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Novel computational and experimental wind engineering approaches for community level performance assessment

Novel computational and experimental wind engineering approaches for community level performance assessment
用于社区级绩效评估的新型计算和实验风工程方法
批准号:
RGPIN-2018-05454
负责人:
Bitsuamlak, Girma
金额:
$3.79万
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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英文摘要
Canada's diverse geography and climate exposes our communities to wind hazards, such as tornadoes and hurricanes. This is further aggravated due to aging infrastructure, population growth and climate change. To maintain the safety and prosperity of our communities, it is vital to develop a comprehensive framework to assess and mitigate the impacts of extreme climate. In this research program novel computer models and large scale experimental approaches will be developed to assess the wind performance of buildings at a community level. This approach is unique as it considers aerodynamics for progressive failure and the interdependence of cladding, structural systems, individual buildings, and neighborhoods.To achieve these goals the following three research objectives are proposed:(1) Computer and experimental wind flow modeling and visualization: This objective proposes novel developments at pre-processing, system modeling and post processing stages. At the pre-processing stages, generation of three-dimensional building layouts in cities assisted with various remote sensing sensors installed on an unmanned air vehicle (UAV) and those obtained from satellites will be automated. At the system modeling stage, detail computer and experimental based methods for modeling turbulent wind (and wind-driven-rain) and its interaction with buildings will be developed. At post-processing level, user friendly data analysis/mining and visualizations will be developed. (2) Progressive aerodynamics and hydrodynamics for buildings and neighborhoods: Here, the computer models developed in (1) will be integrated with building information modeling (BIM) at various levels of development. Since the BIM model will consist of all the parts of building, it is possible to model damage states in detail. In parallel, new experimental testing protocols enabled by emerging 3D printing technologies and large-scale wind testing facilities will be developed for validation. (3) Non-linear aeroelastic characterization for high-rise buildings: Current tall building design for wind only considers linear elastic capacity of structural systems. However, tall buildings can be subjected to loads beyond design capacity during hurricane and tornado events; as a result local plastic deformations may occur. The impact of these types of plastic deformations are unknown. In this objective novel experimental methods for non-linear aeroelastic characterization will be developed assisted with state-of-the-art 3D printers.The insurance, Architectural and Engineering (As leadership in risk mitigation technology.
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Novel computational and experimental wind engineering approaches for community level performance assessment
  • 批准号:
    RGPIN-2018-05454
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.79万
  • 财政年份:
    2021
  • 负责人:
    Bitsuamlak, Girma
  • 依托单位:
Numerical modelling of indoor environment for energy-efficient bio-manufacturing facilities
  • 批准号:
    570405-2021
  • 项目类别:
    Alliance Grants
  • 资助金额:
    $2.19万
  • 财政年份:
    2021
  • 负责人:
    Bitsuamlak, Girma
  • 依托单位:
Wind Engineering
  • 批准号:
    CRC-2016-00105
  • 项目类别:
    Canada Research Chairs
  • 资助金额:
    $7.29万
  • 财政年份:
    2021
  • 负责人:
    Bitsuamlak, Girma
  • 依托单位:
Novel computational and experimental wind engineering approaches for community level performance assessment
  • 批准号:
    RGPIN-2018-05454
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.79万
  • 财政年份:
    2020
  • 负责人:
    Bitsuamlak, Girma
  • 依托单位:
国内基金
海外基金
物体运动对流场扰动的数学模型研究
  • 批准号:
    51072241
  • 项目类别:
    专项基金项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2010
  • 负责人:
    李廷秋
  • 依托单位:
Computational Methods for Analyzing Toponome Data