arXiv subjects

Armin Goudarzi

Publications and source records attributed to Armin Goudarzi.

6 recordsLinked to original sources

arXiv2024

Enhancing Aeroacoustic Wind Tunnel Studies through Massive Channel Upscaling with MEMS Microphones

This paper presents a large 6~m x 3~m aperture 7200 MEMS microphone array. The array is designed so that sub-arrays with optimized point spread functions can be used for beamforming and thus, enable the research of source directivity in wind tunnel facilities. The total array consists of modular 800 microphone panels, each consisting of four unique PCB board designs. This modular architecture allows for the time-synchronized measurement of an arbitrary number of panels and thus, aperture size and total number of sensors. The panels can be installed without a gap so that the array's microphone pattern avoids high sidelobes in the point spread function. The array's capabilities are evaluated on a 1:9.5 airframe half model in an open wind tunnel at DNW-NWB. The total source emission is quantified and the directivity is evaluated with beamforming. Additional far-field microphones are employed to validate the results.

cs.SD↗

arXiv2023

Global, and Local Optimization Beamforming for Broadband Sources

This paper presents an alternative energy function for Global Optimization (GO) beamforming, tailored to acoustic broadband sources. Given, that properties such as the source location, multipole rotation, or flow conditions are parameterized over the frequency, a CSM-fitting can be performed for all frequencies at once. A numerical analysis shows that the nonlinear energy function for the standard GO problem is equivalent to the source's Point Spread Function (PSF) and contains local minima at the grating- and side lobes' locations. The energy function is improved with the proposed broadband energy, as it averages the PSF. Further, it simplifies the process of identifying sources and reconstructing their spectra from the results. The paper shows that the method is superior on synthetic monopoles compared to standard GO and CLEAN-SC. For real-world data the results of the proposed method and CLEAN-SC are similar, and outperform standard GO. The main difference is that source assumption violations cause noisy maps for CLEAN-SC and cause wrong spectral estimations of the proposed method. By using reasonable initial values, the GO problem reduces to a Local Optimization problem with similar results. Further, the proposed method is able to identify synthetic multipoles with different pole amplitudes and unknown pole rotations.

cs.SD↗

arXiv2023

B-CLEAN-SC: CLEAN-SC for broadband sources

This paper presents B-CLEAN-SC, a variation of CLEAN-SC for broadband sources. Opposed to CLEAN-SC, which ``deconvolves'' the beamforming map for each frequency individually, B-CLEAN-SC processes frequency intervals. Instead of performing a deconvolution iteration at the location of the maximum level, B-CLEAN-SC performs it at the location of the over-frequency-averaged maximum to improve the location estimation. The method is validated and compared to standard CLEAN-SC on synthetic cases, and real-world experiments, for broad- and narrowband sources. It improves the source reconstruction at low and high frequencies and suppresses noise, while it only increases the need for memory but not computational effort.

cs.SD↗

arXiv2023

Aeroacoustic testing on a full aircraft model at high Reynolds numbers in the European Transonic Windtunnel

This paper presents an end-to-end approach for the assessment of pressurized and cryogenic wind tunnel measurements of an EMBRAER scaled full model close to real-world Reynolds numbers. The choice of microphones, measurement parameters, the design of the array, and the selection of flow parameters are discussed. Different wind tunnel conditions are proposed which allow separating the influence of the Reynolds number from the Mach number, as well as the influence of slotted and closed test sections. The paper provides three-dimensional beamforming results with CLEAN-SC deconvolution, the selection of regions of interest, and the corresponding source spectra. The results suggest that slotted test sections have little influence on the beamforming results compared to closed test sections and that the Reynolds number has a profound, non-linear impact on the aeroacoustic emission that lessens with increasing Reynolds number. Further, sources show a non-linear Mach number dependency at constant Reynolds number but are self-similar in the observed Mach number range. The findings suggest that it is possible to study real-world phenomena on small-scale full models at real-world Reynolds numbers, which enable further investigations in the future such as the directivity of sources.

physics.flu-dyn↗

arXiv2021

Expert Decision Support System for aeroacoustic source type identification using clustering

This paper presents an Expert Decision Support System for the identification of time-invariant, aeroacoustic source types. The system comprises two steps: first, acoustic properties are calculated based on spectral and spatial information. Second, clustering is performed based on these properties. The clustering aims at helping and guiding an expert for quick identification of different source types, providing an understanding of how sources differ. This supports the expert in determining similar or atypical behavior. A variety of features are proposed for capturing the characteristics of the sources. These features represent aeroacoustic properties that can be interpreted by both the machine and by experts. The features are independent of the absolute Mach number which enables the proposed method to cluster data measured at different flow configurations. The method is evaluated on deconvolved beamforming data from two scaled airframe half-model measurements. For this exemplary data, the proposed support system method results in clusters that mostly correspond to the source types identified by the authors. The clustering also provides the mean feature values and the cluster hierarchy for each cluster and for each cluster member a clustering confidence. This additional information makes the results transparent and allows the expert to understand the clustering choices.

cs.SD↗

arXiv2021

Automatic source localization and spectra generation from sparse beamforming maps

Beamforming is an imaging tool for the investigation of aeroacoustic phenomena and results in high dimensional data that is broken down to spectra by integrating spatial Regions Of Interest. This paper presents two methods that enable the automated identification of aeroacoustic sources in sparse beamforming maps and the extraction of their corresponding spectra to overcome the manual definition of Regions Of Interest. The methods are evaluated on two scaled airframe half-model wind-tunnel measurements and on a generic monopole source. The first relies on the spatial normal distribution of aeroacoustic broadband sources in sparse beamforming maps. The second uses hierarchical clustering methods. Both methods are robust to statistical noise and predict the existence, location, and spatial probability estimation for sources based on which Regions Of Interest are automatically determined.

cs.SD↗