Abstract
Solidification processes are present in a wide range of manufacturing methods and applications, from metallurgy to food processing. In recent years, Phase Field models have been increasingly used to simulate and predict the formation and evolution of material microstructure and phase change interfacial kinetics. However, these methods usually lead to computationally involved numerical schemes, revealing the need for more efficient computational solutions. In this work, two different model reduction techniques, the Laplacian Spectral Decomposition and the Proper Orthogonal Decomposition, have been employed for model reduction of the Kobayashi model, a non-linear solidification Phase-field model. The performance of both low-order models has been illustrated and compared using a range of undercooling and seeding conditions. Results obtained accurately represent the behaviour of the full system, showing the potential of reduced order approaches for the modelling of complex interfacial systems.
| Original language | English |
|---|---|
| Pages (from-to) | 637-642 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 51 |
| Issue number | 2 |
| Early online date | 3 May 2018 |
| DOIs | |
| Publication status | Published - 2018 |
| Event | 9th Vienna International Conference on Mathematical Modelling - Vienna, Austria Duration: 21 Feb 2018 → 23 Feb 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 12 Responsible Consumption and Production
Keywords
- Model reduction
- Phase change
- Phase-field method
- Solidification
ASJC Scopus subject areas
- Control and Systems Engineering
Fingerprint
Dive into the research topics of 'Reduced order methods for the solution of solidification Phase-Field models'. Together they form a unique fingerprint.Projects
- 1 Finished
-
Brunel University lead - Centre for Sustainable Energy Use in Food Chains
Norton, I. (Co-Investigator), Fryer, P. (Principal Investigator) & Windridge, D. (Co-Investigator)
Engineering & Physical Science Research Council
1/04/13 → 30/06/19
Project: Research Councils
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