Similarity Profile of Shear Layer in Water Flow Field beneath an Air Pocket at Inner Top-Wall of a Horizontal Pipe
2013 (English)Conference paper (Refereed)
The characteristics of water flow field around an air pocket stuck to the inner top-wall of a horizontal pipe, with approaching flows having fully developed turbulent boundary layer situation, are investigated experimentally. Flow visualization technique using particle trajectory photography and high-speed particle image velocimetry were employed to explore the water flow field around the air pocket in the plane of symmetry both qualitatively and quantitatively. The Reynolds number Re of the pipe flow (= UD/v, where U and D denote the cross-sectional mean streamwise velocity and pipe diameter being equal to 9.60 cm, respectively, and v is the kinematic viscosity of water) is 17,100. The volume of the air pocket tested varies from 1.0 ml to 10.0 ml. The fully developed boundary layer flow in the pipe is examined at first to assure the water flow field around the air bubble is independent of the streamwise position at which the air pocket adhered to the top-wall of the pipe. Based on the measurement results obtained by high-speed particle image velocimetry, the characteristics of water flow fields around the air pocket are presented using the mean velocity vector fields as well as utilizing the distributions of mean streamwise velocity measured at different streamwise sections. In addition, evolution of the mean streamwise velocity measured beneath the air pocket is demonstrated consequently to highlight the formation of shear layer with a reverse flow region inside and extending to the air-pocket surface. Using the non-linear regression analysis with curve fitting to the measured mean streamwise velocity, the appropriate characteristic velocity and length scales are determined precisely to attain the similarity profiles in the shear layer beneath the air pocket. The proposed characteristic length and velocity scales do provide a promising similarity profile as indicated by the data collapse and regression coefficients.
Place, publisher, year, edition, pages
air pocket, particle image velocimetry, shear layer, characteristic length (or velocity) scale, similarity profile
IdentifiersURN: urn:nbn:se:kth:diva-179762OAI: oai:DiVA.org:kth-179762DiVA: diva2:889416
Asian Symposium on Visualization, 19-23 May 2013, Taiwan
Qc 201601042015-12-242015-12-242016-01-04Bibliographically approved