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Dr. Hendrik Hessenkemper

h.hessenkemperAthzdr.de
Phone: +49 351 260 4719

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orangener PfeilCollegiate works and PhD theses

Experimental methods for optical measurements in bubbly flows

Bubbly flows can be found in many applications in chemical, biological and power engineering. Reliable simulation tools of such flows that allow the design of new processes and optimization of existing one are therefore highly desirable. CFD simulations applying the multi-fluid approach are very promising to provide such a design tool for complete facilities. In the multi-fluid approach, however, closure models have to be formulated to model the interaction between the continuous and dispersed phase. Due to the complex nature of bubbly flows, different phenomena have to be taken into account and for every phenomenon different closure models exist. For a validation of models, experiments that describe as far as possible all relevant phenomena of bubbly flows are needed. Since such data are rare in the literature, several CFD grade experiments are conducted at the department. Concepts to measure gas fraction distributions with corresponding bubble size, shape and velocity together with liquid velocity fields are developed for this purpose.

Methods: Continous Phase

Particle Shadow Velocimetry (PSV)

Particle Image Velocimetry (PIV) is a commonly used tool to determine liquid velocity fields and derive important quantities like vorticity, strain or any kind of turbulence parameter. In bubbly flows, however, the dispersed gas phase can cause an inhomogeneous illumination due to unwanted lateral shadows of the bubbles as well as strong light scattering and reflection at the gas-liquid interfaces. To circumvent these problems, we recently developed particle shadow velocimetry (PSV) method for dispersed two-phase flows. The feature of such a measurement is to use a volumetric direct in-line illumination with e.g. LED-backlights for the region of interest, whereby scattering effects are strongly reduced and no lateral bubble shadows occur. By using a shallow depth of field (DoF), sharp tracer particle shadows positioned inside the DoF region can be identified and the particle displacement is evaluated in a PIV-like manner.

Liquid velocity field in a bubbly flow using the PSV technique.

3D Lagrangian Particle Tracking (LPT)

For 3D measurements, we use the open source code OpenLPT (Tan et al., Exp. Fluids 61, 2020), which uses the Shake-the-Box algorithm to track densely seeded tracer particles in a Lagrangian manner. Images  are  recorded  with  multiple  high-speed  cameras  and  the  flow  is again background  illuminated  with  high-intensity  LED  clusters  (similar  to the aforementioned PSV technique).

3,000 sample trajectories from 3D LPT measurements in a bubble column.

Methods: Dispersed Phase

2D Bubble identification

An automated and reliable processing of bubbly flow images is highly needed to analyse large data sets of comprehensive experimental series. For single bubbles, which occur isolated in recorded images, edge-detection algorithms have proven high reliability and accuracy. A particular difficulty arises in bubbly flow recordings due to overlapping bubble projections in the images, which highly complicates the identification of individual bubbles. Due to the recent advances of deep learning models in the field of pattern recognition and the related task object detection, we are also pursuing developments in this field in order to detect and reconstruct overlapping bubbles in images.

Segmentation and reconstruction of partially overlaid bubbles with deep learning models.

2D Bubble tracking

The subsequent tracking of multiple detected bubbles in close proximity poses further challenges. The tracker not only has to be robust against inaccuracies of the detector, i.e. missing or false detections, but also has to be able to track bubbles that are fully occluded even for multiple times steps, while at the same time having numerous possible associations in the near vicinity. To solve these issues, we also utilize deep learning models and use a graph-based tracking formalism capable of tracking multiple bubbles in bubble swarms over long time spans.

2D-Verfolgung von Blasen in einer Blasenströmung [4].
2D bubble tracking in a bubbly flow.

Work in progress: 3D Bubble tracking

Based on the advances in detecting bubbles in bubbly flow recordings, we currently develop a 3D tracking of deformable bubbles in multi-view measurements. In combination with the 3D LPT method for tracer particles, this allows to capture simultaneously all relevant flow features of both faces in dilute bubbly flow scenarios. Besides a continuous development of our tools and testing of new strategies to detect and track bubbles in 3D, we aim to apply the technique to study bubble interactions in swarms and clustering effects.

Publications