108 research outputs found
Bridging the computational gap between mesoscopic and continuum modeling of red blood cells for fully resolved blood flow
We present a computational framework for the simulation of blood flow with
fully resolved red blood cells (RBCs) using a modular approach that consists of
a lattice Boltzmann solver for the blood plasma, a novel finite element based
solver for the deformable bodies and an immersed boundary method for the
fluid-solid interaction. For the RBCs, we propose a nodal projective FEM
(npFEM) solver which has theoretical advantages over the more commonly used
mass-spring systems (mesoscopic modeling), such as an unconditional stability,
versatile material expressivity, and one set of parameters to fully describe
the behavior of the body at any mesh resolution. At the same time, the method
is substantially faster than other FEM solvers proposed in this field, and has
an efficiency that is comparable to the one of mesoscopic models. At its core,
the solver uses specially defined potential energies, and builds upon them a
fast iterative procedure based on quasi-Newton techniques. For a known
material, our solver has only one free parameter that demands tuning, related
to the body viscoelasticity. In contrast, state-of-the-art solvers for
deformable bodies have more free parameters, and the calibration of the models
demands special assumptions regarding the mesh topology, which restrict their
generality and mesh independence. We propose as well a modification to the
potential energy proposed by Skalak et al. 1973 for the red blood cell
membrane, which enhances the strain hardening behavior at higher deformations.
Our viscoelastic model for the red blood cell, while simple enough and
applicable to any kind of solver as a post-convergence step, can capture
accurately the characteristic recovery time and tank-treading frequencies. The
framework is validated using experimental data, and it proves to be scalable
for multiple deformable bodies
Spatial Coupling of a Lattice Boltzmann fluid model with a Finite Difference Navier-Stokes solver
In multiscale, multi-physics applications, there is an increasing need for
coupling numerical solvers that are each applied to a different part of the
problem. Here we consider the case of coupling a Lattice Boltzmann fluid model
and a Finite Difference Navier-Stokes solver. The coupling is implemented so
that the entire computational domain can be divided in two regions, with the FD
solver running on one of them and the LB one on the other.
We show how the various physical quantities of the two approaches should be
related to ensure a smooth transition at the interface between the regions. We
demonstrate the feasibility of the method on the Poiseuille flow, where the LB
and FD schemes are used on adjacent sub-domains.
The same idea can be also developed to couple LB models with Finite Volumes,
or Finite Elements calculations.
The motivation for developing such a type of coupling is that, depending on
the geometry of the flow, one technique can be more efficient, less memory
consuming, or physically more appropriate than the other in some regions (e.g.
near the boundaries), whereas the converse is true for other parts of the same
system. We can also imagine that a given system solved, say by FD, can be
augmented in some spatial regions with a new physical process that is better
treated by a LB model. Our approach allows us to only modify the concerned
region without altering the rest of the computation.Comment: 10 pages, 2 figure
Multiscale multiphysics process on a HPC infrastructure ::application to coral growth process
Many natural processes are characteristic multiscale multiphysics problems. Over the years techniques have been developed to study and simulate these processes using a computer. Such simulations are highly resource intensive and their performance is computationally bound on a large scale. High Performance Computing (HPC) plays a handy role in such a scenario. However, deploying a multiscale multiphysics application on a HPC infrastructure requires identifying and further tuning some parameters so as to improve performance and efficiency. This paper explains this procedure for the case study of a nutriment-driven coral growth process
Towards a hybrid parallelization of lattice Boltzmann methods
AbstractOngoing research towards the development of a hybrid parallelization concept for lattice Boltzmann methods is presented. It allows coping with platforms sharing both the properties of shared and distributed architectures. The proposed approach relies on spatial domain decomposition where each domain represents a basic block entity which is solved on a symmetric multi-processing (SMP) system. Emphasis is placed on the software design and the reworking needed to achieve good performance using OpenMP in that context. Those ideas are implemented in the C++ project OpenLB, which is also sketched in this article. The efficiency of the proposed approaches is tested on a 3D benchmark problem and compared with a purely MPI based approach
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