0000000000304202
AUTHOR
Peteris Zvejnieks
MHT-X: Offline Multiple Hypothesis Tracking with Algorithm X
An efficient and versatile implementation of offline multiple hypothesis tracking with Algorithm X for optimal association search was developed using Python. The code is intended for scientific applications that do not require online processing. Directed graph framework is used and multiple scans with progressively increasing time window width are used for edge construction for maximum likelihood trajectories. The current version of the code was developed for applications in multiphase hydrodynamics, e.g. bubble and particle tracking, and is capable of resolving object motion, merges and splits. Feasible object associations and trajectory graph edge likelihoods are determined using weak mas…
Dynamic mode decomposition of magnetohydrodynamic bubble chain flow in a rectangular vessel
We demonstrate the first application of dynamic mode decomposition (DMD) to bubble flow with resolved dynamic liquid/gas boundaries. Specifically, we have applied DMD to the output of numerical simulations for a system where chains of bubbles ascend through a rectangular liquid metal vessel. Flow patterns have been investigated in the vessel and bubble reference frames. We show how gas flow rate and applied magnetic affect bubble wake flow and larger-scale flow structures within the liquid metal vessel by examining the velocity field mode statistics over trajectory time and total flow time as well as the computed mode velocity fields. The results of this proof-of-concept study indicate that…