Simulating Three-Dimensional Hydrodynamics on a Cellular-Automata Machine

We demonstrate how three-dimensional fluid flow simulations can be carried out on the Cellular Automata Machine 8 (CAM-8), a special-purpose computer for cellular-automata computations. The principal algorithmic innovation is the use of a lattice-gas model with a 16-bit collision operator that is specially adapted to the machine architecture. It is shown how the collision rules can be optimized to obtain a low viscosity of the fluid. Predictions of the viscosity based on a Boltzmann approximation agree well with measurements of the viscosity made on CAM-8. Several test simulations of flows in simple geometries -- channels, pipes, and a cubic array of spheres -- are carried out. Measurements of average flux in these geometries compare well with theoretical predictions.Comment: 19 pages, REVTeX and epsf macros require

Spreading of a density front in the K\"untz-Lavall\'ee model of porous media

We analyze spreading of a density front in the K\"untz-Lavall\'ee model of porous media. In contrast to previous studies, where unusual properties of the front were attributed to anomalous diffusion, we find that the front evolution is controlled by normal diffusion and hydrodynamic flow, the latter being responsible for apparent enhancement of the front propagation speed. Our finding suggests that results of several recent experiments on porous media, where anomalous diffusion was reported based on the density front propagation analysis, should be reconsidered to verify the role of a fluid flow

Complexity, parallel computation and statistical physics

The intuition that a long history is required for the emergence of complexity in natural systems is formalized using the notion of depth. The depth of a system is defined in terms of the number of parallel computational steps needed to simulate it. Depth provides an objective, irreducible measure of history applicable to systems of the kind studied in statistical physics. It is argued that physical complexity cannot occur in the absence of substantial depth and that depth is a useful proxy for physical complexity. The ideas are illustrated for a variety of systems in statistical physics.Comment: 21 pages, 7 figure

Probabilistic approach for analysis of strength of ceramics with different porous structure based on movable cellular automaton modeling

Movable cellular automaton method which is a computational method of particle mechanics is applied to simulating uniaxial compression of 3D porous ceramic specimens. Pores were considered explicitly by removing automata selected randomly from the original fcc packing. Distribution of pores in space, their size and the total fraction were varied. For each values of porosity there were generated several represented specimens with individual pore position in space. The resulting values of elastic modulus and strength of the specimens were scattered and well described by the Weibull distribution. We showed that to reveal dependence of the elastic and strength properties on porosity it is much better to consider not average of the values for the specimens of the same porosity, but the mathematical expectation of the corresponding Weibull distribution. It is shown that relation between mechanical properties of the material and its porosity depends significantly on pore structure. Namely, percolation transition from closed porosity to interconnected pores strongly manifests itself on strength dependence on porosity. Thus, the curve of strength versus porosity fits different equations for different kind of pore structure. Composite ceramics which pores are filled by plastic filler shows the similar behavior

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