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Appl. Sci. 2018, 8(4), 512; doi:10.3390/app8040512

Silicone-Based Molding Technique for Optical Flow Analysis in Transparent Models of Fluidic Components

Fluid Technology and Microfluidics, University of Rostock, Justus-von-Liebig-Weg 6, 18059 Rostock, Germany
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Received: 19 January 2018 / Revised: 8 March 2018 / Accepted: 26 March 2018 / Published: 27 March 2018
(This article belongs to the Section Mechanical Engineering)
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Abstract

Optical flow analysis methods such as particle image velocimetry can only be performed in fluid systems or components with optical access. Many fluidic components, such as metallic tubes, do not typically feature optical accessibility. A new silicone-based molding technique is presented that makes it possible to replicate non-transparent fluidic components as models with optical accessibility that can be used to perform optical flow analysis. Furthermore, to avoid errors due to refraction, a test fluid is presented whose refractive index matches that of the silicone material of the replication. This new method allows flows to be analyzed in tubes or similar components with diameters in the range of only a few millimeters. An initial test was performed demonstrating the proof of concept and the velocity field of the flow inside a manifold was measured using a micro-particle image velocimetry setup. The study showed that both simple parts like tubes and complex parts such as manifolds can be replicated and investigated. View Full-Text
Keywords: molding technique; micro-particle image velocimetry; refractive index; flow analysis; welded tubes molding technique; micro-particle image velocimetry; refractive index; flow analysis; welded tubes
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Schult, M.; Drobek, C.; Seitz, H. Silicone-Based Molding Technique for Optical Flow Analysis in Transparent Models of Fluidic Components. Appl. Sci. 2018, 8, 512.

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