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Integrated Computational Materials Engineering of Next Generation Aluminum and Magnesium Alloys

Integrated Computational Materials Engineering of Next Generation Aluminum and Magnesium Alloys
下一代铝镁合金集成计算材料工程
批准号:
RGPIN-2019-04043
负责人:
Poole, Warren
金额:
$4.01万
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

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The proposed research program will lead the global Integrated Computational Materials Engineering (ICME) field to replace lengthy, costly, trial-and-error-driven R&D with digital simulation-of materials properties, manufacturing processes, and responses to those processes. This evolution is key to accelerating the insertion of stronger, safer, lighter-weight materials into the transportation sector, which contributes 4.7% of GDP or $94b CAD to the Canadian economy. What sets the current research program apart is the focus on chemistry-dependent models, spatial resolved microstructure (both at the grain level, i.e. 10 of µm's and the part scale, i.e. mm's), and the close linkage between the foundational research and industrial application of the knowledge. The challenges of chemistry dependence, spatial variation of microstructure, and history dependence noted above dictate that a holistic digital building-block approach is needed to link the different manufacturing processes together. The objective of this work is to produce through process (ICME) models to accelerate the insertion of the next generation of high strength and toughness aluminum and magnesium alloys into applications in the transportation sector. The proposed methodology requires a combination of state-of-the-art modeling and simulation tools and advanced characterization tools, including combinatorial studies and high-efficiency experimental approaches. At its heart, the through process approach explicitly considers the linkages between processes. From the beginning, sub-models are developed with the knowledge that they must be linked together; a challenging process requiring careful planning of which variables will be inputs and outputs for each model and how those variables will be passed from one model to the next. This research program will focus on: i) high strength, high toughness aluminum alloys for the automotive industry - the aim for the next generation of aluminum alloys (Al-Mg-Zn-Cu-Zr) is strength above 400 MPa and true fracture strain >0.5 such that they can be formed to make complex parts with improved energy absorption capability for crash applications and ii) novel magnesium sheet alloys that can be formed into complex automotive parts at room temperature while reducing material cost from the current $15 per kg to less than $5 per kg. The insertion of these materials has been demonstrated to have the potential to reduce automobile weight more than 50% with outcomes which include the increased viability of alternative-fuel vehicles, reduced fossil fuel use, and reduced greenhouse gas production, all measurable contributions to a more sustainable planet. Further, 40% of Canadian manufacturers are already reporting immediate skills/labour shortages and 60% of manufacturers anticipate shortages in the next five years. As such, the education, training, and mentoring of the next generation of materials engineers will be a critical outcome for this research program.
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Through Process Modelling of Advanced Structural Materials
  • 批准号:
    CRC-2018-00331
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $14.57万
  • 财政年份:
    2022
  • 负责人:
    Poole, Warren
  • 依托单位:
Through Process Modelling Of Advanced Structural Materials
  • 批准号:
    CRC-2018-00331
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $14.57万
  • 财政年份:
    2021
  • 负责人:
    Poole, Warren
  • 依托单位:
Through process modelling of next generation heavy gauge line pipe
  • 批准号:
    566973-2021
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $6.88万
  • 财政年份:
    2021
  • 负责人:
    Poole, Warren
  • 依托单位:
Integrated Computational Materials Engineering of Next Generation Aluminum and Magnesium Alloys
  • 批准号:
    RGPIN-2019-04043
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $4.01万
  • 财政年份:
    2021
  • 负责人:
    Poole, Warren
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data