaneously achievehigh quality strips with desired product quality. Proper understanding of the jet wiping process and itsinfluence on galvanized product quality has profound impacts on the commercial aspects of hot dipgalvanizing. Based on the current interests in this process optimization, and enhanced productivity (expressedby AM Dofasco hot dip galvanizing lines), an economic impact of $6 million /year is expected from the resultsof this research, which translates to $30 million within five years after completion of this project
在热浸镀锌的情况下,连续移动的钢带上涂有一层薄薄的锌,以抵抗氧化。通过将基材浸入涂层浴中,以液态施加保护金属。然而,在常见的带材速度下,移动幅材拖动的液体层对于所考虑的应用来说太厚且不均匀。因此,最终的涂层厚度由气刀控制,气刀将二维高速气体射流撞击到液体层上。气刀喷射在液体中施加的力导致形成向下流至浴液的回流,从而在基材上下游留下更均匀和恒定的涂层厚度。然而,操作限制和工艺参数变化仍然会导致显着的涂层不均匀性和过量的锌消耗。该研究计划将重点开发一种小型镀锌试点,其中将使用低熔点液态金属作为锌的类似物,并将旋转带装置与气刀相结合,以更详细地可视化喷射擦拭过程。申请人实验室开发的最先进的成像技术将用于可视化擦拭过程、涂层波纹度,并且将提出解决方案策略,以在工艺参数和气刀设计方面优化擦拭系统。热镀锌生产线存在诸多问题,难以满足市场需求。该项目的结果预计将帮助 AM Dofasco 等镀锌带材生产商确定和控制最佳涂层性能,从而使他们获得最高的生产率,同时获得具有所需产品质量的高质量带材。正确理解喷射擦拭工艺及其对镀锌产品质量的影响对热浸镀锌的商业方面具有深远的影响。基于当前对工艺优化和生产率提高的兴趣(以 AM Dofasco 热浸镀锌线表示),本研究结果预计每年产生 600 万美元的经济影响,在该项目完成后的五年内可转化为 3,000 万美元

项目成果

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Barati, MansoorM其他文献

Barati, MansoorM的其他文献

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{{ truncateString('Barati, MansoorM', 18)}}的其他基金

Innovative Low Melting Liquid Metal Model for Optimizing Argon Injection Practices during Steelmaking and Continuous Casting for Productivity and Quality Improvements
创新的低熔点液态金属模型,用于优化炼钢和连铸过程中的吹氩实践,以提高生产率和质量
  • 批准号:
    522412-2017
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Collaborative Research and Development Grants
Continuous caster mould digital twin development for fluid flow control and sliver defect minimization
用于流体流量控制和条子缺陷最小化的连铸机模具数字孪生开发
  • 批准号:
    560338-2020
  • 财政年份:
    2022
  • 资助金额:
    $ 1.82万
  • 项目类别:
    Alliance Grants

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Development of a bench-scale liquid metal wiping pilot system for understanding and optimizing the jet wiping process during hot dip galvanizing
开发小型液态金属擦拭试点系统,用于了解和优化热浸镀锌过程中的喷射擦拭过程
  • 批准号:
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    $ 1.82万
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