A major challenge in meeting noise targets is assessing and reducing noise sources while dealing with several other design constraints. The time and cost of developing and testing physical prototypes are often prohibitive. Experimental testing challenges also include wind tunnel space limitations for extending measurements to the far field, and relating stationary-source wind tunnel measurements to the real-life, moving-source scenario. Therefore, a computational solution is highly desirable.
A key challenge for Computational Aero-Acoustic (CAA) methods is that sound propagated to the far field consists of pressure perturbations that are very small relative to the turbulent pressure fluctuations in the near-field source region. Therefore, highly accurate prediction of the transient flow behavior with sufficiently low dissipation and dispersion is required to resolve small amplitude fluctuations over the frequency range of interest. Moreover, in typical applications such as aircraft or train certification, the far-field noise target involves large distances, making it impractical to extend the computational domain to include both the source region and the receiver.