Analytical and numerical analyses are developed for the interaction and scattering of incident acoustic and vortical disturbances by an unloaded annular cascade in a swirling flow. The mathematical formulation uses the Euler equations linearized about an axial and swirling mean flow. The incident disturbances are decomposed into nearly sonic and nearly convected disturbances using the results of a normal-mode analysis, namely the unsteady pressure is predominantly associated with the former. Exact non-reflecting inflow/outflow conditions are derived in terms of the normal modes using the group velocity to segregate the modes propagating downstream and upstream. An inflow condition is also derived for the nearly convected disturbances. An explicit primitive-variable scheme is implemented and validated by comparison with the uniform flow and narrow annulus limits. Acoustic and aerodynamic results are presented to examine how swirl modifies the scattering from that of the uniform flow and narrow annulus limits and to determine the conditions leading to strong scattering. The results indicate that the swirl changes the physics of the scattering in three major ways: (i) it modifies the number of acoustic modes in the duct, (ii) it changes their duct radial profile, and (iii) it causes significant amplitude and radial phase variations of the incident disturbance. The results also show that when the radial phase of the incident disturbance is different from that of the duct modes, weak scattering into the duct acoustic modes occurs. These results suggest that analysis of the radial variation of the incident disturbance and duct modes can provide an indication of the efficiency of the scattering process.
Phased microphone arrays have become an important tool in the localization of noise sources for aeroacoustic applications. In most practical aerospace cases the conventional beamforming algorithm of the delay-and-sum type has been adopted. Conventional beamforming cannot take advantage of knowledge of the noise field, and thus has poorer resolution in the presence of noise and interference. Adaptive beamforming has been used for more than three decades to address these issues and has already achieved various degrees of success in areas of communication and sonar. In this work an adaptive beamforming algorithm designed specifically for aeroacoustic applications is discussed and applied to practical experimental data. It shows that the adaptive beamforming method could save significant amounts of post-processing time for a deconvolution method. For example, the adaptive beamforming method is able to reduce the DAMAS computation time by at least 60% for the practical case considered in this work. Therefore, adaptive beamforming can be considered as a promising signal processing method for aeroacoustic measurements.
Acoustic arrays have become an important testing tool in noise identification for industry applications, where the typical beamforming algorithm has been adopted as a classical processing technique. In most practical cases the beamforming computations have to be conducted off-line due to the excessive computational requirements. An alternative algorithm with a real-time capability is proposed. The algorithm is similar to a classic observer while array processing is performed in the frequency domain. The performance of this observer-based algorithm is studied here through comparing with the typical beamforming method, particularly for a case of coherent noise sources. In this paper it is shown that the observer-based algorithm could resolve the coherence restriction between the background noise and the signal of interest. The proposed algorithm is also beneficial for its capability of operating over sampling blocks recursively. The convergence rate of this recursive algorithm is fast enough to satisfy the requirements for practical cases. The experimental efforts could be saved extensively as any testing defects could be revealed instantaneously and corrected on site. In addition, this innovative approach provides an alternative perspective, from which many techniques already developed in control and filtering could be extended to this new application area of array processing.
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