International Journal of Material Forming

, Volume 7, Issue 4, pp 487–501 | Cite as

Numerical assessment of springback for the deep drawing process by level set interpolation using shape manifolds

  • Balaji Raghavan
  • Guenhael Le Quilliec
  • Piotr Breitkopf
  • Alain Rassineux
  • Jean-Marc Roelandt
  • Pierre Villon
Original Research


In this paper, we introduce an original shape representation approach for post-springback characterization based on the automatic generation of parameterized level set functions. The central idea is the concept of the shape manifold representing the design domain in the reduced-order shape-space. Performing Proper Orthogonal Decomposition on the shapes followed by using the Diffuse Approximation allows us to efficiently reduce the problem dimensionality and to interpolate uniquely between admissible input shapes, while also determining the smallest number of parameters needed to characterize the final formed shape. We apply this methodology to the problem of springback assessment for the deep drawing operation of metal sheets.


Shape optimization Springback Level sets Manifold learning Model reduction Forming 


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Copyright information

© Springer-Verlag France 2013

Authors and Affiliations

  • