Turbulent and vortical flows are ubiquitous and their characterization is crucial for the
understanding of several natural and industrial processes. Among different techniques to …

Generation and analysis of time-series data is relevant to many quantitative fields ranging
from economics to fluid mechanics. In the physical sciences, structures such as metastable …

The network of interactions among fluid elements and coherent structures gives rise to the
incredibly rich dynamics of vortical flows. These interactions can be described with the use …

We illustrate relationships between classical kernel-based dimensionality reduction
techniques and eigendecompositions of empirical estimates of reproducing kernel Hilbert …

We introduce a network (graph) theoretic community-based framework to extract vortical
structures that serve the role of connectors for the vortical interactions in two-and three …

Lagrangian Coherent Structures (LCS) are flow features which are defined to objectively
characterize complex fluid behavior over a finite time regardless of the orientation of the …

In this study, vortical structures are detected on sparse Shake-The-Box data sets using the
Coherent-Structure Colouring (CSC) algorithm. The performance of this Lagrangian …

This thesis develops a new method for estimating geophysical parameters based on
Lagrangian Coherent Data Assimilation (LaCoDA), a nascent eld combining data …

A novel algorithm to detect coherent structures with sparse Lagrangian particle tracking
data, using Voronoi tessellation and techniques from spectral graph theory, is tested …

The nonlinear interactions amongst vortical structures in fluid flows make their
characterization and control a challenge, particularly in turbulence. In this work, a network …