Predictive model of impact-induced bonding in cold spray using the Material Point Method
dc.contributor.author | Tang, Jiaju | |
dc.date.accessioned | 2021-05-27T13:28:20Z | |
dc.date.available | 2021-05-27T13:28:20Z | |
dc.date.issued | 2021-05-27 | |
dc.date.submitted | 2021-05-20 | |
dc.description.abstract | Cold spray technology has emerged in recent years as a promising method of powder deposition that is inherently different from other processes. Without melting of the particles prior to deposition, powders of a wide range of materials can be deposited onto a substrate primarily through their initial kinetic energy. By keeping particle temperatures below melting, coatings made from cold spray are able to elegantly avoid many temperature-related defects commonly seen in traditional coating methods. The amount of kinetic energy required for successful bonding has been experimentally shown to be defined by a critical velocity, which varies depending on the thermomechanical properties of the powder material. Due to the time duration across which bonding occurs, it is difficult to observe the precise bonding phenomena in experiments leading to an emphasis on numerical simulation. However, most numerical studies have been focused on using mesh-based FEMs and identify bonding during post-processing of results. As such, these models are incapable of properly predicting bonding or bond effects on material behavior. In the current thesis, a bonding model is developed within a Material Point Method (MPM) framework that is able to directly model bonding effects on each body within the simulation. By using the MPM, it is possible to combine the advantages of Lagrangian and Eulerian FEMs while simultaneously minimizing their shortcomings in modeling the extreme strain and strain rate conditions seen in cold spray. This novel, direct bonding model introduces a time-discrete bond parameter whose evolution is based on adhesion energy, similar to the energy release rate seen in damage/fracture modeling. The overall code has been generalized to also provide initial consideration of multiparticle impacts, which is important for modeling the overall build-up and predicting the properties of coatings or structures. With the current model, it is possible to produce accurate predictions of the critical velocity for a range of Al particle sizes. Through use of adhesion energy and regularization techniques, the bonding model is able perform independently of discretization level and accurately capture the material jetting behavior observed experimentally to be related to impact-induced bonding. A linear trend is predicted such that critical velocity decreases as particle diameter increases. Furthermore, the current model also predicts convergence of the percent bonded area with grid size refinement towards a value which aligns with theoretical works. This further suggests that the current model is also able to provide insight on the bond quality and mechanical properties of the final coating/component with sufficient discretization. | en |
dc.identifier.uri | http://hdl.handle.net/10012/17030 | |
dc.language.iso | en | en |
dc.pending | false | |
dc.publisher | University of Waterloo | en |
dc.subject | numerical modeling | en |
dc.subject | cold spray | en |
dc.subject | impact-induced bonding | en |
dc.subject | finite element | en |
dc.subject | material point method | en |
dc.title | Predictive model of impact-induced bonding in cold spray using the Material Point Method | en |
dc.type | Master Thesis | en |
uws-etd.degree | Master of Applied Science | en |
uws-etd.degree.department | Mechanical and Mechatronics Engineering | en |
uws-etd.degree.discipline | Mechanical Engineering | en |
uws-etd.degree.grantor | University of Waterloo | en |
uws-etd.embargo.terms | 0 | en |
uws.contributor.advisor | Jahed, Hamid | |
uws.contributor.advisor | Hirmand, Mohammadreza | |
uws.contributor.affiliation1 | Faculty of Engineering | en |
uws.peerReviewStatus | Unreviewed | en |
uws.published.city | Waterloo | en |
uws.published.country | Canada | en |
uws.published.province | Ontario | en |
uws.scholarLevel | Graduate | en |
uws.typeOfResource | Text | en |