Material simulation

The properties of materials and components are marked by their microstructure and its defects. For this reason, one endeavours to predict these as best as possible. By studying published phase diagrams, one obtains an initial impression of microstructures as a function of composition. Thermodynamic methods enable one to make predictions about complex multi-component and multi-phase systems. If these methods are extended to kinetic processes, such as nucleation, diffusion and dendrite-arm coarsening, then one obtains an account of the time-dependent phase constituents and compositions. An approach which extends beyond this takes into consideration interfacial effects and enables the microstructural development to be simulated. The overarching objective of all these developments is to predict material properties and the inverse definition of the melt composition and process in the virtual development of materials.

Thermodynamic methods

Thermodynamic databases are based on physical models which permit interpolations into “unknown regions”. According to our understanding, a thermodynamic database is a set of polynomials which describe the Gibb’s energy of individual phases of systems as functions of temperature, (the pressure) and the composition. Thermodynamic methods permit phase fractions and phase changes to be determined, precipitation temperatures to be predicted, solidification behaviour to be estimated and to specify thermodynamic data. The figures depict the iron-carbon phase diagram, quasi binary sections with Si and Cr as well as the eutectic temperature for the stable and metastable systems as a function of the Si content.

Thermodynamic-kinetic model

MicroPhase is a thermodynamically coupled microsegregation model for multi-component and multi-phase systems with which chronological development of characteristic microstructural parameters; such as dendrite arm spacing and phase fractions, as well as thermo-physical properties can be predicted during solidification. The model was developed with the objective of generating computationally time-efficient predictions for complex materials in order to depict the influence of microstructural development on the solidification behaviour of components. The following figure shows the simulated microsegregation profile along the radius of a eutectic cell during the solidification of solid solution hardened spheroidal graphite cast iron having low Nb and Mo contents.

Simulation of microstructures

In a further approach, employing MICRESS also enables the time dependent development of microstructures to be computed in order to, for example, assess the influence of alloying elements on the form of spherical graphite in GJS. The following figure shows a simulated solidification sequence of hypereutectic spherical graphite cast iron compared to an etched micrograph. Owing to the nodular graphite, the melt is locally depleted of carbon which leads to the cessation of austenitic dendrite formation. Rather, the austenite grows from nodule to nodule caused by undercooling. These tools employed in research and development to, for example, virtually combine component and material development prior to performing experiments or to accompany traditional materials development.