Thermal Modeling of Polyamide 12 Powder in the Selective Laser Sintering Process Using the Discrete Element Method.

Area of Science:

• Additive Manufacturing
• Computational Materials Science
• Thermal Engineering

Background:

• Selective Laser Sintering (SLS) is a crucial additive manufacturing technique for complex geometries.
• Accurate thermal modeling of SLS is essential for predicting part quality, including microstructure and residual stresses.
• Existing simulation methods may not fully capture the complex thermal dynamics of powder-based processes.

Purpose of the Study:

• To develop and validate a novel discrete element method (DEM) framework for thermal simulation of the SLS process.
• To investigate the temperature evolution within a polyamide 12 (PA12) particle domain during SLS.
• To assess the influence of laser parameters on thermal behavior and validate the simulation's reliability.

Main Methods:

• Development of a thermal simulation framework using the discrete element method (DEM) implemented in Python.
• Simulation of a polyamide 12 (PA12) particle domain with simplified interaction laws.
• Modeling particle-boundary interactions and heat exchange.
• Investigation of laser power and scan time effects on particle temperature.

Main Results:

• The DEM framework accurately captures temperature distribution within the laser-scanned domain.
• The simulation results show good agreement with experimental data.
• The study demonstrates the impact of laser power and projection time on PA12 particle temperatures.

Conclusions:

• The proposed DEM framework provides a reliable tool for simulating thermal processes in powder-based additive manufacturing.
• DEM is effective in predicting temperature distribution and understanding the influence of process parameters in SLS.
• This approach enhances the ability to anticipate and control the quality of SLS-manufactured parts.