4,252 research outputs found
Recent advances in the simulation of particle-laden flows
A substantial number of algorithms exists for the simulation of moving
particles suspended in fluids. However, finding the best method to address a
particular physical problem is often highly non-trivial and depends on the
properties of the particles and the involved fluid(s) together. In this report
we provide a short overview on a number of existing simulation methods and
provide two state of the art examples in more detail. In both cases, the
particles are described using a Discrete Element Method (DEM). The DEM solver
is usually coupled to a fluid-solver, which can be classified as grid-based or
mesh-free (one example for each is given). Fluid solvers feature different
resolutions relative to the particle size and separation. First, a
multicomponent lattice Boltzmann algorithm (mesh-based and with rather fine
resolution) is presented to study the behavior of particle stabilized fluid
interfaces and second, a Smoothed Particle Hydrodynamics implementation
(mesh-free, meso-scale resolution, similar to the particle size) is introduced
to highlight a new player in the field, which is expected to be particularly
suited for flows including free surfaces.Comment: 16 pages, 4 figure
Inertial Coupling Method for particles in an incompressible fluctuating fluid
We develop an inertial coupling method for modeling the dynamics of
point-like 'blob' particles immersed in an incompressible fluid, generalizing
previous work for compressible fluids. The coupling consistently includes
excess (positive or negative) inertia of the particles relative to the
displaced fluid, and accounts for thermal fluctuations in the fluid momentum
equation. The coupling between the fluid and the blob is based on a no-slip
constraint equating the particle velocity with the local average of the fluid
velocity, and conserves momentum and energy. We demonstrate that the
formulation obeys a fluctuation-dissipation balance, owing to the
non-dissipative nature of the no-slip coupling. We develop a spatio-temporal
discretization that preserves, as best as possible, these properties of the
continuum formulation. In the spatial discretization, the local averaging and
spreading operations are accomplished using compact kernels commonly used in
immersed boundary methods. We find that the special properties of these kernels
make the discrete blob a particle with surprisingly physically-consistent
volume, mass, and hydrodynamic properties. We develop a second-order
semi-implicit temporal integrator that maintains discrete
fluctuation-dissipation balance, and is not limited in stability by viscosity.
Furthermore, the temporal scheme requires only constant-coefficient Poisson and
Helmholtz linear solvers, enabling a very efficient and simple FFT-based
implementation on GPUs. We numerically investigate the performance of the
method on several standard test problems...Comment: Contains a number of corrections and an additional Figure 7 (and
associated discussion) relative to published versio
Brownian dynamics of rigid particles in an incompressible fluctuating fluid by a meshfree method
A meshfree Lagrangian method for the fluctuating hydrodynamic equations
(FHEs) with fluid-structure interactions is presented. Brownian motion of the
particle is investigated by direct numerical simulation of the fluctuating
hydrodynamic equations. In this framework a bidirectional coupling has been
introduced between the fluctuating fluid and the solid object. The force
governing the motion of the solid object is solely due to the surrounding fluid
particles. Since a meshfree formulation is used, the method can be extended to
many real applications involving complex fluid flows. A three-dimensional
implementation is presented. In particular, we observe the short and long-time
behaviour of the velocity autocorrelation function (VACF) of Brownian particles
and compare it with the analytical expression. Moreover, the Stokes-Einstein
relation is reproduced to ensure the correct long-time behaviour of Brownian
dynamics.Comment: 24 pages, 2 figure
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