OOF is designed to help materials scientists calculate macroscopic properties from images of real or simulated microstructures. It reads an image, assigns material properties to features in the image, and conducts virtual experiments to determine the macroscopic properties of the microstructure..

OOF will run on any computer running a variant of the Unix operating system, including Mac OS X and Linux.

Here are some key features of "OOF":

· New Fields and Fluxes can be added with only a few lines of Python code. New material properties can be added with a few lines of Python code, or, if speed is an issue, in C++.
· Materials are built from a collection of Properties. Any combination of Properties is allowed, with reasonable constraints on completeness and unambiguity.
· OOF2 contains a powerful set of finite elements: 3 noded triangles, 4 node quadrilaterals, 6 noded subparametric triangles, and 8 noded subparametric quadrilaterals. Adding new element types in C++ is easy.
· OOF generates and refines triangular, quadrilateral, and mixed meshes from image data. Element order is specified independently from element geometry.
· OOF incorporates nonlinear solvers. (But not many non-linear material properties are yet present.)
· OOF can refine meshes adaptively using a-posteriori error estimators.
· OOF is threaded, meaning that it can perform multiple calculations simultaneously.
· OOF is completely scriptable in Python, and can also be run interactively from a graphical user interface.
· OOF can export mesh geometry directly into abaqus input files.
· OOF can read EBSD orientation map data files.

Requirements:

· Python 2.4 or later
· Image Magick++
· gtk+
· pygtk 2.6 or later
· BLAS

What's New in This Release: [ read full changelog ]

· Fixed the image save functionality in displaying orientation map images.