Abstract Summary (Max 250 words)
Mechanically agitated tanks are widely used in the chemical and biochemical industries. The flow developing in mixing tanks is highly complex and three-dimensional. Although few attempts have been made to locally measure the three components of velocity in the three spatial directions, the experimental techniques usually provide two-dimensional Eulerian data. Only recent developments (Shake-the-Box (STB) technique; Wieneke, 2013; Schanz et al., 2013, 2016) have made it possible to measure highly resolved spatial and temporal particle tracks for a high-density particle seeding (typically 0.05 particles per pixel). The objective of this study is to evaluate the accuracy of 4D-LPT in the turbulent regime and to understand its limitations through a comparative study with Large Eddy Simulation. In this context, 4D-LPT measurements are conducted. To the author knowledge this work is one of the first attempt where such a technique has been employed to study mixing tanks. It offers a unique opportunity to measure local and time-resolved velocity fields in a volume. The fluid investigated is water. The impeller is a classical Rushton turbine. Two mixing frequencies are analyzed (N∈[50,100], where N is the mixing frequency. Four cameras (Vision Research VEO 640) are used with 100mm Zeiss Milvius lenses with an aperture of F/16 and 540nm band-pass filters and Scheimpflug V3 mounts (LaVision). The investigated volume is homogeneously illuminated with a high frequency laser Photonics Industries DMX60-527-DH (2×60mJ at 1kHz). The measurement volume has the following dimensions: x=175.5mm, y=232.5mm, z=80mm, starting 40mm above the bottom of the mixing tank. First, Eulerian data are investigated. Local and time-resolved data are post-processed to evaluate ensemble and phase-averaged velocity fields in order to investigate organized structures. In particular, the development of coherent structures in the wake of the impeller is characterized. Furthermore, organized and turbulent motions are assessed through POD for both experimental and numerical data. Finally, Lagrangian data are studied with specific tools to 1) understand the flow dynamics at particle level and 2) characterize the loss of accuracy during the conversion from Lagrangian to Eulerian framework.
