Mr. Vaibhav Nain Profile

Vaibhav Nain

at IREPA LASER

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Publications (1)

Proceedings Article | 20 May 2022 Presentation + Paper

Numerical modeling for large-scale parts fabricated by directed energy deposition

Vaibhav Nain, Thierry Engel, Muriel Carin, Didier Boisselier

Proceedings Volume 12135, 1213503 (2022) https://doi.org/10.1117/12.2624947

KEYWORDS: Distortion, Thermal modeling, 3D modeling, Sensors, Deposition processes, Data modeling, Computer simulations, Additive manufacturing, Process modeling

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The possibility of large-scale part fabrication is the biggest novelty factor associated with Directed Energy Deposition (DED) Additive Manufacturing (AM) technology. However, issues like deformation and residual stresses in the fabricated part originated from DED process physics are still hindering the possibility of large-scale part fabrication. To overcome these bottlenecks, a DED process simulation that predicts the thermo-mechanical response of the material/workpiece can be a useful tool. There are some conventional simulation techniques that are employed commonly for other technologies like welding or Powder Bed Fusion (PBF). But using the same simulation methodologies for the DED process will lead to impractical computation time or inaccurate results. Hence, in the present work, an efficient simulation methodology dedicated to DED is proposed. The proposed model reduces the computation time drastically and also keeps the desired computation accuracy levels. An equivalent heat source is employed that efficiently models the material deposition along with the programmed deposition strategy. The inclusion of deposition strategy in the efficient model is very important for model accuracy, as deposition strategy plays a critical role in the thermo-mechanical response of the deposited material. The proposed model is developed and implemented in COMSOL Multiphysics. With a cantilever tooling, multiple Stainless Steel 316L (SS 316L) thin wall builds of 50- and 100-layers high is fabricated. Numerical results predicted with the efficient model are successfully compared with experimental data such as thermocouple’s in-situ temperature recordings and Laser Displacement Sensor’s in-situ distortion recordings at the substrate during the fabrication of 50- and 100-layers wall. The efficient model successfully captures the thermo-mechanical response of the sample. It also correctly predicts the effect of the number of layers on the accumulation of distortion during and after the material deposition.

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