Gas Flow Measurements by 3D Particle Tracking Velocimetry Using Coloured Tracer Particles

Abstract

This work describes an original approach for 3D Particle Tracking Velocimetry (3D PTV), applicable also for gaseous flows and based on tracer particles of different colours. On the images acquired by several cameras, tracer particles are handled by colour recognition and 3D localisation. Then, the PTV tracking algorithm rebuilds the trajectories of the tracer particles using a criterion of Minimum Acceleration. Theoretical and numerical calculations are first presented to demonstrate that the employed coloured tracer particles follow in a suitable manner the considered gas flows. The test cases analysed comprise low Reynolds number flows involving a variety of interesting features, in particular boundary layer separation, continuous acceleration and recirculations. The experimental setup and the 3D PTV procedure are then described. All results are analysed in a quantitative manner and demonstrate the performance of the developed measurement strategy in gas flows.

Comparison of different tracers for PIV measurements in EHD airflow

“…According to Kallio and Stock (1992), the tracer particle is suitable when the Stokes number . Recently, Tarlet et al (2011) and Burgmann et al (2001) reported that for a Stokes number , the deviation of the tracer particle is negligible.…”

“…2. Their size and density should fulfill conditions avoiding sedimentation and inertial effects (Tarlet et al (2011)). 3.…”

“…If Ar → 0, the particle is not influenced by buoyancy. For tracer particles are not, or only slightly, affected by sedimentation phenomena (Tarlet et al (2011)). Atten et al (1989) introduced the parameter M (also called EHD "Mobility ratio" (IEEE -DEIS-EHD technical committee (2003)), which defines the relationship between the mobility of gas molecules and the mobility of particles in the gas in the presence of an electric field (Eq.…”

Improved 3-D Particle Tracking Velocimetry with Colored Particles

“…The computation of trajectories is described in detail in a separate publication [25]. Figure 9 demonstrates the ability to obtain PTV data within the whole three-dimensional volume of observation around three winglets (Case 1).…”