Prediction of Microstructure Evolution of Cold Sprayed Coatings Using a Dislocation Density Based Constitutive Model

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Prediction of Microstructure Evolution of Cold Sprayed Coatings Using a Dislocation Density Based Constitutive Model
Title:
Prediction of Microstructure Evolution of Cold Sprayed Coatings Using a Dislocation Density Based Constitutive Model
Journal Title:
Proceedings of the 2nd International Conference on Advanced Surface Enhancement (INCASE 2021)
Keywords:
Publication Date:
21 August 2021
Citation:
Msolli, S., Zhang, Z.-Q., Seng, D. H. L., Zhang, Z., Guo, J., Reddy, C. D., Sridhar, N., Pan, J., Tan, B. H., & Loi, Q. (2021). Prediction of Microstructure Evolution of Cold Sprayed Coatings Using a Dislocation Density Based Constitutive Model. Proceedings of the 2nd International Conference on Advanced Surface Enhancement (INCASE 2021), 125–128. https://doi.org/10.1007/978-981-16-5763-4_27
Abstract:
A dislocation density based model is implemented as a user hardening subroutine in Abaqus within the Eulerian finite element framework to predict the Geometrically Necessary Dislocations (GND) density and grain refinement during the cold spray deposition process of Al6061-T6. The model is capable of exploring the dependency of the microstructure on the cold spray process parameters such as particle velocity, deposition angle, initial temperature and particle size. Furthermore, the model depicts microstructural evolution in critical regions such as the coating-substrate interface and particle boundary and provides insights into the microstructural distribution observed at different locations in a cold sprayed part.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the A*STAR - Machining Learning Assisted Control of Metal Cold Spray and Shot Peening Processes
Grant Reference no. : A1894a0032

This research / project is supported by the A*STAR - Singapore Aerospace Program
Grant Reference no. : A1715a0073
Description:
This is a post-peer-review, pre-copyedit version of an article published in Proceedings of the 2nd International Conference on Advanced Surface Enhancement (INCASE 2021). The final authenticated version is available online at: http://dx.doi.org/10.1007/978-981-16-5763-4_27
ISSN:
9789811657634
ISBN:
9789811657627
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