Professor Dirk Lucas

Dr. Dirk Lucas is head of the Computational Fluid Dynamics (CFD) division at the Institute of Fluid Dynamics of the Helmholtz – Zentrum Dresden-Rossendorf (HZDR), Germany. His research focuses on the development and validation of CFD-models for multiphase flows in medium and large scale applications, e.g. in chemical engineering and nuclear reactor safety. In particular he is interested in fundamental phenomena in poly-disperse bubbly flows and in a corresponding modelling in the frame of CFD codes.

Dirk Lucas studied physics at the Technical University of Dresden from 1983 to 1988 and continued with his doctoral thesis at the Technical University of Zittau. He received his PhD in 1991 from the Technical University of Dresden. From 1992 to 2011 he worked as a research fellow at the Research Center Dresden-Rossendorf and became head of the CFD department in 2012. He is vice chair of the Virtual International Research Institute of Two-Phase Flow and Heat Transfer (VIR2AL: http://2phaseflow.org) and member of the editorial boards of the journals "Multiphase Science and Technology" and "Experimental and Computational Multiphase Flow". Dirk Lucas is author or co-author more than 200 scientific papers in peer-reviewed journals.

Abstract:

The temporal and spatial evolution of bubble clusters is a fundamental aspect of the collective behaviour of freely rising bubble swarms. Experimental investigation of this phenomenon is challenging as it requires Lagrangian tracking of the individual bubbles, especially for a three-dimensional measurement in dense swarms of deformable bubbles. Here, a new framework is presented to overcome this challenge. The use of dedicated deep learning models enables the detection and tracking of bubbles in 3D at relatively high image coverage.

By combining our in-house 3D Lagrangian bubble-tracking tool with the dense particle-tracking algorithm OpenLPT, bubbles and tracers are tracked simultaneously in 3D. Based on an advanced bubble cluster detection and tracking strategy, first the lifetime of bubble clusters is characterized as a function of their size. Subsequently, the role of clustering on the mean bubble rise velocity is investigated by tracking individual bubble clusters. It is also considered how the cluster effect compares to bubble-induced turbulence in influencing the bubble rise velocity. Finally, a scaling model for the rise velocity of bubbles rising in a swarm is constructed.