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Fan Noise Prediction for Off-Highway Vehicle

机译:风扇噪声预测离高速公路车辆

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Fan noise can form a significant part of the vehicle noise signature and needs hence to be optimized in view of exterior noise and operator exposure. Putting together unsteady CFD simulation with acoustic FEM modeling, tonal and broadband fan noise can be accurately predicted, accounting for the sound propagation through engine compartment and vehicle frame structure. This paper focuses on method development and validation in view of the practical vehicle design process. In a step by-step approach, the model has been validated against a dedicated test-set-up, so that good accuracy of operational fan noise prediction could be achieved. Main focus was on the acoustic transfer through the engine compartment. The equivalent acoustic transfer through radiators/heat exchangers is modeled based on separate detailed acoustic models. The updating process revealed the sensitivity of various components in the engine compartment. Unsteady CFD included the build-up of a sliding mesh model which was analyzed using the DDES method. After convergence, time data of blade surface pressure were exported in CGNS format. These pressure data were used to generate rotating dipole sources in acoustic FE analysis and predict the fan noise response in frequency domain at two selected rpm. Post processing includes the predicted noise at target microphone positions as well as colormaps of sound pressure distributions that can guide to the development of countermeasures.
机译:风扇噪声可以形成车辆噪声签名的重要部分,从而考虑到外部噪声和操作员曝光来优化。可以精确预测与声学有限元模拟,色调和宽带风扇噪声的不稳定CFD仿真,通过发动机舱和车辆框架结构占声音传播。鉴于实用的车辆设计过程,本文侧重于方法开发和验证。在一步一步的方法中,模型已经针对专用的测试设置验证,因此可以实现操作风扇噪声预测的良好精度。主要重点是通过发动机舱的声学转移。通过散热器/热交换器的等效声学传输基于单独的详细声学模型进行建模。更新过程揭示了发动机舱中各种部件的灵敏度。不稳定的CFD包括使用DDES方法分析的滑动网格模型的积累。收敛后,叶片表面压力的时间数据以CGNS格式导出。这些压力数据用于在声学FE分析中产生旋转偶极源,并在两个选择的RPM中预测频域中的风扇噪声响应。后处理包括目标麦克风位置的预测噪声以及能够指导对策的发展的声压分布的色调。

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