Petar Cosic is a PhD researcher in I-Form based at UCD working in the area of material processing modelling. He obtained his undergraduate degree in Mechanical Engineering from the faculty of Mechanical Engineering, University of Belgrade, and then went on to complete a Masters in Aerospace Engineering at the same faculty. He is currently pursuing his PhD at UCD with his primary research area being multi-scale multi-physics modelling of additive manufacturing processes.
Technical Summary
Powder-Based Fusion Additive Manufacturing is an advanced technique for producing 3D metallic parts using loose alloy powder as raw material. The component is built layer by layer according to a computer-generated model of the final design. This is done by selectively melting sections of the powder with a laser or electron beam, which then solidify and fuse together. This approach is pioneering new advancements in fields like aerospace and biomedical engineering. The mechanical properties of the 3D-printed component are largely influenced by its micro-structure, which is determined by the solidification process.
There are various approaches to simulating this process currently developed but they can be vastly improved by expanding their fidelity and scale level. The main goal of this research is to provide value in the form of a better understanding of the underlying physics behind the PBF process as well as providing a new higher fidelity model for simulating the process on a multi-scale multi-physics level. This higher fidelity model will consider multiple factors such as the inclusion of the vapor phase, taking into account the flow of shielding gas, and taking into account the ejected particles. The output of this project will primarily be a new high-fidelity solver that can be used to simulate the PBF process and to provide better quality and more realistic simulation results on a bigger scale.
Expertise
Additive Manufacturing (3D Printing), Computational Mechanics, Data Analytics, Powder Bed Fusion, Predictive Modeling, Process Modeling