Difference between revisions of "Tzold"

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[[Image:muCT_ani.gif |thumb|300px|right|Picture 2: Two dimensional crosssections of the discretized model.The sidelength of the crosssection is L  and the resolution a. The porespace is black and the grains are gray. A the highest resolution  narrow channel are solved by more than 20 nodes. ]]
 
[[Image:muCT_ani.gif |thumb|300px|right|Picture 2: Two dimensional crosssections of the discretized model.The sidelength of the crosssection is L  and the resolution a. The porespace is black and the grains are gray. A the highest resolution  narrow channel are solved by more than 20 nodes. ]]
  
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Revision as of 09:57, 2 March 2011

Placeholder.jpg
Tzold
PhD student
Office:202
Phone:+49 711 685-67652
Fax:+49 711 685-63658
Email:Thomas.Zauner _at_ icp.uni-stuttgart.de
Address:Tzold
Institute for Computational Physics
Universität Stuttgart
Allmandring 3
70569 Stuttgart
Germany


Research Overview

Sandstone is a very common natural porous medium. ©wikipedia

The general field of my research is the computational investigations of natural porous media. A typical example of such a natural porous medium is sandstone. It consists of very small consolidated grains that form a solid backbone but, due to the space between individual grains, is permeable for many fluids. Insight into physical transport phenomena of natural porous media, such as flow rates, trapping behavior and prediction of effective transport coefficients, has always been of great practical interest for the oil and gas industry and has currently drawn public attention in the context of CO2 sequestration. Porous materials are also used for many industrial applications, for example in filtration processes, as catalyst in chemical reactions or building materials with specially physical properties.


The scientific problems that I address in my work are:

  • Developing algorithms that can generate realistic and macroscopic computer models for granular porous media. These models will be made of many hundred millions of individual grains whose positions, orientations and sizes must fulfill certain correlations and restrictions. The associated large computational demand requires highly efficient parallelized computer algorithms.
  • Identifying and evaluating numerical methods that allow accurate and predictive calculations of physical properties of porous media. These calculations typically require numerically solving partial differential equations within a chosen discretization scheme and at a specific resolution or order of accuracy.


Realistic computer models for granular porous media

In the reconstruction procedure we use a dense packing of spheres is created. The packing must fulfill given restrictions such as density, overlap, size distribution and others. The spheres are later substituted by more complex geometrical objects determined by the shapes of the grains used in the specific model. One option is to use polyhedrons as grain shapes. The resulting model then is a continuum model in the sense that the geometry is defined by a points in the continuum and polyhedrons with analytical defined shapes, sizes and orientations. An example of such a model for Fountainebleau sandstone is shown in image 1. Such a continuous computer model can then be discretized at any desired resolution, see image 2, for further analysis and computer simulations.

Picture 1: Three dimensional rendering of a model for Fontainebleau sandstone. The model contains over 1.2 million quartz grains. Each grain is modeled as a polyhedron. A crosssection is shown in orange.
Picture 2: Two dimensional crosssections of the discretized model.The sidelength of the crosssection is L and the resolution a. The porespace is black and the grains are gray. A the highest resolution narrow channel are solved by more than 20 nodes.




Flow Simulations

A porous mediums permeability is an example of a physical transport parameter. It describes the mediums ability to transmit fluid flow through it. Using Darcy's law the permeability of a porous medium can be calculated from the velocity and corresponding pressure field on the porescale. These fields are solutions of hydrodynamic partial differential equations describing fluid flow on the porescale. Many different numerical methods that solve different hydrodynamic equations can be used to obtain the velocity and pressure field. Possibilities are Navier-Stokes simulations and Lattice-Boltzmann simulations. Our Lattice-Boltzmann implementation, for example, numerically solves the Boltzmann equation using a transient explicit finite-difference scheme. The simulation is ran until a stationary solution has been reached. From this stationary solution the hydrodynamic fields can be calculated.

Very small subvolume (128³ voxel) of a sandstone. The porespace-matrix interface is shown as a mesh. The velocity magnitude, as calculated by a Lattice-Boltzmann simulation, is shown within the porespace. Areas of slow flow are blue, fast flow is shown in red. An empty porespace indicates areas where the fluid is at rest. It can be seen that only a small portion of the porespace contributes to the mass transport. Media:poremovie.avi


Publications

[1] A. Narvaez, T. Zauner, F. Raischel, R. Hilfer, J. Harting, “Quantitative analysis of numerical estimates for the permeability of porous media from lattice-Boltzmann simulations”, Journal of Statistical Mechanics, P11026, 2010, Preprint


[2] S. Grottel, G. Reina, T. Zauner, R. Hilfer, T. Ertl, "Particle-based Rendering for Porous Media", SIGRAD, 2010, Preprint

[3] J. Harting, T. Zauner, R. Weeber, and R. Hilfer Numerical modeling of fluid flow in porous media and in driven colloidal suspensions in High Performance Computing in Science and Engineering '08, edited by W. Nagel, D. Kröner, M. Resch, Springer ,2008. Preprint