3D velocity field reconstruction of gas-liquid two-phase flow based on space-time multi-scale binocular-PIV technology

Abstract

for particle image velocimetry (PIV) technique, the two-dimensional (2D) PIV by one camera can only obtain 2D velocity field, while three-dimensional (3D) PIV based on tomography by three or four cameras is always complex and expensive. In this work, a binocular-PIV technology based on two cameras was proposed to reconstruct the 3D velocity field of gas-liquid two-phase flow, which is a combination of the binocular stereo vision and cross-correlation based on fast Fourier transform (CC-FFT). The depth of particle was calculated by binocular stereo vision on space scale, and the plane displacement of particles was acquired by CC-FFT on time scale. Experimental results have proved the effectiveness of the proposed method in 3D reconstruction of velocity field for gas-liquid two-phase flow.

References

[1] AdrianR J. Twenty years of particle image velocimetry[J]. Experiments in fluids, 2005, 39(2):159-169

[2] YangZ, WangS, ZhengJ, et al.. 20 kHz dual-plane stereo-PIV measurements on a swirling flame using a two-legged burst-mode laser[J]. Optics letters, 2020, 45(20):5756

[3] DoroshenkoA, LeeN, MacdonaldC, et al.. Decline of influenza and respiratory viruses with COVID-19 public health measures: Alberta, Canada[J]. Mayo clinic proceedings, 2021, 96(12): 3042-3052

[4] TanZ P, AlarconR, AllenJ, et al.. Development of a high-speed plenoptic imaging system and application to marine biology PIV[J]. Measurement science and technology, 2020, 31(5):054005

[5] ShuA P, RubinatoM, QinJ P, et al.. The hydrodynamic characteristics induced by multiple layouts of typical artificial M-type reefs with sea currents typical of Liaodong Bay, Bohai Sea[J]. Journal of marine science and engineering, 2021, 9(11): 1155

[6] LiuA H, LinJ J, ZhuangY J. PIV experimental study on the phase change behavior of phase change material with partial filling of metal foam inside a cavity during melting[J]. International journal of heat and mass transfer, 2022, 187: 122567

[7] MinichielloA, ArmijoD, MukherjeeS, et al.. Developing a mobile application-based particle image velocimetry tool for enhanced teaching and learning in fluid mechanics: a design-based research approach[J]. Computer applications in engineering education, 2021, 29(3): 517-537

[8] PakhovV V, StepanovR P, KusyumovA N, et al.. Investigation of aerodynamic performance of a multipurpose medium lift helicopter with different rear fuselage geometries[J]. Russian aeronautics, 2021, 64(2):248-255

[9] AdrianR J. Scattering particle characteristics and their effect on pulsed laser measurements of fluid flow: speckle velocimetry vs. particle image velocimetry[J]. Applied optics, 1984, 23(11):1690

[10] SuY, ZhangB, ChenY, et al.. 3D velocity and temperature distribution measurement and characteristic analysis of swirling combustion[J]. Measurement, 2022, 193: 110949

[11] PEREZ J M, SASTRE F, CLAINCHE S L, et al. Three-dimensional flow field reconstruction in the wake of a confined square cylinder using planar PIV data[J]. Experimental thermal and fluid science, 2021: 110523.

[12] HamdiJ, AssoumH H, AlkheirM, et al.. Analysis of the 3D flow of an impinging jet on a slotted plate using TR-Tomo PIV and proper orthogonal decomposition[J]. Energy reports, 2020, 6(S9): 158-163

[13] LiY F, BloisG, KazemifaR, et al.. Quantifying the dynamics of water-CO₂ multiphase flow in microfluidic porous media using high-speed micro-PIV[C], 2020, New York, ASME Virtual, Online

[14] DuH, LiM G, LiuS X. Study of particle image velocimetry systems based on binocular vision[J]. Systems engineering and electronics, 2007, 29(11):5

[15] ZhangZ. A flexible new technique for camera calibration[J]. IEEE transactions on pattern analysis and machine intelligence, 2000, 22(11): 1330-1334

[16] ZabihR, WoodfillJ. Non-parametric local transforms for computing visual correspondence[J]. Lecture notes in computer science, 1994, 801(1):151-158