A Computational Approach for Modeling Plasma Sprayed Coatings from Splat to Bulk Deposits

Authors

Sadhana Bhusal, Florida International UniversityFollow

Document Type

Thesis

Degree

Master of Science (MS)

Major/Program

Mechanical Engineering

First Advisor's Name

Arvind Agarwal

First Advisor's Committee Title

Committee Co-Chair

Second Advisor's Name

Benjamin Boesl

Second Advisor's Committee Title

Committee Co-Chair

Third Advisor's Name

Yiding Cao

Third Advisor's Committee Title

Committee Member

Fourth Advisor's Name

Sharan Ramaswamy

Fourth Advisor's Committee Title

committee Member

Keywords

Computational Approach, Plasma Spray, Splat Simulation, Finite Element Analysis, Stochastic Approach, Mechanical Property

Date of Defense

5-28-2019

Abstract

In this study, a multi-pronged computational approach is developed to predict the effect of spray parameters on aluminum oxide splat formation and mechanical properties of the coatings. The splat morphology is investigated using computational fluid dynamics approach. Simulated splat morphologies show a good agreement with the experimentally obtained splats. Three-dimensional coating structure is constructed using the stochastic approach using simulated splat morphologies. Finite Element Analysis is used to compute the elastic modulus of the coating. An inter-splat correction factor is introduced which considers inter-splat cracks, interface bonding and other effects like curling of splats and splat sliding. After the correction factor, the computed elastic modulus for simulated coating is comparable to the experimental values (4~5%). This study shows that the proposed computational approach can predict the mechanical properties of the coating and is promising for developing plasma-sprayed coatings with predictable properties and can be extended to other materials systems.

Identifier

FIDC007814

Recommended Citation

Bhusal, Sadhana, "A Computational Approach for Modeling Plasma Sprayed Coatings from Splat to Bulk Deposits" (2019). FIU Electronic Theses and Dissertations. 4220.
https://digitalcommons.fiu.edu/etd/4220