@article{15,
  keywords = {2D/3D toolpath, Deposition geometry model, Directed energy deposition, State space thermomechanical model},
  author = {Deniz Ertay and Mihaela Vlasea and Kaan Erkorkmaz},
  title = {Thermomechanical and geometry model for directed energy deposition with 2D/3D toolpaths},
  abstract = {<p>Directed energy deposition (DED) is a metal additive manufacturing process, where dimensional accuracy and repeatability are traditionally challenging to achieve. Strategies for computationally inexpensive process modelling and fast-response process controls of the laser deposition process are necessary to keep the geometric features close to the required dimensional tolerances. The deposition geometry depends highly on the complex local laser-material interaction and global thermal history of the substrate. In order to control the deposition geometry, an accurate and computationally inexpensive discretized state space thermal history model coupled with an analytical deposition geometry model is developed in this work. The model accounts for the local laser-material interaction using the mass and energy equilibrium equations coupled in a lumped parameter solution, as well as the global thermal history of the product using a state space thermomechanical discretization. In literature, studies have only focused on 1D toolpaths with constant process parameters such as speed, powder feedrate, and laser power. As it is possible to achieve highly complex geometric shapes with additive manufacturing, it is important to have models compatible with 2D/3D complex toolpaths. In this paper, an analytical thermomechanical model and a coupled deposition geometry model for DED process are presented and experimentally validated. As such, the thermal history of the deposited part is predicted throughout the process and the geometric features are predicted for 2D toolpaths.</p>
},
  year = {2020},
  journal = {Additive Manufacturing},
  volume = {35},
  pages = {101294},
  issn = {2214-8604},
  url = {https://www.sciencedirect.com/science/article/pii/S2214860420306667},
  doi = {https://doi.org/10.1016/j.addma.2020.101294},
}