The thermo-mechanical shaping processes, such as rolling, forging and extrusion as well as the heat treatment,
determine the properties of a material. The developed microstructure during hot deformation is the result of
deformation mechanisms such as dynamic recovery and dynamic recrystallisation. The hot deformation can also
result in damage and flow localisation, especially in multiphase metal based materials.
Several models have been proposed to correlate the parameters of the deformation process (temperature, strain and
strain rate) and of the pre- and post- heat treatments (temperature-time history) with the flow behaviour and the
microstructure. Following this objective, the processing maps concepts were developed based on the dynamic
materials model (DMM) and later, the modified DMM introduced some modifications at the calculations of the
processing maps. The processing maps are extensively used with good results not only for one-phase materials but
also for multiphase ones. Even so, the phenomena predicted by the models are not based on microstructural features
of the deforming material as the maps are based on general thermodynamics this leads still some questionable
points related to the materials microstructure interpretation.
The aim of this project is to find the correlation of the relevant microstructural changes with thermodynamic
parameters. New characterization techniques such as EBSD and synchrotron, combined with traditional
characterisation methods are proposed to reveal the microstructural features developed after/during hot
deformation. The quality of the obtained data and of the experimental tests will be improved by the combination of
finite element models to locate the precise deformation parameters in the sample, and the Gleeble simulation
machine. This work will concentrate on microstructural studies related to the hot deformation of metals with
different compositions, stacking fault energies, diffusion parameters and phase combinations: age hardenable
aluminium alloys, alpha-beta and near beta titanium alloys, low carbon steels and magnesium alloys. The results
will be correlated to the processing maps, and finally, a knowledge based relationship will be established to
interpret the J co-content defined in the basics of the dynamic materials model by microstructural properties.