5,654 research outputs found
Derivation of the Lattice Boltzmann Model for Relativistic Hydrodynamics
A detailed derivation of the Lattice Boltzmann (LB) scheme for relativistic
fluids recently proposed in Ref. [1], is presented. The method is numerically
validated and applied to the case of two quite different relativistic fluid
dynamic problems, namely shock-wave propagation in quark-gluon plasmas and the
impact of a supernova blast-wave on massive interstellar clouds. Close to
second order convergence with the grid resolution, as well as linear dependence
of computational time on the number of grid points and time-steps, are
reported
Cholesterol modulates acetylcholine receptor diffusion by tuning confinement sojourns and nanocluster stability
Translational motion of neurotransmitter receptors is key for determining receptor number at the synapse and hence, synaptic efficacy. We combine live-cell STORM superresolution microscopy of nicotinic acetylcholine receptor (nAChR) with single-particle tracking, mean-squared displacement (MSD), turning angle, ergodicity, and clustering analyses to characterize the lateral motion of individual molecules and their collective behaviour. nAChR diffusion is highly heterogeneous: subdiffusive, Brownian and, less frequently, superdiffusive. At the single-track level, free walks are transiently interrupted by ms-long confinement sojourns occurring in nanodomains of ~36 nm radius. Cholesterol modulates the time and the area spent in confinement. Turning angle analysis reveals anticorrelated steps with time-lag dependence, in good agreement with the permeable fence model. At the ensemble level, nanocluster assembly occurs in second-long bursts separated by periods of cluster disassembly. Thus, millisecond-long confinement sojourns and second-long reversible nanoclustering with similar cholesterol sensitivities affect all trajectories; the proportion of the two regimes determines the resulting macroscopic motional mode and breadth of heterogeneity in the ensemble population.Fil: Mosqueira, Alejo. Pontificia Universidad Católica Argentina "Santa MarÃa de los Buenos Aires". Instituto de Investigaciones Biomédicas. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas; ArgentinaFil: Camino, Pablo A.. Pontificia Universidad Católica Argentina "Santa MarÃa de los Buenos Aires". Instituto de Investigaciones Biomédicas. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas; ArgentinaFil: Barrantes, Francisco Jose. Pontificia Universidad Católica Argentina "Santa MarÃa de los Buenos Aires". Instituto de Investigaciones Biomédicas. Consejo Nacional de Investigaciones CientÃficas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Biomédicas; Argentin
The XDEM Multi-physics and Multi-scale Simulation Technology: Review on DEM-CFD Coupling, Methodology and Engineering Applications
The XDEM multi-physics and multi-scale simulation platform roots in the Ex-
tended Discrete Element Method (XDEM) and is being developed at the In- stitute
of Computational Engineering at the University of Luxembourg. The platform is
an advanced multi- physics simulation technology that combines flexibility and
versatility to establish the next generation of multi-physics and multi-scale
simulation tools. For this purpose the simulation framework relies on coupling
various predictive tools based on both an Eulerian and Lagrangian approach.
Eulerian approaches represent the wide field of continuum models while the
Lagrange approach is perfectly suited to characterise discrete phases. Thus,
continuum models include classical simulation tools such as Computa- tional
Fluid Dynamics (CFD) or Finite Element Analysis (FEA) while an ex- tended
configuration of the classical Discrete Element Method (DEM) addresses the
discrete e.g. particulate phase. Apart from predicting the trajectories of
individual particles, XDEM extends the application to estimating the thermo-
dynamic state of each particle by advanced and optimised algorithms. The
thermodynamic state may include temperature and species distributions due to
chemical reaction and external heat sources. Hence, coupling these extended
features with either CFD or FEA opens up a wide range of applications as
diverse as pharmaceutical industry e.g. drug production, agriculture food and
processing industry, mining, construction and agricultural machinery, metals
manufacturing, energy production and systems biology
Quantum fluids of light
This article reviews recent theoretical and experimental advances in the
fundamental understanding and active control of quantum fluids of light in
nonlinear optical systems. In presence of effective photon-photon interactions
induced by the optical nonlinearity of the medium, a many-photon system can
behave collectively as a quantum fluid with a number of novel features stemming
from its intrinsically non-equilibrium nature. We present a rich variety of
photon hydrodynamical effects that have been recently observed, from the
superfluid flow around a defect at low speeds, to the appearance of a
