Theoretical formulation of streak failure conditions and numerical investigation to optimize the illumination code of particle streak velocimetry
Tóm tắt
In a typical coding method for particle streak velocimetry, the streak shape is divided into two dots and one line by controlling the illumination timing. In this study, several parameters were formulated to optimize the streak shape in a uniform flow using a theoretical approach. In contrast, for non-uniform flows, the formulation of optimal conditions does not provide a common criterion for all flow fields. Therefore, we developed a streak simulation technique based on a two-dimensional flow field and investigated a numerical approach to identify the optimization conditions for non-uniform flows. The test flow fields considered were the Couette flow, von Karman vortex, and Rankine vortex, with the streak number considered one of the parameters affecting the failure of the streak shape, increasing from 100 to 1300. In addition, another parameter, the magnification factor acting on the mean velocity of the flow field, was increased from 0.2 to 1.2. Furthermore, five types of streak failure factors were identified and analyzed based on their frequency of occurrence. The results of the two-dimensional streak simulation showed that the condition for maximizing the number of non-failure streaks for each flow field was successfully identified, and an estimation of the optimal illumination time was obtained. Additionally, vector densities of 0.001 vectors per pixel were achieved for the von Karman and Rankine vortices. The streak simulation can be an effective tool for evaluating the availability of PSV.
Tài liệu tham khảo
Adrian RJ (1991) Particle-imaging techniques for experimental fluid mechanics. Annu Rev of Fluid Mech 23(1):261–304. https://doi.org/10.1146/annurev.fl.23.010191.001401
Dong X, Wang X, Zhou W, Wang F, Tang X, Cai X (2022) 3D particle streak velocimetry by defocused imaging. Particuology 72(6):1–9. https://doi.org/10.1016/j.partic.2022.02.002
Fan L, Vena P, Savard B, Xuan G, Fond B (2021) High-resolution velocimetry technique based on the decaying streaks of phosphor particles. Opt Lett 46(3):641–644. https://doi.org/10.1364/OL.416121
Fan L, Vena P, Savard B, Fond B (2022) Experimental and numerical investigation on the accuracy of phosphor particle streak velocimetry. Exp Fluids 63(10):165. https://doi.org/10.1007/s00348-022-03511-9
Feng, M., Zhou, W., and Wang, F. Application of particle streak velocimetry based on binocular vision in cascade flow channel. In: Proceedings of Global Power and Propulsion Society, Xi’an, China, pp 18–20 October 2021.
Kato F, Shimizu I (2001) Optical cross-correlation of PTV image under a deformed double exposure. Trans Visualization Soc of Japan 21(5):86–93. https://doi.org/10.3154/tvsj.21.86. (in Japanese)
Khalighi B, Lee YH (1989) Particle tracking velocimetry: an automatic image processing algorithm. Appl Opt 28(20):4328–4332. https://doi.org/10.1364/AO.28.004328
Sakakibara, J., and Ninomiya, N. 2018 PIV Handbook (in Japanese), 2nd edition, Morikita, pp 83–85.
Wang Z, Liu Y (2017) Comparison of three particle based velocimetry techniques. Trans Am Nucl Soc 117(1):1707–1708
Wang H, Li X, Shao X, Wang B, Lin Y (2017) A colour-sequence enhanced particle streak velocimetry method for air flow measurement in a ventilated space. Build Environ 112(1):77–87. https://doi.org/10.1016/j.buildenv.2016.11.015