Physics-based filtering of irrotational wavepackets from high-speed Schlieren

Abstract

The eduction of acoustically efficient wavepacket structures from experimental measurements or high-fidelity numerical data aids in understanding different noise generation mechanisms in jets. This is often achieved by employing either signal processing techniques or modal decompositions. The former often require some user-defined thresholds that must be adjusted for each operating condition whereas the latter are more robust and can be applied to any jet flow-field irrespective of the operating conditions. The application of physics-based decompositions requires time-accurate spatio-temporally resolved data of the type obtained from well-validated numerical databases, which require substantial computational resources. There is an inherent advantage in extending decomposition-based approaches to experimental measurements, which can provide a substantially longer time series of data compared to numerical simulations. This investigation explores the application of Doak's Momentum Potential Theory to high-speed schlieren imaging, which is a widely used flow visualization tool in jet noise research. The procedure is applied to different test-cases, selected based on the availability of high-quality experimental measurements and numerical data. The coherent wavepackets obtained exhibit superior spatio-temporal coherence and radiative efficiency that capture the noise radiation mechanisms in the flow.