FSVPy: A python-based package for fluorescent streak velocimetry (FSV)

Abstract

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 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 microscale 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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 16, 2022
Source ID
10.1122/8.0000521

Entities

People

  • Brendan C. Blackwell
  • Claire Liu
  • Connor C. Call
  • Han Lin
  • Jeffrey J Richards
  • Michelle Driscoll
  • Shanliangzi Liu

Organizations

  • National Science Foundation
  • Northwestern University
  • United States Department of Energy

Tags

Fields of Study

  • Physics

Readers

  • Distributed Systems and Data Platform Development
  • Fluid Dynamics.
  • Image Processing and Computer Vision.