Iacopo Tirelli

Nationality: Italian
Funding entity and Program: ERC StG NEXTFLOW

PhD Thesis

Data-driven enhancement of optical measurement techniques

Date of Defence: 09 June 2025

Supervisors

Stefano Discetti (UC3M) and Andrea Ianiro (UC3M)

Abstract

One of the main limits of PIV is the spatial resolution. Its importance is evident since high dynamic range is required to investigate turbulent flows down to the smallest scales. The goal of the research is to develop data-driven methods to improve the resolution of PIV beyond the Nyquist limit set by the interparticle spacing.
To this end, machine-learning algorithms for super-resolution will be explored, including Generative Advertise Neural Network or data-driven algorithm created specifically for particle-tracking applications.