  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 procedure is demonstrated using
experimental as well as simulated schlieren images representing a wide range of
imperfectly-expanded free and impinging jet configurations. When combined with
Spectral Proper Orthogonal Decomposition, the method yields modes that
accurately capture (i) the Mach wave radiation from a military-style jet, (ii)
the mode shapes of the feedback tones in an impinging jet, and (iii) the
screech signature in twin rectangular jets, without recourse to user adjusted
parameters. This technique has the potential to greatly expand the use of
high-speed diagnostics and provide real-time monitoring of the acoustic content
of the jet in the nearfield, with feedback control implications. Additionally,
although the present study focuses on jets, the general nature of the approach
allows a straightforward application to other flows, such as cavity
flow-acoustic interactions, among others.
