Computational vibro-acoustic modeling for aircraft fuselage design optimization

用于飞机机身设计优化的计算振动声学建模

基本信息

  • 批准号:
    453375-2013
  • 负责人:
  • 金额:
    $ 1.6万
  • 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:
    2017
  • 资助国家:
    加拿大
  • 起止时间:
    2017-01-01 至 2018-12-31
  • 项目状态:
    已结题

项目摘要

In order to remain commercially competitive and limit the environmental impact of their activities(manufacturing and use of aircraft), Bombardier Aerospace continually searches for optimum aircraft designand manufacturing methods. The focus of this project is on ways to reduce the acoustic noise transmittedthrough the fuselage from the exterior to the interior of the aircraft while minimizing the addition of acousticbarrier material and eliminating costly and environmentally unfriendly manufacturing methods.The proposed project has two main objectives. The first objective is to develop and experimentally verifyaccurate computational (FEM and BEM) vibro-acoustic models of various aircraft fuselage designs. Thesemodels will then allow Bombardier to predict the acoustic transmission loss (acoustic noise attenuation)through different aircraft fuselage designs without the need for expensive iterative experimental measurements.The second objective is to use the newly developed computational modeling tool to search for optimumfuselage designs. This objective has two principal tasks. The first task is to find the design that provides thehighest acoustic noise attenuation with the lowest weight per unit area. The second task will be to evaluatealternative manufacturing methods that could be used with the optimum fuselage design to reduce overallcombined costs (including fuel consumption (due to net weight), manufacturing costs (due to materials usedand fabrication time), and inspection costs (to meet regulatory requirements). The multi-parameter optimizationwill likely require revisiting the original "optimal" design (for reduced noise) and making modifications thatwill affect factors related to manufacturing and operating costs. The computational model that predictsvibro-acoustic noise transmission will allow this iterative process to be completed without the need forprototype testing until the final stage, therefore saving considerable time and money.
为了保持商业竞争力并限制其活动(飞机制造和使用)对环境的影响,庞巴迪宇航公司不断寻求最佳的飞机设计和制造方法。该项目的重点是如何减少通过机身从外部传递到飞机内部的噪音,同时尽量减少隔音材料的添加,消除昂贵和环境不友好的制造方法。第一个目标是开发和实验验证各种飞机机身设计的精确计算(FEM和BEM)振动声学模型。这些模型将使庞巴迪能够通过不同的飞机机身设计来预测声传输损失(声噪声衰减),而不需要昂贵的迭代实验测量。第二个目标是使用新开发的计算建模工具来搜索最佳机身设计。这一目标有两项主要任务。第一个任务是找到设计,提供最高的声学噪声衰减与最低的重量每单位面积。第二项任务是评估可用于最佳机身设计的替代制造方法,以降低总综合成本(包括燃料消耗(由于净重)、制造成本(由于所用材料和制造时间)和检查成本(满足法规要求))。多参数优化可能需要重新审视最初的“最佳”设计(以降低噪音),并进行修改,这将影响与制造和运营成本相关的因素。预测振动噪声传输的计算模型将允许完成这个迭代过程,而无需进行原型测试,直到最后阶段,因此节省了大量的时间和金钱。

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:
    $ 1.6万
  • 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:
    $ 1.6万
  • 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:
    2021
  • 资助金额:
    $ 1.6万
  • 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:
    $ 1.6万
  • 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:
    2020
  • 资助金额:
    $ 1.6万
  • 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:
    $ 1.6万
  • 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:
    2020
  • 资助金额:
    $ 1.6万
  • 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:
    2019
  • 资助金额:
    $ 1.6万
  • 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:
    $ 1.6万
  • 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:
    $ 1.6万
  • 项目类别:
    Collaborative Research and Development Grants

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Computational vibro-acoustic modeling for aircraft fuselage design optimization
用于飞机机身设计优化的计算振动声学建模
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    453375-2013
  • 财政年份:
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  • 资助金额:
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