Characterization of cavitation during the closing of mechanical (heart) valves

Our main goal in this project is to tackle the complex challenge of data-driven low-dimensional modeling and control of multiphase flows. Although the methods we intend to investigate are fundamental and generalizable to a large class of problems, we focus on a specific scenario of friction drag reduction in liquid flows by gas injection, a vibrant area of fundamental research for several decades. Despite enormous potential, there are still many unknowns both regarding flow physics (e.g. drag reduction mechanism), as well as real-world applications (e.g. optimal gas supply in ships). Control schemes, with the notable exception of a simple open-loop control of air injection, have been almost non-existent.
In this project, we aim to develop data-driven techniques for reduced order modelling of such flows, which will enable successful closed-loop control. To achieve this ambitious goal, we will exploit various flow measurement techniques (including particle image velocimetry, pressure and drag measurements) to ensure optimal data collection and representation of different flow states

Project is funded by Cohesie Round 2022

Chair:
Multiphase Systems

Involved People:
Semanur Küçük
Dr. A. (Angeliki) Laskari
Dr. C. (Cosimo) Della Santina (CoR, ME)