Improved methods for thin, surface boundary layer investigations

New techniques are developed to improve the velocity flow-field measurement capability within a freesurface boundary layer region on which progressive capillarygravity waves are present. Due to the extremely thin but rather vortical characteristics of the aforementioned boundary layer, conventional particle image velocimetry (PIV) methods fail to estimate velocity (and vorticity) vectors at an acceptable detection rate. This failure is a direct consequence of optimal PIV parameters that are difficult to achieve in practice for such flow situations. A new technique, Sub-pattern PIV, is developed. This method has features similar to both the super-resolution PIV (Keane et al. 1995) and the particle image distortion (PID) technique (Huang et al. 1993), but is predicated upon a very differential philosophy. Another difficulty that arises in experiments to investigate surface boundary layer flows is that the oscillating and deforming air—water interface has a mirror-like behavior that affects the images, and generates very noisy data. An alternative experimental setup that utilizes the Brewster angle phenomenon is adopted and the specular effects of the free-surface are removed successfully. This Brewster angle imaging, along with the Sub-pattern PIV technique, is used for the target application — a free-surface boundary layer investigation. It proved to be very effective. The methodology of both techniques is discussed, and the modified PIV procedure is validated by numerical probabilistic simulations. Application to the capillary-gravity wave boundary layer is presented in a subsequent paper. Received: 31 July 1997/Accepted: 4 February 1998 H. J. Lin Department of Mechanical Engineering and Applied Mechanics University of Michigan Ann Arbor, MI 48109-2125, USA M. Perlin Department of Naval Architecture and Marine Engineering University of Michigan Ann Arbor, MI 48109-2145, USA Correspondence to: M. Perlin This research was supported by the Office of Naval Research Under the University Research Initiative Ocean Surface Processes and Remote Sensing at the University of Michigan, contract number N00014-92-J1650.