Deterministic simulations of solidification capture unstable dendritic growth resulting from undercooling and capillary effects.
Significance and Impact:
The unstable growth of a phase front in metallic melts results in formation of dendritic microstructures which impacts the material behavior. Deterministic simulation of the phase change phenomenon enables quantitative analysis of the morphology and prediction of unstable dendritic branches as well as development of reduced models for process scale simulations.
- Dendritic growth simulation using a sharp interface model to capture coarsening, remelting and unstable perturbations on the solidification front.
- A high order accurate level set based ghost fluid approach was developed to model the sharp solidification front on a structured finite difference grid.
- Front speed and interface morphology are quantified using a probability density function.
- Dendritic arm coarsening and remelting phenomenon are predicted from the probability density function.
- Anisotropic capillary effects are included in the model to account for crystal orientation.
The work was performed using the computational resources of the Oak Ridge Leadership Computing Facility (OLCF) and Compute and Data Environment for Science (CADES).
This research was supported by the High-Performance Computing for Manufacturing Project Program (HPC4Mfg), managed by the U.S. Department of Energy Advanced Manufacturing Office within the Energy Efficiency and Renewable Energy Office.
Vimal Ramanuj, Ramanan Sankaran, and Balasubramaniam Radhakrishnan, A sharp interface model for deterministic simulation of dendrite growth, Computational Materials Science, 169, November 2019, doi: 10.1016/j.commatsci.2019.109097.
Dendritic solidification and microstructure evolution play a vital role in determining the material properties. Capturing the morphology of the solidification front becomes critical in predicting the final dendritic structure. Front speed and curvature govern the local morphological changes. Development of branched microstructures is a complex phenomena which warrant direct numerical simulations and quantitative analysis. The work describes a high order accurate numerical model and strategies for quantifying the speed-curvature relationship using a probability density function (PDF). The coarsening of dendritic arms, remelting and instability of branched microstructures in presence of non-uniform temperature gradient and anisotropic surface tension are captured using the proposed approach. The data generated using such deterministic simulations and the probability density function can be used for developing reduced models for process scale simulations.