Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (4/4 displayed)

  • 2022Conventional Meso-Scale and Time-Efficient Sub-Track-Scale Thermomechanical Model for Directed Energy Deposition5citations
  • 2022Conventional Meso-Scale and Time-Efficient Sub-Track-Scale Thermomechanical Model for Directed Energy Deposition5citations
  • 2022Numerical modeling for large-scale parts fabricated by Directed Energy Deposition2citations
  • 2021Development of an Elongated Ellipsoid Heat Source Model to Reduce Computation Time for Directed Energy Deposition Process17citations

Places of action

Chart of shared publication
Boisselier, Didier
2 / 8 shared
Carin, Muriel
2 / 21 shared
Engel, Thierry
2 / 3 shared
Chart of publication period
2022
2021

Co-Authors (by relevance)

  • Boisselier, Didier
  • Carin, Muriel
  • Engel, Thierry
OrganizationsLocationPeople

document

Numerical modeling for large-scale parts fabricated by Directed Energy Deposition

  • Boisselier, Didier
  • Carin, Muriel
  • Engel, Thierry
  • Nain, Vaibhav
Abstract

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.

Topics
  • Deposition
  • impedance spectroscopy
  • stainless steel
  • inclusion
  • simulation
  • directed energy deposition
  • powder bed fusion