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Multiscale Optimization of Materials

Multiscale Optimization of Materials
材料的多尺度优化
批准号:
RGPIN-2020-04784
负责人:
Zurob, Hatem
金额:
$5.54万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2020
资助国家:
加拿大
项目状态:
已结题
起止时间:
2020-01-01 至 2021-12-31

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中文摘要
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英文摘要
The development of novel structural materials is a key component of the clean energy transformation. These materials are needed to increase the fuel efficiency of automobiles and to improve the durability of infrastructure. These needs have stimulated continued improvement of traditional materials, as well as, the emergence of new classes of materials. In parallel, advances in computer science and process automation have led to breakthroughs in the areas of additive manufacturing and machine learning. The convergence of these trends creates unprecedented opportunities to simultaneous optimize the design of components, as well as, the composition, processing and architecture of materials. Multiscale Materials Optimization addresses two key challenges in the area of materials engineering. The first is the need to understand the increasingly more complex microstructures of emerging alloys, which are often far from equilibrium. The second is to develop novel approaches, by which, heterogeneity is intentionally introduced into the material in order to obtain combinations of properties that could not be attained using "uniform" microstructures. More specifically, the program will explore ways of overcoming two constraints that would soon limit the potential for light weighting in the automotive industry. First, the limited stiffness of thin steel panels will be addressed by developing high modulus steels using an innovative surface alloying process. This unique process will reinforce the surface layer with high modulus ceramic particles, without compromising the ductility of the material at the core of the sheet. Secondly, the stagnating light weighting potential of traditional aluminum alloys will be enhanced by exploiting a recently developed precipitation process. This novel process takes advantage of the non-equilibrium conditions created by cyclic deformation leading to significant increases in the strength and ductility of aluminum alloys. The research program will also explore the development of novel energy absorbing materials through the use of honeycomb structures that have been optimized for specific mass-sensitive applications in the space and aerospace industries. Defects will be introduced into these structures to control the way in which the material deforms and absorbs energy. The program will train 2 M.Sc. students, 2 Ph.D. students and 1 post doctoral fellows at the state-of-the-art facilities of the Canadian Centre for Electron Microscopy and the Centre for Automotive Materials and Corrosion. The trainees will also use national and international facilities at CanmetMATERIALS and the European Synchrotron. The HQP will gain an advanced skillset in the areas of microstructure modelling, structure-property relationships and alloy design. These skills are highly sought after in the steel, aluminum, automotive and aerospace industries as these sectors look to accelerate the development and adoption of new materials.
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Multiscale Optimization of Materials
  • 批准号:
    RGPIN-2020-04784
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $5.54万
  • 财政年份:
    2022
  • 负责人:
    Zurob, Hatem
  • 依托单位:
Effect of Chemical Composition and Microstructure on Liquid Metal Embrittlement in Advanced High Strength Steels.
  • 批准号:
    543708-2019
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $1.97万
  • 财政年份:
    2021
  • 负责人:
    Zurob, Hatem
  • 依托单位:
Multiscale Optimization of Materials
  • 批准号:
    RGPIN-2020-04784
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $5.54万
  • 财政年份:
    2021
  • 负责人:
    Zurob, Hatem
  • 依托单位:
Process compatibility and damage performance of carbide-free bainite advanced high strength steel (AHSS) sheets
  • 批准号:
    531490-2018
  • 项目类别:
    Collaborative Research and Development Grants
  • 资助金额:
    $1.28万
  • 财政年份:
    2021
  • 负责人:
    Zurob, Hatem
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
供应链管理中的稳健型(Robust)策略分析和稳健型优化(Robust Optimization )方法研究
  • 批准号:
    70601028
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    7.0万元
  • 批准年份:
    2006
  • 负责人:
    王明征
  • 依托单位: