Emergent vortices in populations of colloidal rollers

Coherent vortical motion has been reported in a wide variety of populations including living organisms (bacteria, fishes, human crowds) and synthetic active matter (shaken grains, mixtures of biopolymers), yet a unified description of the formation and structure of this pattern remains lacking. Here we report the self-organization of motile colloids into a macroscopic steadily rotating vortex. Combining physical experiments and numerical simulations, we elucidate this collective behavior. We demonstrate that the emergent-vortex structure lives on the verge of a phase separation, and single out the very constituents responsible for this state of polar active matter. Building on this observation, we establish a continuum theory and lay out a strong foundation for the description of vortical collective motion in a broad class of motile populations constrained by geometrical boundaries

Taking movement data to new depths : Inferring prey availability and patch profitability from seabird foraging behavior

Funded byNatural Environment Research Council. Grant Number: NE/K007440/1 and Marine Scotland Science and Seabird Tracking and Research (STAR) Project led by the Royal Society for the Protection of Birds (RSPB)Peer reviewedPublisher PD

Spatially hybrid computations for streamer discharges: II. Fully 3D simulations

We recently have presented first physical predictions of a spatially hybrid model that follows the evolution of a negative streamer discharge in full three spatial dimensions; our spatially hybrid model couples a particle model in the high field region ahead of the streamer with a fluid model in the streamer interior where electron densities are high and fields are low. Therefore the model is computationally efficient, while it also follows the dynamics of single electrons including their possible run-away. Here we describe the technical details of our computations, and present the next step in a systematic development of the simulation code. First, new sets of transport coefficients and reaction rates are obtained from particle swarm simulations in air, nitrogen, oxygen and argon. These coefficients are implemented in an extended fluid model to make the fluid approximation as consistent as possible with the particle model, and to avoid discontinuities at the interface between fluid and particle regions. Then two splitting methods are introduced and compared for the location and motion of the fluid-particle-interface in three spatial dimensions. Finally, we present first results of the 3D spatially hybrid model for a negative streamer in air

Computational models for turbulent bubbly flows in bubble columns

Bubble columns are widely used in the chemical and pharmaceutical industries as gas--liquid contactors because of their simple construction and ability to provide high contact area for mass and heat transfer. The design and scale up of bubble columns depends on heat/mass transfer and mixing characteristics provided by it. These two factors highly depend on the bubbly flow hydrodynamics of the column. Although simple in construction, the bubbly flow hydrodynamics inside bubble columns are complex due the presence of turbulence and bubble--bubble interactions (coalescence, breakup), thus, the development of accurate CFD (Computational Fluid Dynamics) models that describe bubbly flows are important and challenging. Two-fluid models are widely used as CFD models for the prediction of bubbly flows in bubble columns due to its low computational cost. In this thesis computational models are developed in order to improve the capabilities of two-fluid models in predicting bubbly flows in bubble colum

Colloids with perception-dependent motility: Dynamics and structure of rotating aggregates and directed swarms

In this thesis we focus on two-dimensional systems of colloids governed by Brownian dynamics that are able to sense their neighbors via a visual-type of perception, then they can switch their motility between passive and active depending on a given perception parameter. Our setup corresponds to experiments performed in Bechinger's lab in Konstanz University, where they have considered cases of quorum-sensing (isotropic perception) and visual-type of perception (anisotropic perception). Here we study the case when the perception is both anisotropic and also misaligned with respect to the self-propulsion orientation vector. The purpose of this thesis is to characterize the emergence of collective behaviors in this model, as well as the dynamics and structural changes of the system. We provide novel strategies where the interplay between perception and motility of the agents allows them to self-organize into rotating aggregates and directed swarms. Our study sheds light in the understanding of active automatons with adaptable collective states, and can be implemented for example in macroscopic swarms of robots, or microscopic colloids activated by light. In chapter 2 we introduce the ingredients necessary to perform particle-based numerical simulations, like the integration method, interaction forces, boundary conditions, and optimization techniques. We also briefly comment on the organization and design of the Brownian dynamics code we developed to obtain results shown in this thesis. In chapter 3, we consider systems of colloids with discontinuous motility and misaligned visual perception. We explain how this type of interaction generically leads to aggregation and rotation of cohesive structures. Then, we characterize the resulting dynamics for different system parameters. In chapter 4 we characterize different types of circular structures that emerge in this model, as a function of the perception threshold and misalignment angle. We also derive analytical expressions from conservation equations corresponding to a solid-body rotation of a continuum aggregate driven by activity at the interface. We find an agreement between theory and numerical results for the density, size, and angular velocity of the aggregates as a function of the system parameters. In chapter 5 we consider a binary mixture of particles with different misalignment angle. Under given conditions, we find the striking case where the system aggregates, self-sorts into species subdomains which counter-rotate leading to a self-propulsion of the overall system. We characterize this process by means of dynamic parameters and their averages in steady state. We find cases where the directed swarms can either dilute or remain robust, or where the aggregate is species homogeneous and its center of mass describes random motion. We also study the swarms shape and how it can change for varying misalignment angle. In chapter 6 we study cases when the mixture is non-equimolar. In this case the system self-organizes into swarms describing helical trajectories. We also show an example of an externally guided system, where we dynamically change the misalignment angle of the particles, leading to a swarm performing run-and-turn motion

Comparing plasma fluid models of different order for 1D streamer ionization fronts

We evaluate the performance of three plasma fluid models: the first order reaction-drift-diffusion model based on the local field approximation; the second order reaction-drift-diffusion model based on the local energy approximation and a recently developed high order fluid model by Dujko et al (2013 J. Phys. D 46 475202) We first review the fluid models: we briefly discuss their derivation, their underlying assumptions and the type of transport data they require. Then we compare these models to a particle-in-cell/Monte Carlo (PIC/MC) code, using a 1D test problem. The tests are performed in neon and nitrogen at standard temperature and pressure, over a wide range of reduced electric fields. For the fluid models, transport data generated by a multi-term Boltzmann solver are used. We analyze the observed differences in the model predictions and address some of the practical aspects when using these plasma fluid models