Published: March 23, 2021

Background

Laser Doppler velocimetry (LDV) has long been a standard technique in experimental fluid mechanics labs. Researchers in Associate Professor Greg Rieker's lab at CU Â鶹¹ÙÍø extend the capabilities of this technique by reshaping the intensity profile of the optical probe beam and by developing a machine learning-based signal processing scheme to analyze the expected signals which can be more complicated than those from LDV.

Technology

The light scattered by a particle passing through a probe beam caries with it a history of the particle’s trajectory through the beam. When the beam is patterned, the scattered light signal is matched with the properties which gave rise to the motion via a machine learning model.

Advantages

  • Signal processing technique makes no compromise between spatial and temporal resolution
  • Uses readily available seeding particles and requires only a low seeding density
  • May function with existing LDV hardware

Applications

  • Combustion R&D
  • Environmental research
  • Flow facilities (wind tunnels, water channels)
  • Medical devices
  • Microfluidic systems
  • Granular flows

What's Next?

This technology is looking for exclusive and non-exclusive licensing.

Contact

Nicole Forsberg: nicole.forsberg@colorado.edu