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The book surveys the state-of-the-art methods that are currently available to model and simulate the presence of rigid particles in a fluid flow. For particles that are very small relative to the characteristic flow scales and move without interaction with other particles, effective equations of motion for particle tracking are formulated and applied (e.g. in gas-solid flows). For larger particles, for particles in liquid-solid flows and for particles that interact with each other or possibly modify the overall flow detailed model are presented. Special attention is given to the description of the approximate force coupling method (FCM) as a more general treatment for small particles, and derivations in the context of low Reynolds numbers for the particle motion as well as application at finite Reynolds numbers are provided. Other topics discussed in the book are the relation to higher resolution immersed boundary methods, possible extensions to non-spherical particles and examples of applications of such methods to dispersed multiphase flows.
This book lays out a vision for a coherent framework for understanding complex systems. By developing the genuine idea of Brownian agents, the author combines concepts from informatics, such as multiagent systems, with approaches of statistical many-particle physics. It demonstrates that Brownian agent models can be successfully applied in many different contexts, ranging from physicochemical pattern formation to swarming in biological systems.
Keywords: alignment, flocking, singular kernel, singular potential, kinetic equation, non-Newtonian fluid.
Multiscale models in social applications combine mean-field and kinetic equations with either microscopic or macroscopic level descriptions. In this book the reader will find not only a wide spectrum of multiscale analysis results (like convergence proofs), but also practically important information such as derivations of mean-field equations, methods to handle hard contacts numerically, to model group behavior, to quantitative estimate microscopic/macroscopic segregation of competing species, to quantitative understand the limits of validity of mass-action kinetics for simple reactions.
This book lays out a vision for a coherent framework for understanding complex systems. By developing the genuine idea of Brownian agents, the author combines concepts from informatics, such as multiagent systems, with approaches of statistical many-particle physics. It demonstrates that Brownian agent models can be successfully applied in many different contexts, ranging from physicochemical pattern formation to swarming in biological systems.
Recently, there has been an increasing focus on various biological and physical systems known as "active matter". Examples of such systems range from individual units, such as motile cells or artificial self-propelled particles, to large systems of interacting active particles or individuals. The emergence of large-scale collective motion, as exhibited by flocks of birds or bacterial colonies, is just one prominent and fascinating example of self-organization in active matter systems. In this work, we discuss different individual-based models of active matter using the concept of active Brownian motion. The first part of this work explores the dynamical behavior of single active particles with a particular emphasis on the impact of so-called active fluctuations. The second part extends the scope of this study to interacting active Brownian particles and their collective behavior. First, a systematic derivation of kinetic equations for active Brownian particles with velocity alignment is presented. Further on, motivated by recent biological observations, a new type of "escape-pursuit" model of collective motion is introduced and successfully employed in modeling collective locust behavior.
This thesis focuses on experimental studies on collective motion using swimming bacteria as model active-matter systems. It offers comprehensive reviews of state-of-the-art theories and experiments on collective motion from the viewpoint of nonequilibrium statistical physics. The author presents his experimental studies on two major classes of collective motion that had been well studied theoretically. Firstly, swimming filamentous bacteria in a thin fluid layer are shown to exhibit true, long-range orientational order and anomalously strong giant density fluctuations, which are considered universal and landmark signatures of collective motion by many numerical and theoretical works but have never been observed in real systems. Secondly, chaotic bacterial turbulence in a three-dimensional dense suspension without any long-range order as described in the first half is demonstrated to be capable of achieving antiferromagnetic vortex order by imposing a small number of constraints with appropriate periodicity. The experimental results presented significantly advance our fundamental understanding of order and fluctuations in collective motion of motile elements and their future applications.