Next generation combined sonic-hotfilm anemometer: wind alignment and automated calibration procedure using deep learning

Roni H. Goldshmid, Ewelina Winiarska, Dan Liberzon

Research output: Contribution to journalArticlepeer-review

Abstract

The study of naturally occurring turbulent flows requires the ability to collect empirical data down to the fine scales. While hotwire anemometry offers such ability, the open field studies are uncommon due to the cumbersome calibration procedure and operational requirements of hotwire anemometry, e.g., constant ambient properties and steady flow conditions. The combo probe—the combined sonic-hotfilm anemometer—developed and tested over the last decade has demonstrated its ability to overcome this hurdle. The older generation had a limited wind alignment range of 120° and the in situ calibration procedure was human decision based. This study presents the next generation of the combo probe design, and the new fully automated in situ calibration procedure implementing deep learning. The new design now enables measurements of the incoming wind flow in a 360° range. The improved calibration procedure is shown to have the robustness necessary for operation in everchanging open field flow and environmental conditions. This is especially useful with diurnally changing environments and possibly non-stationary measuring stations, i.e., probes placed on moving platforms like boats, drones, and weather balloons. Together, the updated design and the new calibration procedure, allow for continuous field measurements with minimal to no human interaction, enabling near real-time monitoring of fine-scale turbulent fluctuations. Integration of these probes will contribute toward generation of a large pool of field data to be collected to unravel the intricacies of all scales of turbulent flows occurring in natural setups. Graphical abstract: [Figure not available: see fulltext.]

Original languageEnglish
Article number30
JournalExperiments in Fluids
Volume63
Issue number1
DOIs
StatePublished - Jan 2022

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Fluid Flow and Transfer Processes
  • General Physics and Astronomy
  • Computational Mechanics

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