A Data-Driven Approach to Predict the Extent of Surface Oxidation During Hot-Rolling and Annealing of New Steels
A Data-Driven Approach to Predict the Extent of Surface Oxidation During Hot-Rolling and Annealing of New Steels
批准号:
2822991
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
未结题
起止时间:
2020 至 --
中文摘要
该项目的目的是为预测高强度扁钢产品在热处理过程中形成的表面氧化物的性质和程度提供一个深刻的模型。这些预测将适用于各种各样的工业条件,并考虑EPSRC繁荣合作伙伴项目中合作行业之间的影响。除了对结果的预测不确定性进行量化外,该理论模型还将用于根据最佳表面质量提出汽车钢的最佳制造路线。因此,该项目与EPSRC的“工程”和“未来制造”优先领域重叠。
英文摘要
The aim of this project is to deliver a profound model for the prediction of both the nature and extent of surface oxides that have been formed during the heat treatments of high strength flat steel products. The predictions will be applicable to a wide variety of industrial conditions and consider effects between the partnered industries within the EPSRC Prosperity partnership project. In addition to a quantification of the result's predictive uncertainty, the theoretical model will be used to propose an optimum manufacturing route for automotive steels in view of an optimum surface quality. The project hence overlaps with the EPSRC priority areas of "Engineering" and "Manufacturing of the Future".
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国内基金
海外基金
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
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批准号:--
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项目类别:外国青年学者研究基金项目
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资助金额:--
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批准年份:2024
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负责人:江洋子
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依托单位: