8,554 research outputs found
Simulations of propelling and energy harvesting articulated bodies via vortex particle-mesh methods
The emergence and understanding of new design paradigms that exploit flow
induced mechanical instabilities for propulsion or energy harvesting demands
robust and accurate flow structure interaction numerical models. In this
context, we develop a novel two dimensional algorithm that combines a Vortex
Particle-Mesh (VPM) method and a Multi-Body System (MBS) solver for the
simulation of passive and actuated structures in fluids. The hydrodynamic
forces and torques are recovered through an innovative approach which crucially
complements and extends the projection and penalization approach of Coquerelle
et al. and Gazzola et al. The resulting method avoids time consuming
computation of the stresses at the wall to recover the force distribution on
the surface of complex deforming shapes. This feature distinguishes the
proposed approach from other VPM formulations. The methodology was verified
against a number of benchmark results ranging from the sedimentation of a 2D
cylinder to a passive three segmented structure in the wake of a cylinder. We
then showcase the capabilities of this method through the study of an energy
harvesting structure where the stocking process is modeled by the use of
damping elements
Automated visual tracking for studying the ontogeny of zebrafish swimming
The zebrafish Danio rerio is a widely used model organism in studies of genetics, developmental biology, and recently, biomechanics. In order to quantify changes in swimming during all stages of development, we have developed a visual tracking system that estimates the posture of fish. Our current approach assumes planar motion of the fish, given image sequences taken from a top view. An accurate geometric fish model is automatically designed and fit to the images at each time frame. Our approach works across a range of fish shapes and sizes and is therefore well suited for studying the ontogeny of fish swimming, while also being robust to common environmental occlusions. Our current analysis focuses on measuring the influence of vertebra development on the swimming capabilities of zebrafish. We examine wild-type zebrafish and mutants with stiff vertebrae (stocksteif) and quantify their body kinematics as a function of their development from larvae to adult (mutants made available by the Hubrecht laboratory, The Netherlands). By tracking the fish, we are able to measure the curvature and net acceleration along the body that result from the fish's body wave. Here, we demonstrate the capabilities of the tracking system for the escape response of wild-type zebrafish and stocksteif mutant zebrafish. The response was filmed with a digital high-speed camera at 1500 frames s–1. Our approach enables biomechanists and ethologists to process much larger datasets than possible at present. Our automated tracking scheme can therefore accelerate insight in the swimming behavior of many species of (developing) fish
Entropic Lattice Boltzmann Method for Moving and Deforming Geometries in Three Dimensions
Entropic lattice Boltzmann methods have been developed to alleviate intrinsic
stability issues of lattice Boltzmann models for under-resolved simulations.
Its reliability in combination with moving objects was established for various
laminar benchmark flows in two dimensions in our previous work Dorschner et al.
[11] as well as for three dimensional one-way coupled simulations of
engine-type geometries in Dorschner et al. [12] for flat moving walls. The
present contribution aims to fully exploit the advantages of entropic lattice
Boltzmann models in terms of stability and accuracy and extends the methodology
to three-dimensional cases including two-way coupling between fluid and
structure, turbulence and deformable meshes. To cover this wide range of
applications, the classical benchmark of a sedimenting sphere is chosen first
to validate the general two-way coupling algorithm. Increasing the complexity,
we subsequently consider the simulation of a plunging SD7003 airfoil at a
Reynolds number of Re = 40000 and finally, to access the model's performance
for deforming meshes, we conduct a two-way coupled simulation of a
self-propelled anguilliform swimmer. These simulations confirm the viability of
the new fluid-structure interaction lattice Boltzmann algorithm to simulate
flows of engineering relevance.Comment: submitted to Journal of Computational Physic
Probabilistic models of individual and collective animal behavior
Recent developments in automated tracking allow uninterrupted,
high-resolution recording of animal trajectories, sometimes coupled with the
identification of stereotyped changes of body pose or other behaviors of
interest. Analysis and interpretation of such data represents a challenge: the
timing of animal behaviors may be stochastic and modulated by kinematic
variables, by the interaction with the environment or with the conspecifics
within the animal group, and dependent on internal cognitive or behavioral
state of the individual. Existing models for collective motion typically fail
to incorporate the discrete, stochastic, and internal-state-dependent aspects
of behavior, while models focusing on individual animal behavior typically
ignore the spatial aspects of the problem. Here we propose a probabilistic
modeling framework to address this gap. Each animal can switch stochastically
between different behavioral states, with each state resulting in a possibly
different law of motion through space. Switching rates for behavioral
transitions can depend in a very general way, which we seek to identify from
data, on the effects of the environment as well as the interaction between the
animals. We represent the switching dynamics as a Generalized Linear Model and
show that: (i) forward simulation of multiple interacting animals is possible
using a variant of the Gillespie's Stochastic Simulation Algorithm; (ii)
formulated properly, the maximum likelihood inference of switching rate
functions is tractably solvable by gradient descent; (iii) model selection can
be used to identify factors that modulate behavioral state switching and to
appropriately adjust model complexity to data. To illustrate our framework, we
apply it to two synthetic models of animal motion and to real zebrafish
tracking data.Comment: 26 pages, 11 figure
From whole-brain data to functional circuit models: the zebrafish optomotor response
Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging, behavioral analysis, functional perturbations, and network modeling. Here, we harness these tools to generate a brain-scale circuit model of the optomotor response, an orienting behavior evoked by visual motion. We show that such motion is processed by diverse neural response types distributed across multiple brain regions. To transform sensory input into action, these regions sequentially integrate eye- and direction-specific sensory streams, refine representations via interhemispheric inhibition, and demix locomotor instructions to independently drive turning and forward swimming. While experiments revealed many neural response types throughout the brain, modeling identified the dimensions of functional connectivity most critical for the behavior. We thus reveal how distributed neurons collaborate to generate behavior and illustrate a paradigm for distilling functional circuit models from whole-brain data
Active Brownian Particles. From Individual to Collective Stochastic Dynamics
We review theoretical models of individual motility as well as collective
dynamics and pattern formation of active particles. We focus on simple models
of active dynamics with a particular emphasis on nonlinear and stochastic
dynamics of such self-propelled entities in the framework of statistical
mechanics. Examples of such active units in complex physico-chemical and
biological systems are chemically powered nano-rods, localized patterns in
reaction-diffusion system, motile cells or macroscopic animals. Based on the
description of individual motion of point-like active particles by stochastic
differential equations, we discuss different velocity-dependent friction
functions, the impact of various types of fluctuations and calculate
characteristic observables such as stationary velocity distributions or
diffusion coefficients. Finally, we consider not only the free and confined
individual active dynamics but also different types of interaction between
active particles. The resulting collective dynamical behavior of large
assemblies and aggregates of active units is discussed and an overview over
some recent results on spatiotemporal pattern formation in such systems is
given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte
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