About
Sampreet Rangaswamy
Postgraduate Researcher
DCU
Sampreet Rangaswamy is a PhD researcher in I-Form, based at DCU. He completed his bachelor’s degree in Mechanical Engineering from the SRM Institute of Science and Technology (India). He obtained his master’s degree in Advanced Engineering Materials from the University of Manchester (UK). He worked on laser and TIG welding of Hastelloy C-276 during his undergraduate studies and for his master’s degree, he examined the microstructural evolution of aluminium alloy 7075 during solution heat treatment using the CALPHAD method. He is pursuing his PhD at DCU while working on the development and validation of a thermal model for additive manufacturing of Nitinol/IN939. His main research interests include metal additive manufacturing, parameter optimisation, material characterisation and process modelling/simulation.
Research Interests (Lay Summary)
Sampreet started his PhD with I-Form in 2022 and his research focuses on investigating the properties and optimising the process parameters in additive manufacturing of Nitinol and Inconel 939 alloys. Nickel-based superalloys, NiTi and IN939 are used in various aerospace, automobile, and biomedical applications owing to their extraordinary properties. Additive manufacturing is the process of building a component layer by layer and is capable of producing parts with intricate geometries and precise dimensions. The thermal models developed in Sampreet’s project will enhance the modelling capability for additive manufacture of components using Nitinol and Inconel 939 alloys.
Technical Summary
Sampreet’s PhD project involves developing a thermal model for IN939 and NiTi alloys processed via metal additive manufacturing that can be used in a process design database. Determining the process parameters of metal Additive Manufacturing which result in specific properties, such as level of porosity, induced strain, and tensile strength is still challenging and requires detailed investigations for new materials and geometries. The lack of a process design database poses difficulty for product design and development teams to determine and optimise process parameters. A process design database provides reverse engineering capabilities to users and it enables process engineers to set the correct levels within the process to achieve specific produced part quality and capabilities. Metal composition and process parameter variation will be investigated as part of Sampreet’s research project.