Multi-Δt 3D-PTV based on Reynolds decomposition

A novel approach is investigated to extend the range of measurable velocities by 3D-PTV systems. The method is specifically conceived for robotic volumetric PTV measurements, but it has applications for other similar techniques. The multi-Δt method relies upon combining the information from two or more sets of double-frame images with pulse separation of different time duration. Measurements with a short time separation yield a robust particle velocity field estimation with a higher percentage of valid vectors, yet a low measurement precision. Conversely, measurements with longer time separation potentially offer a higher measurement precision but suffer from an increased probability of spurious particle pairing. Reynolds decomposition is used to combine the two (dual-Δt) sets where a predictor for the mean particle displacement and its statistical dispersion is used to pair particle recordings from a longer time separation. For this reason, this method is aimed at the analysis of turbulent flows where the Reynolds decomposition is meaningful (e.g. turbulent flows with steady/quasi-steady boundary conditions). The extent of the search region is selected dynamically, based on the estimate of the velocity fluctuations from the short time separation evaluation. A more advanced variant of the algorithm contemplates the progressive increase of the pulse separation (multi-Δt) until the expected dispersion of data due to turbulent fluctuations eventually exceeds the distance between neighbouring particles. Flow measurements in the near wake of a truncated cylinder obstacle and of an Ahmed body are carried out to examine the performance of the proposed method. Reference data is taken from time-resolved multi-frame analysis based on the Shake-The-Box (STB) algorithm. The two experiments differ for the measurement principle used: The first one is conducted with a tomographic-like system (large aperture), whereas the latter uses coaxial volumetric velocimetry. The rate of c
Aerodynamics
Aerodynamics, Wind Energy & Propulsion