Develop Efficient Numerical Methods to Model Laser Powder Bed Fusion Additive Manufacturing Processes

During the process of Laser powder bed fusion (L-PBF), highly localized heating and rapidly cooling induce unique microstructure, residual stress and deformation in the built parts. Efficient numerical modeling methods were developed to predict temperature, microstructure, hardness, stress, strain, and deformation for L-PBF. The analysis method includes a pre-processing module, a powder deposition module, a thermal module, a metallurgical module, and a mechanical module. The pre-processing module is used to slice a solid geometry into layers and create laser heat lines for each layer based on a designed scan pattern. The power deposition module is used to model powder-to-solid transition by changing material properties based on the laser’s locations. The thermal module works with ABAQUS software to predict temperature by inputting laser power, travel speed, and a heat-line sequence. The metallurgical module is used to predict microstructure and hardness by inputting the predicted temperature history. The mechanical module is used to predict stress and deformation by inputting the predicting temperature history.

Microstructure and hardness of AISI 4140 steel built with L-PBF were predicted using the developed numerical modeling tool. Experimental measured hardness was used to validate the model prediction. It was found that tempering effect has to be modeled in order to predict the hardness correctly. Residual stresses of Inconel 718 were predicted in a block sample built by L-PBF. The predicted maximum principal stress distribution in the block shows that tensile stresses were on the outer surface and compressive stresses were inside the block. This stress distribution explains that cracks are often initiated on the surface and stopped after propagating a certain depth during L-PBF for some crack-sensitive materials. Deformation on bridge samples made of Inconel 718 and Ti-6Al-4V were predicted by a layer-heating technique. The predicted deformation agreed with experimental measurement.