Multi-scale modelling of additively manufactured components

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Problem statement

Powder bed or direct energy deposition based AM techniques require specialized alloy compostions which are not readily available. Inspite of welding and AM techniques having some similarities in the process, most of the weldable alloys compositions are not printable and require changes to its composition[1][2]. It would be ingenious to take experimental route to arrive at a composition that is printable with sufficient end quality. On the other hand, by implementing ICME based models we can narrow down the experimental composition ranges to a large extent. A comprehensive model built complelety based on multi-scale modeling approach can help us chisel each segment of AM process right from chosing the alloy composition to preheating to processing conditions during AM to the nature of heat treatment done on the part after AM to recover strength.

Modeling approach

A concept map that illustrates the suggested model improvement


Residual stress resulting from the temperature field, volumetric expansion due to phase transformations and solidification kinetics contribute to cracking in additive manufacturing. A Transient heat transfer model assuming an elastic-plastic material behavior and its effect on stress accumulation is considered in the macroscale. Latent heat of melting and vaporization are modeled using enthalpy based computations. The element birth technique can be used to simulate the consecutive layer addition and material deposition during additive manufacturing[3].


Meso-scale phase field simulations back-coupled with the macro scale can be used to estimate the volume fraction of liquid remaining in the inter-dendritic region during the final stages of the solidification. Thus a cracking criteria can be developed which maps the process parameters to cracking susceptibility thereby predicting solidification cracking[4].


Temperature gradients and cooling rates passed on from the macro scale is used to determine the microstructure at the solidification front. Diffusion coefficients, thermodynamic and kinectic data are required for the microstructure to evolve from the voronoi tessellations.


With molecular dynamics(MD) simulations at atomic level we can evaluate the diffusion coefficients which is passed on as a input to the micro-scale. By considering a RVE in this scale it is possible to study the dislocation motion based on the burger’s vector and calculate the plastic strain rate which is provided as a input to the macro scale[5].



  1. W. J. Sames, F. A. List, S. Pannala, R. R. Dehoff & S. S. Babu (2016) The metallurgy and processing science of metal additive manufacturing, International Materials Reviews, 61:5, 315-360, DOI: 10.1080/09506608.2015.1116649
  2. T. DebRoy, H.L. Wei, J.S. Zuback, T. Mukherjee , J.W. Elmer, J.O. Milewski, A.M. Beese, A. Wilson-Heid, A. De, W. Zhang "Additive manufacturing of metallic components – Process, structure and properties" Progress in Materials Science 92 (2018) 112–224
  3. T. Mukherjee, W. Zhang, T. DebRoy "An improved prediction of residual stresses and distortion in additive manufacturing" Computational Materials Science 126 (2017) 360–372
  4. M. Rappaz, J.-M. Drezet, and M. Gremaud "A New Hot-Tearing Criterion" METALLURGICAL AND MATERIALS TRANSACTIONS A-Volume-30A (Pg 449-455)
  5. Integrated Computational Materials Engineering (ICME) for metals: Using Multiscale Modeling to Invigorate Engineering Design with Science MARK F. HORSTEMEYER
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