Multi-scale Multi-physics Modelling of Metal Additive Manufacturing: Heterogeneity and Validation
Assoc. Prof. Chinnapat Panwisawas, Queen Mary University of London, UK
15:00-16:00, November 10, 2023
Yiucheng Lecture Hall (500), Xu Zuyao Building
Chinnapat Panwisawas is currently Associate Professor (Senior Lecturer) in Materials and Solid Mechanics at Queen Mary University of London (QMUL) since July 2022. He obtained his PhD in Metallurgy and Materials from University of Birmingham in 2013. From 2013 to 2018, he joined Rolls-Royce University Technology Centre at the University of Birmingham. In June 2018, he became Senior Fellow & EPSRC UKRI Innovation Fellow at Department of Materials, University of Oxford. Before joining QMUL, he was Associate Professor in Digital Manufacturing at School of Engineering, University of Leicester. His research interest focused on multi-scale materials modelling of liquid/solid reactions, particularly in additive manufacturing of high-performance alloys using an integrated computational material engineering framework. Validatory studies using in-situ neutron measurement, X-ray tomography, high-speed imaging and advanced characterisation were used to verify the mathematical modelling.
Understand the fluid dynamics of multi-metals powders and laser using powder-bed additive manufacturing (AM) as a function of AM process parameters through a high-fidelity multi-physics modelling using particle spreading model and melt-pool simulation via computational fluid dynamics calculation rationalises the multi-metal thermal-chemical-fluid flow and allows the link between composition and metal fluid flow science to be constructed. The results provide insights into elemental powder AM and in-situ alloying of NiTi binary metals and Ti-Zr-Cu tertiary system. Prediction of microstructure variation using microstructure modelling induced by the localised liquid/solid reaction can facilitate process design for laser-materials interaction process. Better understand of property scatter induced by relevant microstructures can be used as a science-based tool for part scale simulation. This leads to development of reduced-order modelling to simulate macroscale AM components. The novel materials-process design developed will lead to AM design of optimum final product composition and mitigation of defect formation. The framework provides a materials physics-based approach to simulate the multi-metal AM process. Synergy between modelling and in-situ experiments needs to be steered for accomplishing the novel digital disruptive materials and process design for metal AM.