Deliverables Appraisal of metallurgical theories Physically-based models allow tests to be performed on the assumed theories: do they actually generate the correct microstructures, as are observed? These can address major issues, such as how does a particular morphology occur at all, or gradations: under what conditions will the growth change from one morphology to another? The software has proved itself useful regarding prediction of cellular or dendritic morphology and the associated, characteristic length-scales. It has explained how under certain circumstances, the microsegregation peaks that were all aligned during solidification, can 'drift' and become out of phase during cooling in the solid-state. It is beginning to show insight into peritectic cracking susceptibility. It has highlighted issues that need revised or new theories to explain them. The simulations, employing accepted assumptions/theory, produce fairly smooth kinetics for grain growth. The experimental results under Result 17748 show that in practice, grains grow with periods of stagnation punctuated by localised bursts of activity. Similarly, the simulations show that Strain Induced Boundary Migration should be the principal recrystallization mechanism: although this is the case in some steels, in typical formable sheet steels this mechanism is almost dormant, allowing alternative mechanisms to occur. The simulations are logical consequences of the assumed theories, so we have a problem with the theories. Some progress has also been made concerning the formation of bainite. If the transformation is primarily diffusion driven, why do we get a morphology of 2-fold symmetry from a system of crystallographic/energetic 4-fold symmetry? Coupling with stress fields arising from the density difference between the parent austenite and the bainitic ferrite, it has been shown that a 2-fold symmetric forms can result. However, it did not prove possible to compare alternative theories of bainite formation within this project. Experimental data The project has yielded a valuable set of experimental results on the kinetics of the ferrite formation from austenite in several types of steel, and on the resulting microstructures. Since different experimental techniques have been used (Confocal Laser Scanning Microscopy, dilatometry, microscopy and others), different aspects of the kinetics and of the microstructures have been highlighted. A very good accuracy has been achieved, which makes the results very useful for interpretation in terms of kinetic and microstructural models (specifically: phase-field modelling). The results can thus serve as a basis for further understanding of the occurring phenomena, but can (and will) also be used in the education of both undergraduate and graduate students in Materials Science and Engineering. Besides, with the help of these results the potential for scientific interaction and collaboration with research groups in the field has been strongly enhanced. Software package Based on the so-called phase-field theory a state-of-the-art software package for simulation of microstuctural evolution in alloys have been developed. This software package, i.e. MICRESS, can now simulate in 3D, phase transformations in alloys including e.g. solidification, recrystallization and grain growth. The initial code existing at the start of the project has migrated to Fortran 90, an improved nucleation model has been incorporated, account has been made for limited interface mobility due to both solute drag and particle pinning, a recrystallisation model has been added and a model added to account for effects from stress and strain fields. Furthermore, MICRESS has been linked to Thermo-Calc using the so-called TQ-Interface. The TQ-Interface is a product in itself and it has been integrated into other software outside this project. The interface establishes a standard for using thermodynamic data in application software. For linking the TQ-Interface to MICRESS several specific modifications and improvements had to be made. This link to Thermo-Calc provides the MICRESS user with easy access to assess and proper thermodynamic and kinetic information, to incorporate and base a particular simulation on. A key factor for the success of the integration of real thermodynamics in the phase field software is the speed of calculation. A complex simulation in 3D may take from several hours to weeks even on a fast computer. Adding thermodynamic calculations inside this may make the simulation 100-1000 times slower. Even if the computer speed is expected to improve in the future the goal has been to make simulations possible also on standard computers. This means a technique had to be developed to improve the speed and for this purpose a neural network was adopted. Instead of calculating the thermodynamic properties in each grid-point and each time step the neural network is ¿trained¿ during an initial stage, and during the main part of the simulation the network will provide interpolated values with the possibility to improve these using the full thermodynamic description. Searching for OpenAIRE data... There was an error trying to search data from OpenAIRE No results available
