Foams Numerical Tools for Structure and Dynamics _______________________________ Overview Foams may be characterized in two regimes -- static and dynamic. The instantaneous structure of the foam is described by quantities such as the number of nearest neighbors of the bubbles, the positions of the bubbles etc. These quantities may be used to extract stress fields that are important to the stability of the foam. The variation of the instantaneous characterizations may be developed to study the dynamic attributes of foams, such as T1 events etc. We present some of the basic tools to extract and study these properties from experimental images of foam flows. The code listed is written in Matlab (tested on version 7), and is easily implimented on a variety of systems such as colloidal suspensions and emulsions etc. with minimal modifications. It is designed to work for 2D image sequences of the data. Preliminaries    Raw data, Filteration and image processing: Reduction to cell centers, edges and vertices.    A time series of images form the basic data provided from experiments. Before further analysis it is important to process these images to minimize the influence of pixel noise etc. A variety of techniques, are available to do this, from real space filters to fourier space filters. The choice of technique depends very much on the quality of data one has, but in the end one in interested in building a binary image (or cubical complex) that is a good representation of the structure. The binary image distinguishes the bubbles from its walls. Techniques from computational geometry allow one to develop better representations of the state of the foam in terms of the vertices and edges of the cell/bubble walls.   Static properties   Size Distributions, Nearest neighbors, Next-Nearest Neighbors, Stress tensors.    The vertices and edges comprising the cellular structure of the foam are sufficient descriptions to identify nearest neighbors and next nearest neighbors in the structure. The deviatoric stress that relates to the surface tension of the cell walls may also be extracted as a measure of stability. Dynamic properties   Particle Tracking, Velocity profiles, T1 events.   The variation of the static characterizations with time may be used to extract significant dynamical features of foam flows. Such features may include measuring velocities of the individual bubbles, or detecting T1 events. Characterizing the local topological reconfiguration between cells forms the basis for flow in such granular systems. Download all files: foam_code.tar.gz Contact Please send me an email for bug reports, clarifications, usage etc. Any useful modifications, suggestions or additions to the programs would be welcome and appreciated, and may also be included on this website. Thank you.   Kapil Krishan   E-mail: kkrishan@uci.edu   Michael Dennin   E-mail: mdennin@uci.edu   4129 Frederick Reines Hall   Department of Physics and Astronomy   University of California, Irvine   Irvine, CA - 92697 Links to groups working on foams.   Rheology and a broad set of theoretical and experimental investigations in foams - Trinity College, Dublin   Foams stability and stress fields - Francois Graner, University of Grenoble   Modelling and some experiments, surface minimization with surface evolver - Simon Cox, University of Wales   Rheology, and experimental stress measurements - Michael Dennin, UC Irvine   Fracture in Foams, Drainage - Sascha Hilgenfeldt, Northwestern University   Foam Drainage - Eric Weeks, Emory University   Foam Drainage - Stephan Koehler, Emory University    This work has been funded with support from Department of Energy grant DE-FG02-03ER46071.