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Development of a reduced-order model of multiple vortex tornadoes from small-scale experimental data

In nature, a tornado can be composed of several subvortices (or suction vortices) revolving around the centre of their parent tornado. These multiple-vortex tornadoes are among the largest, strongest and most destructive tornadoes known to date. Despite their reputation, the fluid dynamics of multiple-vortex tornadoes remains poorly understood. As part of this work, the flow of two- and three-vortex tornadoes has been modelled and captured using a small-scale fundamental model. In particular, hypothetical attenuation or amplification processes between two- and three-vortex systems will be considered.

The objective of this project is to develop a reduced-order model of multiple-vortex systems based on the collected experimental data. We will explore the use of the so-called Zernicke polynomials as a mathematical basis onto which the data will be projected. The results will be compared to a proper orthogonal decomposition of the dataset as well as to analytical point vortex models. The flows will be studied based on their velocity potential and vorticity fields.

Required knowledge

Knowledge of fluid dynamics (potential flows). Knowledge of engineering mathematics (linear algebra, multivariable calculus). Ability to program in MATLAB or Python.

Desired program of studies

Masters with project

Research domains

Sustainable Development, the Circular Economy and Environmental Issues



To be discussed with the professor.

Additional information

Starting: Fall 2023