| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
Cold Spray Additive Manufacturing: Part Quality and Performance
|
| Presentation Title |
A Hybrid Molecular Dynamics/Finite Element Approach to Studying the Bonding Process of Cold Sprayed Metal Particles |
| Author(s) |
Scott Julien, Mark DelloStritto, Jason Pattis, Akul Chaudhuri, Enqiang Lin, Qiyong Chen, Ozan C. Ozdemir, Michael L. Klein, Sinan Muftu |
| On-Site Speaker (Planned) |
Scott Julien |
| Abstract Scope |
While the strength and nature of cold spray particle bonding can be studied to a limited extent using experimental techniques (e.g., single particle impacts and micrographic inspection of debonded particles), computational techniques, such as finite element (FE) method, are needed to fully understand the process dynamics. Molecular dynamics (MD) simulations have been shown to effectively extract a traction-separation law (TSL) for a material, at timescales (picosecond, 10^-12) similar to that of particle impacts (PI, nanosecond, 10^-9). In the present study, a neural network potential (NNP), trained using ab initio density functional theory (DFT), is used to model the interaction between nickel (Ni) atoms. The NNP is implemented in MD simulations of the bonding/debonding process of two slabs of Ni atoms, and the interfacial TSL is derived. The TSL is input into FE PI models of Ni atoms impacting an Ni substrate, and the physics of the bonding process is studied. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Powder Materials, Modeling and Simulation, Computational Materials Science & Engineering |