Distortion correction of two-component two-dimensional PIV using a large imaging sensor with application to measurements of a turbulent boundary layer flow at $$\hbox {Re}_{\tau } = 2386$$ Re τ = 2386

In the past decade, advances in electronics technology have made larger imaging sensors available to the experimental fluid mechanics community. These advancements have enabled the measurement of 2-component 2-dimensional (2C–2D) velocity fields using particle image velocimetry (PIV) with much higher spatial resolution than previously possible. However, due to the large size of the sensor, lens distortion needs to be accounted for and corrected to ensure accurate high-fidelity 2C–2D velocity field measurements, since it will now have a more significant effect on the measurement quality. In this paper, two dewarping models, a second-order rational function (R2) and a bicubic polynomial (P3) are investigated with regards to their performance, uncertainty and sensitivity and applied to correct 2C–2D PIV measurements of a high Reynolds number zero-pressure-gradient turbulent boundary layer using a large imaging sensor. Furthermore, two approaches are considered and compared, namely: (i) dewarping the images prior to 2C–2D cross-correlation digital PIV analysis and (ii) undertaking 2C–2D cross-correlation digital PIV analysis using the raw single-exposed PIV images followed by correcting the velocity vector positions to their correct locations determined using the dewarping function. The results demonstrate that the use of the P3 dewarping model to correct lens distortion yields better results than the R2 dewarping model and that, both approaches of applying the P3 dewarping model yield results that are statistically indistinguishable.