Computational vibro-acoustic modeling for aircraft fuselage design optimization

为了保持商业竞争力并限制其活动(制造和使用飞机)对环境的影响，庞巴迪宇航不断寻求最佳的飞机设计和制造方法。这个项目的重点是如何减少从飞机外部到内部通过机身传递的声学噪音，同时最大限度地减少添加隔音材料，并消除昂贵和不环保的制造方法。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(有限元和边界元)振声模型。然后，这些模型将允许庞巴迪预测不同机身设计的声学传输损失(声学噪声衰减)，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寻找最佳机身设计。这一目标有两项主要任务。第一个任务是找到在单位面积重量最小的情况下提供最高噪音衰减的设计。第二项任务是评估可与最佳机身设计一起使用的替代制造方法，以降低总体综合成本(包括燃料消耗(由于净重)、制造成本(由于使用的材料和制造时间)和检查成本(以满足法规要求)。多参数优化很可能需要重新审视原始的“最佳”设计(以降低噪音)，并做出会影响制造和运营成本因素的修改。预测振动-声学噪声传播的计算模型将允许完成这一迭代过程，直到最后阶段不需要原型测试，因此节省了大量的时间和金钱。

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.