Predictive constitutive equations that connect easy-to-measure transport
properties (e.g., viscosity and conductivity) with system performance variables
(e.g., power consumption and efficiency) are needed to design advanced thermal
and electrical systems. In this work, we explore the use of fluorescent
particle-streak analysis to directly measure the local velocity field of a
pressure-driven flow, introducing a new Python package (FSVPy) to perform the
analysis. Fluorescent streak velocimetry (FSV) combines high-speed imaging with
highly fluorescent particles to produce images that contain fluorescent
streaks, whose length and intensity can be related to the local flow velocity.
By capturing images throughout the sample volume, the three-dimensional
velocity field can be quantified and reconstructed. We demonstrate this
technique by characterizing the channel flow profiles of several non-Newtonian
fluids: micellar Cetylpyridinium Chloride solution, Carbopol 940, and
Polyethylene Glycol. We then explore more complex flows, where significant
acceleration is created due to micro-scale features encountered within the
flow. We demonstrate the ability of FSVPy to process streaks of various shapes,
and use the variable intensity along the streak to extract position-specific
velocity measurements from individual images. Thus, we demonstrate that FSVPy
is a flexible tool that can be used to extract local velocimetry measurements
from a wide variety of fluids and flow conditions