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High-Order Unstructured Methods for Large Eddy Simulation and Shape Optimization

High-Order Unstructured Methods for Large Eddy Simulation and Shape Optimization
用于大涡模拟和形状优化的高阶非结构化方法
批准号:
RGPIN-2017-06773
负责人:
Vermeire, Brian
金额:
$2.19万
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
翻译
在环境法规和国际竞争的推动下,加拿大下一代飞机和喷气发动机必须更安静,更省油,才能保持商业可行性。这种飞机的设计将严重依赖于破坏性计算流体动力学(CFD)技术,特别是大涡模拟(LES),以满足性能和污染目标。美国、欧盟以及加拿大公司的直接竞争对手,包括劳斯莱斯、空中客车和BAE系统公司,目前正在投资或采用LES用于飞机和喷气发动机设计,预计时间为2020年。然而,在加拿大并没有得到类似的投资,这就产生了明显的竞争劣势。这项研究计划的长期目标是通过开发更精确、可靠和更便宜的LES新技术,确保加拿大工业保持竞争力。这将通过三个特定的多年研究目标来实现,以提高精度,降低成本,并增加LES的适用范围:1)LES在复杂几何形状附近,2)使用下一代计算机硬件的LES,以及3)使用LES的空气动力学形状优化。该研究项目的最终产品将是这些新技术在CFD套件中的应用,并提供给加拿大的工业合作伙伴,从而使加拿大能够设计出具有商业可行性的下一代飞机和喷气发动机。
英文摘要
Motivated by environmental regulation and international competition, next-generation Canadian aircraft and jet engines must be significantly quieter and more fuel efficient to remain commercially viable. The design of such aircraft will rely heavily on disruptive computational fluid dynamics (CFD) technologies, specifically large eddy simulation (LES), to meet performance and pollution targets. The United States, European Union, and direct competitors to Canadian companies including Rolls Royce, Airbus, and BAE Systems, are currently investing in or adopting LES for aircraft and jet engine design with a projected 2020 timeline. However, this has not been met by similar investment in Canada, yielding a distinct competitive disadvantage. The long-term objective of this research program is to ensure Canadian industry remains competitive by developing novel technologies for LES that are more accurate, reliable, and less expensive. This will be achieved via three specific multi-year research objectives to improve accuracy, reduce cost, and increase the range of applicability of LES: 1) LES in the Vicinity of Complex Geometries, 2) LES using Next-Generation Computer Hardware, and 3) Aerodynamic Shape Optimization using LES. A final product from this research program will be an implementation of these novel technologies in a CFD package made available to Canadian industry partners, enabling the design of commercially viable next-generation aircraft and jet engines in Canada.
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High-Order Unstructured Methods for Large Eddy Simulation and Shape Optimization
  • 批准号:
    RGPIN-2017-06773
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.19万
  • 财政年份:
    2022
  • 负责人:
    Vermeire, Brian
  • 依托单位:
High-Order Unstructured Methods for Large Eddy Simulation and Shape Optimization
  • 批准号:
    RGPIN-2017-06773
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $2.19万
  • 财政年份:
    2021
  • 负责人:
    Vermeire, Brian
  • 依托单位:
Industrialization of High-Order Unstructured Methods for Computational Fluid Dynamics
  • 批准号:
    571551-2021
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $3.28万
  • 财政年份:
    2021
  • 负责人:
    Vermeire, Brian
  • 依托单位:
High-Order Unstructured Methods for Large Eddy Simulation and Shape Optimization
  • 批准号:
    507988-2017
  • 项目类别:
    Discovery Grants Program - Accelerator Supplements
  • 资助金额:
    $2.91万
  • 财政年份:
    2019
  • 负责人:
    Vermeire, Brian
  • 依托单位:
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