Fuselage structural dynamic and vibro-acoustic analysis, modeling, and optimization

机身结构动力学和振动声学分析、建模和优化

基本信息

  • 批准号:
    536637-2018
  • 负责人:
  • 金额:
    $ 3.68万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Collaborative Research and Development Grants
  • 财政年份:
    2020
  • 资助国家:
    加拿大
  • 起止时间:
    2020-01-01 至 2021-12-31
  • 项目状态:
    已结题

项目摘要

Bombardier Aerospace maintains a high standard of advanced aircraft design through the use of sophisticated analysis and manufacturing methods. This includes measurement, analysis, and computational modeling of the structural dynamics and structure-borne acoustic behavior of the fuselage in response to external (engines and turbulence) and internal (sub-systems mounted within the fuselage) excitation. However, to improve the dynamic and vibro-acoustic behavior of the fuselage structure, Bombardier needs to develop new methodologies that will help define optimum configurations and material selection. The computational modeling and optimization tools to be developed will be used to define optimum fuselage designs. Optimum, in this case, refers to minimizing the structural vibration response to various excitations and/or limiting the frequency range of the responses as well as minimizing acoustic noise transmission through the fuselage while maintaining the lowest possible weight. Computational models that predict vibro-acoustic noise transmission will allow for the application of optimization strategies and an iterative process of development and virtual testing without the need for prototype fabrication and testing until the final stage. The proposed project includes three main objectives. These include the development of verified computational models of a fuselage mounted rear-engine aircraft. Verification will take place using modal testing on a matching physical model. The models will then be used to explore alternative structural modifications to the fuselage and support structures used to mount the engines and auxiliary systems. Extension of the computational structural dynamic model will include acoustic field estimation. These will then be used to investigate different structural components, material types, thicknesses, and placement to prevent acoustic noise from being transmitted through fuselage structures and skin. New topology optimization methods will also be developed focused on vibration damping and acoustic barrier material selection and placement primarily using minimization of the acoustic sound field within the cabin as the performance objective.

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Mechefske, Christopher其他文献

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system
  • DOI:
    10.1016/j.cja.2017.11.017
  • 发表时间:
    2018-01-01
  • 期刊:
  • 影响因子:
    5.7
  • 作者:
    Hanachi, Houman;Liu, Jie;Mechefske, Christopher
  • 通讯作者:
    Mechefske, Christopher
Performance-Based Gas Turbine Health Monitoring, Diagnostics, and Prognostics: A Survey
  • DOI:
    10.1109/tr.2018.2822702
  • 发表时间:
    2018-09-01
  • 期刊:
  • 影响因子:
    5.9
  • 作者:
    Hanachi, Houman;Mechefske, Christopher;Chen, Ying
  • 通讯作者:
    Chen, Ying

Mechefske, Christopher的其他文献

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{{ truncateString('Mechefske, Christopher', 18)}}的其他基金

Hybrid Data-driven Physics-based Modeling for Machine Fault Detection, Diagnosis, and Prediction
用于机器故障检测、诊断和预测的混合数据驱动的基于物理的建模
  • 批准号:
    RGPIN-2019-03967
  • 财政年份:
    2022
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Discovery Grants Program - Individual
Fuselage structural dynamic and vibro-acoustic analysis, modeling, and optimization
机身结构动力学和振动声学分析、建模和优化
  • 批准号:
    536637-2018
  • 财政年份:
    2021
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Collaborative Research and Development Grants
Hybrid Data-driven Physics-based Modeling for Machine Fault Detection, Diagnosis, and Prediction
用于机器故障检测、诊断和预测的混合数据驱动的基于物理的建模
  • 批准号:
    RGPIN-2019-03967
  • 财政年份:
    2021
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Discovery Grants Program - Individual
Machine tool monitoring using data analytics and physics-based models
使用数据分析和基于物理的模型进行机床监控
  • 批准号:
    523509-2018
  • 财政年份:
    2021
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Collaborative Research and Development Grants
Machine tool monitoring using data analytics and physics-based models
使用数据分析和基于物理的模型进行机床监控
  • 批准号:
    523509-2018
  • 财政年份:
    2020
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Collaborative Research and Development Grants
Hybrid Data-driven Physics-based Modeling for Machine Fault Detection, Diagnosis, and Prediction
用于机器故障检测、诊断和预测的混合数据驱动的基于物理的建模
  • 批准号:
    RGPIN-2019-03967
  • 财政年份:
    2020
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Discovery Grants Program - Individual
Machine tool monitoring using data analytics and physics-based models
使用数据分析和基于物理的模型进行机床监控
  • 批准号:
    523509-2018
  • 财政年份:
    2019
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Collaborative Research and Development Grants
Hybrid Data-driven Physics-based Modeling for Machine Fault Detection, Diagnosis, and Prediction
用于机器故障检测、诊断和预测的混合数据驱动的基于物理的建模
  • 批准号:
    RGPIN-2019-03967
  • 财政年份:
    2019
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Discovery Grants Program - Individual
Fuselage structural dynamic and vibro-acoustic analysis, modeling, and optimization
机身结构动力学和振动声学分析、建模和优化
  • 批准号:
    536637-2018
  • 财政年份:
    2019
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Collaborative Research and Development Grants
Characterization and Control of Non-Steady State Machine Vibration
非稳态机器振动的表征和控制
  • 批准号:
    RGPIN-2014-05922
  • 财政年份:
    2018
  • 资助金额:
    $ 3.68万
  • 项目类别:
    Discovery Grants Program - Individual

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RADx-UP 数据的综合网络分析可提高刑事法律系统 (PCLS) 相关人员的 COVID-19 检测和疫苗接种率
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