A Robust Physics-based Method to Filter Coherent Wavepackets from High-speed Schlieren Images
Chitrarth Prasad, Datta Gaitonde

TL;DR
This paper introduces a robust, physics-based method to extract coherent wavepackets from high-speed schlieren images, enabling better analysis of jet dynamics and acoustic phenomena without extensive parameter tuning.
Contribution
It extends Momentum Potential Theory to experimental schlieren data, allowing accurate wavepacket extraction and mode analysis in high-speed jet flows.
Findings
Successfully isolates acoustic wavepackets in experimental images
Captures jet noise modes without user-adjusted parameters
Applicable to various flow configurations beyond jets
Abstract
A complete understanding of jet dynamics is greatly enabled by accurate separation of the acoustically efficient wavepackets from their higher-energy convecting turbulent counterparts. Recent developments using Momentum Potential Theory (MPT) have successfully isolated the acoustic component in all regions of the jet, to better understand the dynamics as well as to develop wavepacket models. MPT is however a data-intensive method since the inherent Poisson equation solution requires fluctuation quantities in the entire flowfield; as such, it has to date been applied only to numerically obtained data. This work develops an approach to extend its application to extract coherent wavepackets from high-speed schlieren images. The procedure maps pixel intensities from the schlieren to a scaled surrogate for the density gradient integrated along the line of sight. The effectiveness of the…
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