Large-scale grid-enabled lattice-Boltzmann simulations of complex fluid flow in porous media and under shear

Well designed lattice-Boltzmann codes exploit the essentially embarrassingly parallel features of the algorithm and so can be run with considerable efficiency on modern supercomputers. Such scalable codes permit us to simulate the behaviour of increasingly large quantities of complex condensed matter systems. In the present paper, we present some preliminary results on the large scale three-dimensional lattice-Boltzmann simulation of binary immiscible fluid flows through a porous medium derived from digitised x-ray microtomographic data of Bentheimer sandstone, and from the study of the same fluids under shear. Simulations on such scales can benefit considerably from the use of computational steering and we describe our implementation of steering within the lattice-Boltzmann code, called LB3D, making use of the RealityGrid steering library. Our large scale simulations benefit from the new concept of capability computing, designed to prioritise the execution of big jobs on major supercomputing resources. The advent of persistent computational grids promises to provide an optimal environment in which to deploy these mesoscale simulation methods, which can exploit the distributed nature of compute, visualisation and storage resources to reach scientific results rapidly; we discuss our work on the grid-enablement of lattice-Boltzmann methods in this context.Comment: 17 pages, 6 figures, accepted for publication in Phil.Trans.R.Soc.Lond.

Large-scale lattice Boltzmann simulations of complex fluids: advances through the advent of computational grids

During the last two years the RealityGrid project has allowed us to be one of the few scientific groups involved in the development of computational grids. Since smoothly working production grids are not yet available, we have been able to substantially influence the direction of software development and grid deployment within the project. In this paper we review our results from large scale three-dimensional lattice Boltzmann simulations performed over the last two years. We describe how the proactive use of computational steering and advanced job migration and visualization techniques enabled us to do our scientific work more efficiently. The projects reported on in this paper are studies of complex fluid flows under shear or in porous media, as well as large-scale parameter searches, and studies of the self-organisation of liquid cubic mesophases. Movies are available at http://www.ica1.uni-stuttgart.de/~jens/pub/05/05-PhilTransReview.htmlComment: 18 pages, 9 figures, 4 movies available, accepted for publication in Phil. Trans. R. Soc. London Series

Real-Time Maps of Fluid Flow Fields in Porous Biomaterials

Mechanical forces such as fluid shear have been shown to enhance cell growth and differentiation, but knowledge of their mechanistic effect on cells is limited because the local flow patterns and associated metrics are not precisely known. Here we present real-time, noninvasive measures of local hydrodynamics in 3D biomaterials based on nuclear magnetic resonance. Microflow maps were further used to derive pressure, shear and fluid permeability fields. Finally, remodeling of collagen gels in response to precise fluid flow parameters was correlated with structural changes. It is anticipated that accurate flow maps within 3D matrices will be a critical step towards understanding cell behavior in response to controlled flow dynamics.Comment: 23 pages, 4 figure

A probabilistic algorithm approximating solutions of a singular PDE of porous media type

The object of this paper is a one-dimensional generalized porous media equation (PDE) with possibly discontinuous coefficient $\beta$, which is well-posed as an evolution problem in $L^1(\mathbb{R})$. In some recent papers of Blanchard et alia and Barbu et alia, the solution was represented by the solution of a non-linear stochastic differential equation in law if the initial condition is a bounded integrable function. We first extend this result, at least when $\beta$ is continuous and the initial condition is only integrable with some supplementary technical assumption. The main purpose of the article consists in introducing and implementing a stochastic particle algorithm to approach the solution to (PDE) which also fits in the case when $\beta$ is possibly irregular, to predict some long-time behavior of the solution and in comparing with some recent numerical deterministic techniques

Validation of the granular temperature prediction of the kinetic theory of granular flow by particle image velocimetry and discrete particle model

In order to give a detailed description of the hydrodynamics in large industrial scale fluidized beds, continuum models are required. Continuum models often use the kinetic theory of granular flow (KTGF) to provide closure equations for the internal momentum transport in the particulate phase. In this work the outcome of the continuum model is compared with both an experimental technique and detailed simulations, i.e. particle image velocimetry (PIV) and the discrete particle model (DPM).\ud PIV is used for the measurement of an instantaneous velocity field of the flow in the front plane of a fluid bed. The classical PIV analysis is extended to enable the measurement of the local velocity fluctuations in the interrogation area, i.e. the granular temperature. In the DPM, each particle is tracked individually. In this model detailed collision models can be incorporated, rendering the DPM a valuable research tool to validate the underlying assumptions in the KTGF concerning the particle-particle interactions and the particle velocity distribution functions.\ud The aforementioned experimental and numerical techniques are used to measure the granular temperature distribution around a single bubble rising in a gas-fluidized bed. It was found that the results of PIV and the DPM are very similar. Although the initial bubble shape and size are well predicted by the continuum model, it fails once the bubble has detached from the bottom plate. Further research in the area of KTGF closures is needed to improve the predictions of the TFM

Steering in computational science: mesoscale modelling and simulation

This paper outlines the benefits of computational steering for high performance computing applications. Lattice-Boltzmann mesoscale fluid simulations of binary and ternary amphiphilic fluids in two and three dimensions are used to illustrate the substantial improvements which computational steering offers in terms of resource efficiency and time to discover new physics. We discuss details of our current steering implementations and describe their future outlook with the advent of computational grids.Comment: 40 pages, 11 figures. Accepted for publication in Contemporary Physic