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The role of acoustic cavity modes in vehicle NVH (noise, vibration and harshness) development is well established in the automotive industry today. Prior knowledge of these modes can help prevent potential issues later in the development cycle, as well as aid in root cause analysis of vibro-acoustic issues. OEMs utilize them as part of their overall modal alignment strategy and cascade them to major system and sub-system suppliers for robust NVH designs. Today, acoustic cavity modes can be obtained rather easily using CAE (computer aided engineering) methods early in the development cycle. However, unlike acoustic modal testing, the CAE normal mode solution cannot scale the relative amplitudes of the modes. The sheer number of acoustic modal frequencies to be avoided can be a serious deterrent during the early design phase. This paper proposes an alternate approach for acoustic modal analyses using CAE to scale the relative amplitudes of cavity modes.

For most car manufacturers, aerodynamic noise is becoming the dominant high frequency noise source (≻ 500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain mainly an experimental art implying high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the development of a reliable numerical prediction capability. This paper presents a computational approach that can be used to predict the vehicle interior noise from the greenhouse wind noise sources, during the early stages of the vehicle developmental process so that design changes can be made to improve the wind noise performance of the vehicle.

For most car manufacturers, aerodynamic noise is becoming the dominant high frequency noise source (≻500 Hz) at highway speeds. Design optimization and early detection of issues related to aeroacoustics remain an experimental art implying high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the development of a reliable numerical prediction capability. This paper presents a computational approach that can be used to predict the vehicle interior noise from the greenhouse wind noise sources, during the early stages of the vehicle developmental process so that design changes can be made to improve the wind noise performance of the vehicle.