| KEYWORD |
Application of the complex network theory for the analysis of turbulent flows
Thesis abroad
keywords COMPLEX NETWORKS, DATA MINING, TURBULENCE
Reference persons LUCA RIDOLFI, STEFANIA SCARSOGLIO
External reference persons G. Iacobello (Polito), J. G. M. Kuerten (TUE), P. Salizzoni (ECL)
Thesis type EXPERIMENTAL AND SIMULATION, THEORETICAL AND NUMERICAL
Description Turbulent flows represent a fundamental research topic, since most flows occurring in industrial applications (e.g., flow through pipes, vehicles wake and combustion processes) and in nature (e.g., river and oceanic currents and atmospheric flows) are turbulent. Nowadays, novel tools are continuously required in order to extract information about the dynamics of turbulent flows and to manage big-data extracted from more and more accurate numerical/experimental simulations.
In this context, complex networks emerged in last two decades as a powerful and versatile tool to study complex systems as turbulence. The complex networks theory combines elements of the graph theory – where discrete elements are linked each other to highlight the features of complex systems – and other disciplines such as statistical physics and data mining. So far, complex networks have been successfully applied in many contexts, such as internet, economy-finance, social networks, biology (e.g., metabolic and neuronal networks). It is more recent the application of complex networks for studying physical/engineering problems, such as climate network analyses.
This thesis proposal aims to give insights into the dynamics of turbulent flows (i.e., a fluid dynamics problem) by means of the tools offered by complex networks theory. Consequently, this approach is original and strongly multidisciplinary, since complex networks still represent a not-completely-explored alternative to classical statistical tools for the study of turbulence. More in detail, the following thesis are proposed:
o Eulerian approach for the study of turbulent flows (e.g., wall bounded turbulence) – spatial network (possible thesis abroad at the Eindhoven University of Technology, TUE, Prof. J. G. M. Kuerten);
o Lagrangian approach for the analysis of turbulent mixing – spatiotemporal network (possible thesis abroad at the Eindhoven University of Technology, TUE, Prof. J. G. M. Kuerten);
o Time series analysis of turbulent flows (e.g., visibility algorithm, recurrence networks);
o Analysis of transport processes of pollutants over urban environments (low atmosphere boundary layer) – single and multilayer networks approach (possible thesis abroad at the École centrale de Lyon, ECL, Prof. P. Salizzoni).
The goal of the thesis proposals is to provide a novel perspective on the spatiotemporal characterization of turbulence, with particular emphasis to wall bounded turbulence and dispersion processes.
Required skills Good programming/algorithms developing skills (e.g., Matlab, R); high interest into interdisciplinary applications. For further details, please contact references.
Deadline 25/07/2021
PROPONI LA TUA CANDIDATURA