The 3D printing simulation in Abaqus is done via two methods:
- Using python scripting and subroutine
- Using AM Modeler plug in
The initial approach involves layering the model, which can be done using either a CAD software or Abaqus itself. Every layer must be printed and activated in each step. Additionally, boundary conditions and material properties must be applied according to the problem’s equations after a layer has been printed. These equations explain the changes in material properties, thermal conditions, and so on. These tasks are separated between python code and the necessary subroutines. Simply input your data, run the python code, and wait for the analysis to finish.
Python scripting: To perform a 3D printing simulation in Abaqus, the layers of the model must be imported and assigned material properties, and then piled up and assembled in the Assembly module. Each layer is printed in a separate step and must be activated in the Interaction module and have its boundary conditions defined in the Load module. Finally, the layers are meshed and the model is ready. However, manually applying settings to each layer can be time-consuming and exhausting, so a script can be executed with input data to automate the simulation process.
Subroutine: Due to the variability of elasticity during the 3D printing process, a specific subroutine is necessary to calculate the elasticity properties based on the equations that describe these changes. Additionally, a subroutine is necessary to calculate the temperature variations that occur during the process. The USDFLD and DISP subroutines are suitable for these tasks.
You can find more info about the first method via the links below:
The second method, on the other hand, uses a plug-in called “AM Modeler” in Abaqus. The AM Modeler is a graphical user interface plug-in that enables 3D printing simulations with minimal errors. No coding or programming is required, simply input the necessary data, create a job, and begin the simulation. The plug-in offers two simulation methods: Eigenstrain and Thermomechanical, each with multiple process types. The Eigenstrain method includes Trajectory-based and Pattern-based processes, while the Thermomechanical method includes Trajectory-based powder bed fabrication, Pattern-based powder bed fabrication, Laser direct energy deposition, and Fusion deposition modeling processes. The plug-in supports popular 3D printing types such as Power Bed Fusion (PBF), Direct Energy Deposition (DED), and Material Extrusion (ME).
Eigenstrain: Eigenstrain is an engineering concept used to account for inelastic deformation resulting in residual stresses and distortions in manufactured components, including those from additive manufacturing. A single static stress analysis serves as the basis for an eigenstrain analysis of an additive manufacturing process, where predefined eigenstrains are applied to each element to indicate inelastic deformation. The goal of an eigenstrain analysis is to predict distortions and residual stresses in the part. While a thermal-stress analysis yields more accurate results, an eigenstrain analysis is faster as it only requires a static procedure.
Thermomechanical: This method involves a sequential analysis of an additive manufacturing process, where a heat transfer analysis is conducted first, followed by a static structural analysis that incorporates the temperature fields obtained from the thermal analysis. This approach provides precise control over the solution’s accuracy and enables users to specify processing conditions accurately in both time and space. However, the simulation can become computationally expensive as the time and spatial resolution increase, despite its thoroughness and realism.
You can find more info about the second method via the links below:
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