The best and most current information about the OOF software, including current downloads, can be found at the main OOF site.
The general workflow of the OOF software begins with a 2D or 3D image. OOF provides tools for maniupating the image to highlight scientifically important features, and to then construct a finite-element mesh on this image that matches these features. Users can then specify the bulk properties of the various regions of the microstructure -- many simple properties are packaged with the software, and there is also an application program interface for users to provide custom constitutive rules for their materials models. Finally, users can perform a "virtual experiment" with the software to characterize the response of the microstructure as a whole to various boundary conditions.
OOF currently has both first and second order time dependence, and a variety of properties whose structure is that of a divergence equation -- these include heat or chemical flux, elasticity, and several important couplings, including thermal expansion and piezoelectricity.
The principal OOF activity now is the addition of crystal plastic constitutive rules to the code, with the goal of being able to predict the microstructure-dependent mechanical response of complex materials to large loads. Because of the history-dependence, plasticity differs in character from materials models previously considered in the OOF software. We face a number of architectural and performance challenges in bringing this capability to a useable state, while preserving the wide range of applicability and generalizability that is the primary goal of the OOF software.
With the assistance of an expert from the field of computational mecahnics, post-doctoral researcher Shahriyar Keshavarz, the architectural challenge is now essentially solved in a prototype code.
The difficulties arising from the history-dependence of the plastic behavior turned out to be only part of the story. A previously unrecognized difficulty arose related to the incorporation of large-strain elasticity. From the point of view of mathematics or physics, large-strain elasticity appears to effectively amount to a different constitutive rule, and with an understanding of the geometry, it seems that it is at least conceptually straightforward to construct an equation which can be solved in either the reference, undeformed configuration, or in the "lab space," depending on one's choice of stress measure and willingness to undertake successive applications of the chain rule of differentiation. One makes a selection, applies it consistently, and achieves whatever level of generality one wishes.
In the computational mechanics community, there is a time-honored way of approaching this problem which involves a decomposition into constitutive and geometric parts, and the construction of an intermediate space in which plastic strain is present but elastic deformation is not. This space has high importance for crystal plasticity, because it is a space in which the lattice remains invariant, and in particular where the crystallographic planes along which the plasticity acts retain their original orientations. Understanding the evolution rules for the system as acting in these two spaces connects usefully to the different physical mechanisms taking place. It is, on the one hand, a powerful tool in understanding the mechanisms, and on the other hand, essential to communicating with the computational mechanics community against whom we want to benchmark, and from whom we expect to obtain candidate constitutive rules.
Respecting this decomposition means one cannot simply write a more general history-dependent PDE solver to properly address this problem.
We now have a software architectural demonstration code which maintains the desired generality of the OOF code, retains the ability to operate on unstructured meshes derived from image data, and incorporates the spatial decomposition of the problem while allowing for "pluggable" plastic constitive rules, to facilitate structure-property explorations. Our next task is to incorporate this into the main OOF code itself.
In addition, we have a renewed focus on interoperability, and have near-term plans to make it easier to incorporate OOF capabilities into existing or currently-planned high-throughput or scale-crossing workflows, either by ingesting property information from the emerging suite of repositories, setting up an MDCS instance to allow the public exchange of OOF property and materials data, or incorporting OOF into scale-crossing design-optimizing workflows.
To this end, we are investigating the practicality of ingesting or producing microstructural data in the Dream3D format, or related HDF5-based formats under development in Europe, and are participating in workshops where tools and workflows are featured, starting with the PRISMs and ICE workflows, from the University of Michigan and the US Air Force, respectively.