• Luckabauer, Martin
• Sattari, Mohammad
• Römer, Gert-Willem

Abstract

In laser-based metal processing techniques, the intensity profile of the laser beam plays an essential role in the cyclic temperature evolution of the process. On the other hand, the microstructure and the resulting mechanical properties of the part follow the temperature profile during solidification. One way to control the microstructure and mechanical properties of a part, is the manipulation of the laser beam intensity profile using the so-called laser beam shaping method. Since finding a suitable laser beam intensity profile based on the required microstructure and mechanical properties is an expensive iterative trial and error process, the use of high-fidelity models is preferable to experiments.<br/><br/>In this research, a thermo-fluid model is developed for the Laser-assisted powder-based Direct Energy Deposition (L-DED) process based on the Computational Fluid Dynamics (CFD) method, where the powder particle flow is simulated using the Discrete Element Method (DEM) and the governing equations are solved using the Finite Volume Method (FVM). Also the<br/>Volume of Fluid (VOF) method is used to track the metal and gas interface. With high accuracy, this model includes arbitrary laser beam intensity profiles, powder particle stream and particle size distribution, powder particle and laser beam interaction, addition of powder particles to the molten pool, temperature- and incident angle- dependent laser beam<br/>absorption, Marangoni effects due to surface tension, buoyancy flow, evaporation, solidification, shrinkage, and heat transfer in the substance and to the surroundings. On the other hand, a solidification microstructure texture model is developed and one-way coupled to the thermo-fluid model. The microstructure model is based on the Cellular Automata (CA) method and includes the grain nucleation and columnar-equiaxed grain growth competition to simulate the crystallographic texture changes of 316L austenitic stainless steel. In this model, the crystallographic orientation of the nuclei is selected randomly, but the grain growth with the preferred crystallographic orientation is followed based on a dendrite growth kinetics model. With the aid of experiments, both the thermo-fluid and the solidification microstructure models are validated. The thermo-fluid model has a high agreement with the experiments in terms of the geometry of the molten pool and clad. The microstructure model also predicts the size and crystallographic orientation of the grains after solidification in excellent agreement with the EBSD results.<br/>

Topics

• Deposition
• impedance spectroscopy
• surface
• grain
• stainless steel
• experiment
• texture
• electron backscatter diffraction
• evaporation
• directed energy deposition
• solidification
• grain growth
• discrete element method
• cellular automata