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Through Process Modelling for Sustainable Aluminium

Through Process Modelling for Sustainable Aluminium
通过可持续铝的流程建模
批准号:
2386020
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:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --

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中文摘要
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英文摘要
Innoval is a UK based company that provides a unique resource of independent expertise to the global aluminium industry (producers and users). The company is a key partner in enabling sustainable, cost effective aluminium alloy production, for use in applications such as automotive, aerospace, and packaging.Innoval have a particular expertise in developing models to predict the evolution of the structure and properties through the complex process chain that aluminium alloys experience. Models are critical to optimize the processing of aluminium alloys and enable the use of greater recycled content, thus moving towards fully closed loop recycling of aluminium. Innoval have developed a library of models for different parts of the process chain, but these models are not connected. This means it is not possible to predict through process microstructure and performance. The aim of this EngD is to take the existing models and couple them to enable a through process simulation capability. To do this, experimental validation will be required at each step, and additional models may be needed to be developed.The project will therefore involve a combination of computer based modelling and experimental validation of models using advanced techniques such as electron microscopy. The project will involve spending time at Manchester and at Innoval's UK facilty (Banbury). It will also require international travel.Through the EngD you will gain an in-depth knowledge of, and exposure to, the aluminium industry. This is a rapidly growing field with increasing opportunities due to the benefits of aluminium in lightweighting. On completing the project, you will have a combination of computer modelling and experimental skills that are in strong demand by employers. Candidates are sought with a background in materials science, engineering, physics, or chemistry.
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海外基金
Neural Process模型的多样化高保真技术研究
磁转动超新星爆发中weak r-process的关键核反应
多臂Bandit process中的Bayes非参数方法
  • 批准号:
    71771089
  • 项目类别:
    面上项目
  • 资助金额:
    48.0万元
  • 批准年份:
    2017
  • 负责人:
    吴贤毅
  • 依托单位: