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

A modified lattice Bhatnagar-Gross-Krook model for convection heat transfer in porous media

The lattice Bhatnagar-Gross-Krook (LBGK) model has become the most popular one in the lattice Boltzmann method for simulating the convection heat transfer in porous media. However, the LBGK model generally suffers from numerical instability at low fluid viscosities and effective thermal diffusivities. In this paper, a modified LBGK model is developed for incompressible thermal flows in porous media at the representative elementary volume scale, in which the shear rate and temperature gradient are incorporated into the equilibrium distribution functions. With two additional parameters, the relaxation times in the collision process can be fixed at a proper value invariable to the viscosity and the effective thermal diffusivity. In addition, by constructing a modified equilibrium distribution function and a source term in the evolution equation of temperature field, the present model can recover the macroscopic equations correctly through the Chapman-Enskog analysis, which is another key point different from previous LBGK models. Several benchmark problems are simulated to validate the present model with the proposed local computing scheme for the shear rate and temperature gradient, and the numerical results agree well with analytical solutions and/or those well-documented data in previous studies. It is also shown that the present model and the computational schemes for the gradient operators have a second-order accuracy in space, and better numerical stability of the present modified LBGK model than previous LBGK models is demonstrated.Comment: 38pages,50figure

Computer Simulation of Particle Suspensions

Particle suspensions are ubiquitous in our daily life, but are not well understood due to their complexity. During the last twenty years, various simulation methods have been developed in order to model these systems. Due to varying properties of the solved particles and the solvents, one has to choose the simulation method properly in order to use the available compute resources most effectively with resolving the system as well as needed. Various techniques for the simulation of particle suspensions have been implemented at the Institute for Computational Physics allowing us to study the properties of clay-like systems, where Brownian motion is important, more macroscopic particles like glass spheres or fibers solved in liquids, or even the pneumatic transport of powders in pipes. In this paper we will present the various methods we applied and developed and discuss their individual advantages.Comment: 31 pages, 11 figures, to appear in Lecture Notes in Applied and Computational Mechanics, Springer (2006

Lattice Kinetic Monte Carlo Simulations of Platelet Aggregation and Deposition

Platelet aggregation is an essential process in forming a stable clot to prevent blood loss. The response of platelets to a complex signal of pro-clotting agonists determines the stability and size of the resulting clot. An underdeveloped clot represents a bleeding risk, while an overdeveloped clot can cause vessel occlusion, which can lead to heart attack or stroke. A multiscale model was developed to study the integration of platelet signaling within the complex phenomena driven by flow. The model is built upon a lattice kinetic Monte Carlo algorithm (LKMC) to track platelet motion and binding. First, a new method for including flow-driven particle motion in LKMC was derived from a timescale analysis of particle motion. Simple methods for simulating flow-driven motion were found to exhibit concentration dependent velocities violating the assumptions in the model. The nature of the error was analyzed mathematically and resolved by considering the chain length distribution on the lattice. The accuracy of the method was found to scale linearly with the lattice spacing. Second, the LKMC method was extended to study particle aggregation in complex flows. The LKMC results for simple flows were compared directly to a continuum population balance equation (PBE) approach. A contact time model was introduced to capture nonideal collisions in the LKMC model and a connection to the continuum collision efficiency was derived. The particle size distribution for a baffled geometry with regions of standing vortices and squeezing flows was determined using the LKMC method for varying baffle heights. Finally, the LKMC method was incorporated within a multiscale model to simulate platelet aggregation including platelet signaling (neural network model), blood flow (lattice Boltzmann method), and the release of soluble platelet agonists (finite element method). The neural network model for platelet signaling was trained on patient-specific, experimental measurements of intracellular calcium enabling patient-specific predictions of platelet function in flow. The model accurately predicted the order of potency for three antiplatelet therapies, donor-specific aggregate size, and donor-specific response to antiplatelet therapy as compared to microfluidic experiments of platelet aggregation

Three-Dimensional Lattice Boltzmann Simulation of Two-Phase Flow Containing a Deformable Body with a Viscoelastic Membrane

First published in Communications in Commun. Comput. Phys. in No. 5, 9 (2011), published by Global Science PressThe lattice Boltzmann method (LBM) with an elastic model is applied to the simulation of two-phase flows containing a deformable body with a viscoelastic membrane. The numerical method is based on the LBM for incompressible two-phase fluid flows with the same density. The body has an internal fluid covered by a viscoelastic membrane of a finite thickness. An elastic model is introduced to the LBM in order to determine the elastic forces acting on the viscoelastic membrane of the body. In the present method, we take account of changes in surface area of the membrane and in total volume of the body as well as shear deformation of the membrane. By using this method, we calculate two problems, the behavior of an initially spherical body under shear flow and the motion of a body with initially spherical or biconcave discoidal shape in square pipe flow. Calculated deformations of the body (the Taylor shape parameter) for various shear rates are in good agreement with other numerical results. Moreover, tank-treading motion, which is a characteristic motion of viscoelastic bodies in shear flows, is simulated by the present method.ArticleCommunications in Computational Physics. 9(5):1397-1413 (2011)journal articl

Stokesian Dynamics

Particles suspended or dispersed in a fluid medium occur in a wide variety of natural and man-made settings, e.g. slurries, composite materials, ceramics, colloids, polymers, proteins, etc. The central theoretical and practical problem is to understand and predict the macroscopic equilibrium and transport properties of these multiphase materials from their microstructural mechanics. The macroscopic properties might be the sedimentation or aggregation rate, self-diffusion coefficient, thermal conductivity, or rheology of a suspension of particles. The microstructural mechanics entails the Brownian, interparticle, external, and hydrodynamic forces acting on the particles, as well as their spatial and temporal distribution, which is commonly referred to as the microstructure. If the distribution of particles were given, as well as the location and motion of any boundaries and the physical properties of the particles and suspending fluid, one would simply have to solve (in principle, not necessarily in practice) a well-posed boundary-value problem to determine the behavior of the material. Averaging this solution over a large volume or over many different configurations, the macroscopic or averaged properties could be determined. The two key steps in this approach, the solution of the many-body problem and the determination of the microstructure, are formidable but essential tasks for understanding suspension behavior. This article discusses a new, molecular-dynamics-like approach, which we have named Stokesian dynamics, for dynamically simulating the behavior of many particles suspended or dispersed in a fluid medium. Particles in suspension may interact through both hydrodynamic and nonhydrodynamic forces, where the latter may be any type of Brownian, colloidal, interparticle, or external force. The simulation method is capable of predicting both static (i.e. configuration-specific) and dynamic microstructural properties, as well as macroscopic properties in either dilute or concentrated systems. Applications of Stokesian dynamics are widespread; problems of sedimentation, flocculation, diffusion, polymer rheology, and transport in porous media all fall within its domain. Stokesian dynamics is designed to provide the same theoretical and computational basis for multiphase, dispersed systems as does molecular dynamics for statistical theories of matter. This review focuses on the simulation method, not on the areas in which Stokesian dynamics can be used. For a discussion of some of these many different areas, the reader is referred to the excellent reviews and proceedings of topical conferences that have appeared (e.g. Batchelor 1976a, Dickinson 1983, Faraday Discussions 1983, 1987, Family & Landau 1984). Before embarking on a description of Stokesian dynamics, we pause here to discuss some of the relevant theoretical literature on suspensions, and dynamic simulation in general, in order to put Stokesian dynamics in perspective

Ein Kumulanten-Lattice-Boltzmann-Methode für LES von Dispersionsmikrosystemen

The production of nano-particles from larger aggregates is an important industrial process, especially for life-science products. In this thesis a micro-machined disperser developed by the DFG Research Group FOR 856 mikroPART is studied numerically by the cumulant lattice Boltzmann method. The aggregates are modeled as tracer particles with mass and drag coefficient. They record the history of the stresses and the relative velocity of the aggregates with respect to the fluid. For the evaluation of the velocities and stresses a compact second-order interpolation scheme is utilized. The tracer particles are implemented in a massively parallel multi-resolution lattice Boltzmann framework. The simulation of the disperser is validated against PIV and flow rate measurements from collaborators in the mikroPART Research Group. The drag coefficients of the aggregates are obtained by detailed simulations of synthetic aggregates in simple shear flow, elongational flow, and rotational flow. An empirical relation between the drag coefficient and the number of primary particles in the aggregate and its fractal dimensions is found and used in the tracer simulation of the disperser. Different measures of load on the aggregates are obtained by the simulation, for example maximal strain, exposure time to a certain strain, and relative velocity of the particles with respect to the surrounding fluid. It is assumed that ceramic aggregates break-up when they suffer a threshold strain rate. The distribution of the maximum strain rate seen by an aggregate can be condensed into a simple exponential cumulative probability distribution. Combined with a given threshold for the particle break-up this condensed model can also be used to determine the probability for aggregate breakage after n passages of the device. It is found that aggregates with realistic geometry (fractal number 1.85) usually have Stokes numbers smaller than one such that the load on these aggregates is dominated by the strain in the surrounding fluid. This is in contrast to spherical particles (fractal number 3) that have Stokes numbers in excess of one such that the load from their relative velocity with respect to the surrounding fluid is not negligible.Die Erzeugung von Nanopartikeln aus größeren Aggregaten ist ein wichtiger industrieller Prozess insbesondere in den Lebenswissenschaften. In dieser Dissertation wird ein von der DFG-Forschergruppe FOR 856 mikroPART entwickelter Dispergierkanal mit Hilfe der Kumulanten-Lattice-Boltzmann-Methode numerisch untersucht. Die Aggregate werden als Partikel mit Masse und Strömungswiderstandsbeiwert modelliert. Sie zeichnen den Verlauf der Spannungen und den der Relativgeschwindigkeit zwischen Partikel und Fluid über die Zeit auf. Die Geschwindigkeiten und Spannungen werden mit Hilfe eines kompakten Interpolationsschemas zweiter Ordnung berechnet. Die Partikelsimulation wird in ein massiv-paralleles Mehrskalen-Lattice-Boltzmann-Framework eingebettet. Zur Validierung wird die Simulation des Dispergierkanals mit PIV- und Flussratenmessungen verglichen, die von Projektpartnern innerhalb der mikroPART-Forschergruppe durchgeführt wurden. Die Strömungswiderstandsbeiwerte der Aggregate werden durch umfangreiche Simulationen synthetischer Aggregate in einfachen Scherströmungen, Dehnströmungen und Rotationsströmungen ermittelt. Es wird ein empirischer Zusammenhang zwischen dem Strömungswiderstandsbeiwert und der Anzahl der Partikel im Aggregat sowie dessen fraktaler Dimension aufgestellt. Dieser wird in der Partikelsimulation des Dispergierkanals verwendet. Die Simulation liefert verschiedene Masse für die Belastung der Aggregate, unter anderem die maximale Dehnung, die Einwirkzeit einer gegebenen Mindestdehnung und die Relativgeschwindigkeit der Partikel zu dem umgebenden Fluid. Es wird angenommen, dass keramische Aggregate brechen, wenn eine bestimmte Schwellendehnungsrate überschritten wird. Die Verteilung der maximalen von einem Aggregat erfahrene Dehnungsrate kann durch eine einfache exponentielle kumulative Wahrscheinlichkeitsverteilung ausgedrückt werden. In Verbindung mit dem Schwellenwert kann dieses reduzierte Modell zur Abschätzung der Wahrscheinlichkeit des Aggregatbruches nach n Durchquerungen des Dispergierkanals verwendet werden. Es wird festgestellt, dass bei realistischen Aggregatsgeometrien (fraktale Dimension 1.85) typischerweise Stokeszahlen kleiner als eins auftreten, so dass der dominierende Lastmechanismus die Dehnung durch das umgebende Fluid ist. Im Gegensatz dazu treten bei kugelförmigen Partikeln (fraktale Dimension 3) Stokeszahlen größer als eins auf. Daher ist die Last aus der Relativgeschwindigkeit zu dem umgebenden Fluid nicht vernachlässigbar

Multiscale Modelling Of Platelet Aggregation

During clotting under flow, platelets bind and activate on collagen and release autocrinic factors such ADP and thromboxane, while tissue factor (TF) on the damaged wall leads to localized thrombin generation. Toward patient-specific simulation of thrombosis, a multiscale approach was developed to account for: platelet signaling (neural network trained by pairwise agonist scanning, PAS-NN), platelet positions (lattice kinetic Monte Carlo, LKMC), wall-generated thrombin and platelet-released ADP/thromboxane convection-diffusion (PDE), and flow over a growing clot (lattice Boltzmann). LKMC included shear-driven platelet aggregate restructuring. The PDEs for thrombin, ADP, and thromboxane were solved by finite element method using cell activation-driven adaptive triangular meshing. At all times, intracellular calcium was known for each platelet by PAS-NN in response to its unique exposure to local collagen, ADP, thromboxane, and thrombin. The model accurately predicted clot morphology and growth with time on collagen/TF surface as compared to microfluidic blood perfusion experiments. The model also predicted the complete occlusion of the blood channel under pressure relief settings. Prior to occlusion, intrathrombus concentrations reached 50 nM thrombin, ~1 μM thromboxane, and ~10 μM ADP, while the wall shear rate on the rough clot peaked at ~1000-2000 sec-1. Additionally, clotting on TF/collagen was accurately simulated for modulators of platelet cyclooxygenase-1, P2Y1, and IP-receptor. The model was then extended to a rectangular channel with symmetric Gaussian obstacles representative of a coronary artery with severe stenosis. The upgraded stenosis model was able to predict platelet deposition dynamics at the post-stenotic segment corresponding to development of artery thrombosis prior to severe myocardial infarction. The presence of stenosis conditions alters the hemodynamics of normal hemostasis, showing a different thrombus growth mechanism. The model was able to recreate the platelet aggregation process under the complex recirculating flow features and make reasonable prediction on the clot morphology with flow separation. The model also detected recirculating transport dynamics for diffusible species in response to vortex features, posing interesting questions on the interplay between biological signaling and prevailing hemodynamics. In future work, the model will be extended to clot growth with a patient cardio-vasculature under pulsatile flow conditions