Advanced iterative particle reconstruction for Lagrangian particle tracking

Abstract

The method of iterative particle reconstruction (IPR), introduced by Wieneke (Meas Sci Technol 24:024008, 2013), constitutes a major step toward Lagrangian particle tracking in densely seeded flows (Schanz et al. in Exp Fluids 57:1–27, 2016). Here we present novel approaches in several key aspects of the algorithm, which, in combination, triple the working range of IPR in terms of particle image densities. The updated method is proven to be fast, accurate and robust against image noise and other imaging artifacts. Most of the proposed changes to the original processing are easy to implement and come at low computational cost. Furthermore, a bundle adjustment scheme that simultaneously updates the 3D locations of all particles and the camera calibrations is introduced. While the particle position optimization proved to be more effective using localized ‘shake’ schemes, this so-called global shake scheme constitutes an effective measure to correct for decalibrations and vibrations, acting as an in-situ single-image volume-self-calibration. Further optimization strategies using such approaches are conceivable. Graphic abstract

3D Lagrangian Particle Tracking in Fluid Mechanics

“…Increased particle track densities in the measurement volume can be achieved with scanning 3D PTV techniques (Hoyer et al 2005, Kozul et al 2019, reaching higher ppv values for relatively low flow velocities. Nowadays, state-of-the-art 3D LPT techniques can reach high particle image densities of ∼0.05-0.2 ppp using the Shake-The-Box (STB) method (Schanz et al 2016, Jahn et al 2021, Leclaire et al 2021, Sciacchitano et al 2021b.…”

“…The STB technique is an advanced 3D LPT method that combines the triangulation-based advanced iterative particle reconstruction (IPR) technique (Wieneke 2012, Jahn et al 2021 with the exploitation of the temporal and spatial coherence of Lagrangian particle tracks in the investigated flow. STB enables the processing of particle image densities up to N I = 0.2 ppp under good experimental conditions with an almost complete suppression of ghost particles.…”

“…Due to the iterative shifting, while approaching the minimum of R, this process is often referred to as shaking the particles. This gradient decent can be determined either numerically (Wieneke 2012) or analytically ( Jahn et al 2021). A different approach by uses a kernel optimization to deduct the optimal particle position.…”

Effects of anisotropy on the geometry of tracer particle trajectories in turbulent flows

“…A system of multiple cameras records time-resolved images of the tracer particles, being illuminated by a suitable light source (typically a highspeed laser or LEDs). STB employs Iterative Particle Reconstruction [22,23] to reconstruct 3D particle positions, combined with a temporal predictor-corrector scheme of known tracks. The combination of these methods allows to track particles in high numbers, while avoiding the generation of false (ghost) tracks.…”

Experimental study of turbulent bubbly jet. Part 1. Simultaneous measurement of three-dimensional velocity fields of bubbles and water

“…As a result, the image of the bubbles is completely removed and STB tracking can be performed on pure particle images (see figure 5 c ). The particle position reconstruction with STB was performed using advance iterative particle reconstruction (Wieneke 2012; Jahn, Schanz & Schröder 2021). The measurement area exhibits a high dynamic velocity range: regions with low velocities (large quiescent parts surrounding the plume) are in proximity to regions with at least an order of magnitude higher velocity in the centre of the plume.…”