Mr Gowthaman Parivendhan
Postgraduate Researcher

Gowthaman Parivendhan is a Postgraduate researcher in I-Form, working in the area of Additive Manufacturing (AM) process-structure-property modeling. He obtained his bachelor’s degree in Mechanical Engineering from Anna University, Chennai, India and then completed a master’s in Computational Materials Science (CMS) at Technische Universität Bergakademie Freiberg, Germany. His main research interests include metal AM, computational fluid dynamics, and numerical modeling of granular media.

Research Interests (Lay Summary)

Gowthaman commenced his PhD in 2018 and has been developing a numerical model for powder flow and melting. Numerical models are used to simulate and predict the behaviour of materials during the Selective Laser Melting (SLM) process cycle. The significance of numerical modeling is to study the physical phenomena that take place during melting and subsequent solidification of Ti6Al4V powder, thus providing a better understanding of the SLM process mechanism. The results obtained from this work, along with experimental studies, will improve the quality of additively manufactured parts.

 

Technical Summary

Melt pool dynamics and subsequent crystallization have a significant impact on the mechanical properties of an additively manufactured part. Numerical modeling of SLM can aid in understanding the underlying physical phenomena. The powder bed is discrete and randomly packed, which if neglected can lead to an unrealistic symmetrical melt track. To account for the stochastic nature of the powder bed, the Discrete Element Method (DEM) is used to model the powder deposition. The powder particles are then transferred onto a Finite Volume Mesh to solve the heat transfer and flow equations using OpenFOAM.

The Volume of Fluid (VOF) approach is used to model the flow in the system while an extended version of a solidification phase change model by Voller et al. is employed to solve the energy equation. Laser irradiation is included by solving the Radiation Transfer Equation (RTE) using the Discrete Ordinate (DO) method and these are introduced as source terms in the energy equation. Numerical benchmarks such as the Bubble rise problem, Stefan problem and 2-D Gallium melting are employed to verify the implementation of the above mentioned mathematical models. Influence of the particle size distribution on the shape and size of melt tracks are then investigated.

The results obtained from this study can provide better understanding of powder bed modeling of the SLM process.

Expertise

Advanced Manufacturing, Failure Modeling, Powder Bed Fusion, Predictive Modeling, Process Modeling, Selective Laser Melting (SLM), Selective Laser Sintering (SLS)