Mach-Cherenkov cone in a supersonic flow, to the hydrodynamic formation of
topological excitations such as quantized vortices and dark solitons at the
surface of large impenetrable obstacles. While our review is mostly focused on
a class of semiconductor systems that have been extensively studied in recent
years (namely planar semiconductor microcavities in the strong light-matter
coupling regime having cavity polaritons as elementary excitations), the very
concept of quantum fluids of light applies to a broad spectrum of systems,
ranging from bulk nonlinear crystals, to atomic clouds embedded in optical
fibers and cavities, to photonic crystal cavities, to superconducting quantum
circuits based on Josephson junctions. The conclusive part of our article is
devoted to a review of the exciting perspectives to achieve strongly correlated
photon gases. In particular, we present different mechanisms to obtain
efficient photon blockade, we discuss the novel quantum phases that are
expected to appear in arrays of strongly nonlinear cavities, and we point out
the rich phenomenology offered by the implementation of artificial gauge fields
for photons.Comment: Accepted for publication on Rev. Mod. Phys. (in press, 2012
Self-propelled droplet driven by Marangoni flow and its applications
We developed a new class of self-propelled droplet, which is made of water/ethanol dispersed in squalane/monoolein. During the propulsion, a spontaneous phase separation of the droplet occurs due to the release of ethanol and the uptake of monoolein. This phase separation can lead to the formation of a Janus droplet consisting of a water-rich phase and an ethanol-rich phase. The droplet moves as a pusher, which is determined by µPIV, before the phase separation and as a neutral squirmer after it. The time before phase separation can be quantified by a model. Additionally the quantitative analysis of the driving mechanisms before and after the phase separation are presented. Depending on salt concentration, added DNA or RNA can be controlled to accumulate either in the water-rich or in the ethanol-rich phase as a 'cargo'. This 'cargo' can be selectively delivered to a target controlled by hydrodynamic interaction and wettability. The same water/ethanol droplet in an ethanol-saturated squalane shows chemotaxic attraction. In this system, the droplet uptakes ethanol from squalane and droplets are attracted to each other supposably driven by this ethanol gradient, which is created by themselves. Large numbers of droplets can form patterns with different shapes, which is controlled by number density and vertical confinement.Wir haben eine neue Klasse von selbst-angetriebenen Tropfen entwickelt, die aus Wasser / Ethanol bestehen und in Squalan / Monoolein dispergiert sind. Während der Bewegung kommt es zu einer spontanen Phasentrennung des Tropfens aufgrund der Abgabe von Ethanol und der Aufnahme von Monoolein. Diese Phasentrennung kann zur Ausbildung eines Janus-Tropfens führen, der aus einer wasserreichen Phase und einer ethanolreichen Phase besteht. Der Tropfen bewegt sich vor der Phasentrennung als 'Pusher', der durch µPIV bestimmt wird, und danach als neutraler 'Squirmer'. Die Zeit vor der Phasentrennung kann durch ein Modell quantifiziert. Zusätzlich wird die quantitative Analyse der Antriebsmechanismen vor und nach der Phasentrennung vorgestellt. Abhängig von der Salzkonzentration kann die zugesetzte DNA oder RNA so gesteuert werden, dass sie sich entweder in der wasserreichen oder in der ethanolreichen Phase als "Ladung" ansammelt. Diese 'Ladung' kann selektiv an ein Ziel geliefert werden und durch hydrodynamische Wechselwirkung und Benetzbarkeit gesteuert werden. Der gleiche Wasser/Ethanol Tropfen in ethanolgesättigten Squalan zeigt eine chemotaktische Anziehungskraft. In diesem System nehmen die Tropfen Ethanol aus Squalan auf und die Tropfen werden vermutlich durch diesen Ethanolgradienten, der von ihnen selbst erzeugt wird, voneinander angezogen. Die Ansammlung vieler Tropfen können Muster bilden. Das Muster wird von der Tropfendichte und der vertikalen Ausdehnung kontrolliert
The 1999 Center for Simulation of Dynamic Response in Materials Annual Technical Report
Introduction:
This annual report describes research accomplishments for FY 99 of the Center
for Simulation of Dynamic Response of Materials. The Center is constructing a
virtual shock physics facility in which the full three dimensional response of a
variety of target materials can be computed for a wide range of compressive, ten-
sional, and shear loadings, including those produced by detonation of energetic
materials. The goals are to facilitate computation of a variety of experiments
in which strong shock and detonation waves are made to impinge on targets
consisting of various combinations of materials, compute the subsequent dy-
namic response of the target materials, and validate these computations against
experimental data
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