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Artificial Neural Networks Approach for Ductility Prediction of Copper Cold Spray Laser Heat Treated Coatings

Artificial Neural Networks Approach for Ductility Prediction of Copper Cold Spray Laser Heat Treated Coatings
人工神经网络方法预测铜冷喷涂激光热处理涂层的延展性
批准号:
567502-2021
负责人:
Jodoin, Bertrand
金额:
$2.19万
依托单位:
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2021
资助国家:
加拿大
项目状态:
已结题
起止时间:
2021-01-01 至 2022-12-31

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中文摘要
翻译
加拿大有300多万个核用燃料束(UFBs)作为核电站发电的副产品,今后每年将产生超过12万个UFBs。该伙伴关系的目标是以协同的方式利用渥太华大学和国家研究中心现有的知识和资源,以支持核废物管理组织(NWMO)寻求使用冷喷涂(CS)添加剂制造(CSAM)来开发创新的旧燃料容器(UFC)。该项目是NWMO广泛研发计划的一部分,该计划将确保将不明飞行物安全储存在深层地质储存库中,取代地面上的短期储存地点。应使用铜涂层覆盖焊接闭合区(UFC主体和闭合端盖之间的焊接接头),以保护UFC的腐蚀。该项目将使涂层达到所需的延展性,以符合它可能在多年中遇到的外力,而不会导致燃料电池外的放射性材料出现裂缝和泄漏。这将通过开发激光热处理来实现,该激光热处理将使用经过训练的神经网络模型来设计,该模型能够将激光参数与所产生的延展性(输入-输出)相关联。除了创造新的基础知识/培训高素质的人员外,该项目的具体成果将是开发一种新的快速激光热处理(HT)技术,用于厚CSAM铜涂层(用于UFC),以确保安全使用的最低延展性为10%。这项工作将对NWMO提出的深层储存库的UFC设计可行性产生直接影响。此外,它还将创造关于激光高温超导的新知识,这些知识可以适用于对加拿大重要的工业领域,如航空航天和汽车。
英文摘要
There is over 3 million nuclear used fuel bundles (UFBs) in Canada as by-products of electricity production by nuclear power plants and over 120,000 UFBs will be generated per year going forward. The goal of the partnership is to use in a synergetic approach existing knowledge and resources available at uOttawa and NRC to support The Nuclear Waste Management Organization (NWMO) in its quest to use cold spray (CS) additive manufacturing (CSAM) in the development of innovative used fuel container (UFC). The project is part of the NWMO extensive research and development program that will ensure the safe storage of UFBs in UFCs in deep geological repositories, replacing short-term above ground storage sites. Copper coating are to be used to cover the weld closure zone (welded junction between the main UFC body and the closing end cap) for corrosion protection of the UFCs. The project will allow achieving the coating ductility required to comply with external forces that it could encounter over the years without resulting in cracks and leaks of the radioactive material outside the UFCs. This will be achieved through the development of a laser heat treatment that will be designed using a trained neural network model able to correlate the laser parameters to the resulting ductility (input-output). In addition to the creation of new fundamental knowledge/training of highly qualified personnel, the project specific outcome will be the development of a new fast laser heat treatment (HT) on thick CSAM copper coatings (used on UFCs) to ensure a minimum ductility of 10% for safe usage. The work will have a direct impact on the UFC design viability proposed by NWMO for deep ground repository. Furthermore, it will create new knowledge on laser HT that can be adapted to industrial fields important to Canada such as aerospace and automotive.
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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    RGPIN-2017-04671
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
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  • 财政年份:
    2020
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  • 项目类别:
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  • 资助金额:
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国内基金
海外基金
Neural Process模型的多样化高保真技术研究