Accurate numerical prediction of thermo-mechanical behaviour and phase fractions in SLM components of advanced high strength steels for automotive applications

Authors

  • Kiranmayi Abburi Venkata Simufact engineering gmbh, a Hexagon company
  • Rohith Uppaluri Simufact engineering gmbh, a Hexagon company
  • Bernd Schob Department of Lightweight Structures and Polymer Technology, Chemnitz University of Technology
  • Camilo Zopp Department of Lightweight Structures and Polymer Technology, Chemnitz University of Technology
  • Richard Kordass EDAG Engineering GmbH
  • Jan Bohlen EDAG Engineering GmbH
  • Matthias Höfemann Salzgitter Mannesmann Forschung GmbH, Department Welding and Joining Technology
  • Marcin Kasprowicz Wadim Plast Sp. z o.o.
  • Andrzej Pawlak Centre for Advanced Manufacturing Technologies CAMT, Faculty of Mechanical Engineering, Wroclaw University of Science and Technology
  • Edward Chlebus Centre for Advanced Manufacturing Technologies CAMT, Faculty of Mechanical Engineering, Wroclaw University of Science and Technology

DOI:

https://doi.org/10.21935/tls.v5i1.145

Abstract

Conventional crash absorber in automotive applications, so called crash boxes are fabricated via deep drawn sheet metal resulting in significant lead times and costs. Laser Powder Bed Fusion processes, like Selective Laser Melting (SLM) offer an attractive alternative for the fabrication of crash parts while eliminating any need for costly forming dies and reducing the lead times, provided required material properties are achieved. Reliable numerical simulation model to predict the SLM build process with greater spatial resolution and accuracy is indispensable to understand the process further in order to ensure its applicability to crash structures. In this paper, an improved simulation methodology for SLM process is presented to predict the material behaviour via temperature, deformation, hardening, flow stress and phase fractions throughout the component with increased accuracy and greater resolution. To achieve desired spatial resolution, the equivalent layers are subdivided into individual tracks, which are then deposited sequentially to simulate the printing process. The material is a medium manganese (7­-8 %) transformation induced plasticity (TRIP) steel with austenite and martensite primary phases. The multiple solid-state phase transformation cycles undergone by the material are modelled in the simulation and the final phases are predicted. The results indicate improved accuracy and higher resolution in predictions for temperature, phase fractions and deformation.

Published

2022-03-15