Multi-Δt approach for peak-locking error correction and uncertainty quantification in PIV

Sagar Adatrao*, Michele Bertone, Andrea Sciacchitano

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)
21 Downloads (Pure)


A novel approach is devised for the quantification of systematic uncertainty due to peak locking in particle image velocimetry (PIV), which also leads to correction of the peak-locking errors. The approach, applicable to statistical flow properties such as time-averaged velocity and Reynolds stresses, relies on image recordings with multiple time separations Δt and a least-squares regression of the measured quantities. In presence of peak locking, the measured particle image displacement is a non-linear function of Δt due to the presence of measurement errors which vary non-linearly with the sub-pixel particle image displacement. Additionally, the measured displacement fluctuations are a combination of the actual flow fluctuations and the measurement error. When the image recordings are acquired with multiple Δt's, a least-squares regression among the statistical results yields a correction where systematic errors due to peak locking are significantly diminished. The methodology is assessed for planar PIV measurements of the flow over a NACA0012 airfoil at 10 degrees angle of attack. Reference measurements with much larger Δt than the Δt's of the actual measurements, such that relative peak-locking errors are negligible for the former, are used to assess the validity of the proposed approach.

Original languageEnglish
Article number054003
Number of pages19
JournalMeasurement Science and Technology
Issue number5
Publication statusPublished - 2021


  • least-squares regression
  • multi-Δt
  • particle image velocimetry
  • peak-locking errors
  • uncertainty quantification
  • t
  • multi-&#916


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