Modelling flying formations and vortex ring motions
Christiana is an Assistant Professor at the Courant Institute of Mathematical Sciences (New York University) working in the Applied Math Lab, primarily with Leif Ristroph and Jun Zhang. Her interests are in using modeling, numerical simulations, and experiments to study fluid dynamical problems, with an emphasis on fluid-structure interactions.
Currently Christiana is working on understanding the role of flow interactions in flying bird formations and the hydrodynamics of swimming fish.
Abstract
We consider two problems in fluid dynamics: the collective locomotion of flying animals and the interaction of vortex rings with fluid interfaces. First, we present a model of formation flight, viewing the group as a material whose properties arise from the flow-mediated interactions among its members. This aerodynamic model explains how flapping flyers produce vortex wakes and how they are influenced by the wakes of others. Long in-line arrays show that the group behaves as a soft, excitable "crystal" with regularly ordered member "atoms" whose positioning is susceptible to deformations and dynamical instabilities. Second, we delve into the phenomenon of vortex ring reflections at water-air interfaces. Experimental observations reveal reflections analogous to total internal reflection of a light beam. We present a vortex-pair--vortex-sheet model to simulate this phenomenon, offering insights into the fundamental interactions of vortex rings with free surfaces.
Spontaneous shape transformations of active surfaces
Alexander Mietke is a theoretical physicist working on active and living matter. He frequently collaborates with experimentalists who study processes at the cell, tissue and organism scale to identify minimal physical principles that guide these processes. This often inspires new theoretical work on topics in non-equilibrium soft matter physics, more broadly in the self-organization of mechanical and chemical patterns in active matter, the emergent shape dynamics of membranes and active surfaces, liquid crystals in complex geometries, chirality in active systems, as well as in developing coarse-graining and inference approaches that are directly applicable to experimental data.
Abstract
Biological matter has the fascinating ability to autonomously generate material deformations via intrinsic active forces, where the latter are often present within effectively two-dimensional structures. The dynamics of such “active surfaces” inevitably entails a complex, self-organized interplay between geometry of a surface and its mechanical interactions with the surrounding. The impact of these factors on the self-organization capacity of surfaces made of an active material, and how related effects are exploited in biological systems, is largely unknown.
In this talk, I will first discuss general numerical challenges in analysing self-organising active surfaces and the bifurcation structure of emergent shape spaces. I will then focus on active surfaces with broken up-down symmetry, of which the eukaryotic cell cortex and epithelial tissues are highly abundant biological examples. In such surfaces, a natural interplay arises between active stresses and surface curvature. We demonstrate that this interplay leads to a comprehensive library of spontaneous shape transformations that resemble stereotypical morphogenetic processes. These include cell-division-like invaginations and the autonomous formation of tubular surfaces of arbitrary length, both of which robustly overcome well-known shape instabilities that would arise in analogue passive systems.
Optimal design of odd active solids
Anton Souslov is an Associate Professor of Theoretical Statistical Physics working on the theory of soft materials, including mechanical metamaterials, active matter, topological states, and polymer physics.
Abstract
Active solids consume energy to allow for actuation and shape change not possible in equilibrium. I will first introduce active solids in comparison with their active fluid counterparts. I will then focus on active solids composed of non-reciprocal springs and show how so-called odd elastic moduli arise in these materials. Odd active solids have counter-intuitive elastic properties and require new design principles for optimal response. For example, in floppy lattices, zero modes couple to microscopic non-reciprocity, which destroys odd moduli entirely in a phenomenon reminiscent of rigidity percolation. Instead, an optimal odd lattice will be sufficiently soft to activate elastic deformations, but not too soft. These results provide a theoretical underpinning for recent experiments and point to the design of novel soft machines.
Machine Learning