Additive Manufacturing
Solutions by Application
- Improve the accuracy of macroscopic heat conduction models.
- Microstructure tailoring by understanding the influence of process parameters
on nucleation, solidification length scale and grain morphology. - Design effective homogenization schemes.
- Expand the selection of materials with the help of multicomponent diffusion.
Additive manufacturing (AM) submits the material to extremely high cooling rates and thermal gradients, which results in unique microstructures and materials properties. OpenPhase provides detailed insights into microstructure evolution in the context of additive manufacturing. Process parameters control dendrite spacing and shape, concentration gradients, nucleation kinetics and mechanical properties. OpenPhase evaluates these properties through simulation of physics-based models resolved in space and time.
OpenPhase capabilites
1- Improve the accuracy of macroscopic heat conduction models.
- The implicit heat conduction model gives one precise control over the thermal boundary conditions specific to the additive manufacturing process.
- Accurate modelling of latent heat release, thereby effective cooling rate during solidification.
- Obtain solidification velocity and tip undercooling, which significantly influence grain morphology.
- OpenPhase also enables the modelling partial remelting of previously built layers.
2- Microstructure tailoring by understanding the influence of process parameters.
- AM involves several critical process parameters making it difficult to understand the influence of each process parameter on the grain morphology. With OpenPhase, it is possible to estimate the dendrite arm spacings and solidification grain morphologies for the given process conditions.
- Based on the application, the either equiaxed or columnar grain structure is preferred. With OpenPhase, it is possible to control the grain morphology by modelling the nucleation of primary and secondary phases specific to the thermal boundary conditions and chemical compositions.
- For single crystal microstructure, it is crucial to restrict nucleation resulting from partial remelting of previously built layers. With OpenPhase, one can estimate the solute undercooling resulting from remelting and adjust the process parameters to control the nucleation.
- Understand the segregation behaviour of alloying elements at interdendritic regions and the bulk of the primary and secondary phases.
3-Design effective homogenization schemes.
- Estimate the solvus temperatures for the secondary phases
- Estimate the time required for complete homogenization of the system.
- Avoid incipient melting by the knowledge of in microsegregation after complete solidification.
4- Expand the selection of materials with the help of multicomponent diffusion.
- With TC-Coupling, OpenPhase enables modelling solidification of the entire alloy composition.
- Gibbs energies, chemical diffusivities and kinetic mobilities are obtained directly from the thermodynamic database.
- With a full alloy range, the chemical diffusivities vary significantly among the solute elements. Understand microsegregation of different alloying elements in each phase.
