<p dir="ltr">Particle tracking velocimetry, also known as PTV, is a technology to measure velocity and study the flow field in fluid by observing change in position of individual tracer particles over time. A laser sheet illuminates a thin layer of the sample, in which particles emit fluorescent light and are visible to the camera. Particles at different distances from the microscope lens focal plane are visible, because particle diameter is much smaller than the thickness of laser sheet in micro-scale. The defocused distance changes the shape of particle seen by the camera. Analyzing particle shapes and obtaining the defocused distance of particles completes the third dimension of PTV with the use of a single camera. One approach to obtain defocused distance from particle shape is by comparing particle shapes with calibration images of known defocused distance. The accuracy of PTV relies on the collection of proper calibration images. There are three methods involved in this work. The first approach is to use synthetic images generated by solving Lommel differential equations, which describe the intensity distribution of particles under the impact of defocusing aberration. It was later discovered that the point source assumption inherent in Lommel function causes inaccuracy in generated calibration images. The second approach captures particle images while manually shifting the microscope stage in the z-direction. This approach causes systematic error by ignoring the refractive index of the immersion medium. The third approach is to use a microscale reference ramp as calibration target. Results are experimentally compared with particle shapes obtained from pressure driven flow with known velocity profile.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/26072443 |
| Date | 22 June 2024 |
| Creators | Baoxuan Tao (18858733) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/_b_Defocused_Distance_Prediction_in_3D_Particle_Tracking_b_/26072443 |
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