Abstract: As a novel volumetric particle image velocimetry technique, single-camera light-field PIV (LF-PIV) is able to acquire three-dimensional flow fields through a single camera. Compared with other multi-camera 3D PIV techniques, LF-PIV has distinct advantages, including concise hardware setup and low optical access requirements. Its capability has proven effective in many experimental investigations. In this study, the use of LF-PIV in measuring a self-similar adverse pressure-gradient turbulent boundary layer (APG-TBL) is demonstrated. Experiments are performed in a large water tunnel at the Laboratory for Turbulence Research in Aerospace and Combustion (LTRAC), Monash University. Sets of 250 light-field PIV image pairs are captured covering both the inner and outer regions of the boundary layer. Instantaneous 3D velocity fields are reconstructed using a GPU accelerated density ray tracing multiplicative reconstruction technique (DRT-MART) and three-dimensional cross-correlation methods. The LF-PIV results are compared with two-dimensional PIV (2D-PIV) measurements of the same flow. Comparable accuracy to 2D-PIV is achieved for first- and second-order velocity statistics above approximately y/ δ₁= 1. Graphic abstract: [Figure not available: see fulltext.].

As a novel volumetric particle image velocimetry technique, single-camera light-field PIV (LF-PIV) is able to reconstruct three-dimensional flow fields with a single camera. The merits of LF-PIV lie in its concise hardware setup and minimum optical access requirement, its capability has been proved in many flow scenarios. In this study, LF-PIV is used to measure a self-similar adverse pressure gradient turbulent boundary layer (APG-TBL). Experiments were performed in a large water tunnel at the Laboratory for Turbulence Research in Aerospace and Combustion (LTRAC), Monash University. 20 independent batches of light-field PIV images were captured for both inner and outer flow, each consisting of 250 instantaneous image pairs. Instantaneous 3D velocity fields were reconstructed with the GPU accelerated DRT-MART and 3D cross-correlation methods and compared with two-dimensional PIV (2D-PIV) results. Initial results show that though limited by the experiment conditions and PIV algorithms developed in 2016, we still can have similar accuracy to 2D-PIV near and above the boundary layer. With the volumetric calibration method that compensates optical distortions caused by lens defect and misalignment between the micro-lens array (MLA) and image sensor, the resolution of LF-PIV is sure to have a large improvement.