Hidden Coherence in Complex Flows

Mattia Serra

Assistant Professor of Physics
University of California San Diego

Seminar Information

Seminar Series
Fluid Mechanics, Combustion, & Engineering Physics

Seminar Date - Time
October 3, 2022, 3:00 pm
-
4:15

Seminar Location
Hybrid: In Person & Zoom (connection in link below)

Engineering Building Unit 2 (EBU2)
Room 479

Seminar Recording Available: Please contact seminar coordinator, Jake Blair at (j1blair@eng.ucsd.edu)

Professor Mattia Serra

Abstract

From environmental sciences to aerodynamic separation, fluid flows exhibit entangled stretching and
folding, leading to chaos. Using concepts from calculus of variations, geometry and fluid mechanics, I
discuss the development of mathematical methods that unveil the organizers of the dynamical systems’
phase space. While several stretching measures exist as Finite-time Lyapunov exponents, Cauchy--Green
and rate-of-strain tensors, less is known about folding. I will present analytic results for the evolution of
Lagrangian Folding of material lines and surfaces in 2D and 3D flows. I illustrate our results on
experimental data related to highly unsteady separated flows and search and rescue operations at sea. I
show how our techniques uncover previously unknown structures, including the onset of aerodynamic
separation and hidden short-term attractors on the ocean surface, currently adopted by the US Coast
Guard.

Speaker Bio

Mattia Serra earned a Ph.D. in Nonlinear Dynamics from ETH Zurich (2014-2017) before joining the
division of Applied Mathematics at Harvard University as a Schmidt Science Fellow until 2020. In
September 2020, Mattia joined the Department of Physics at the University of California San Diego as an
Assistant Professor. Professor Serra’s group develops geometric methods and mathematical models to
study complex physical and biological systems. These systems are typically nonlinear, multi-scale, and
chaotic. Thus, they require new ideas to 1) best uncover the underlying causal mechanisms from their
footprint on data, and 2) predict and control their behavior from the essential driving processes.

Selected Awards: Schmidt Science Fellow (2018), ETH Medal Award for Outstanding Doctoral Thesis
(2018), Early Postdoc Mobility Fellowship - Swiss National Science Foundation (2019).
More on Serra’s group: https://www.mattiaserra.com/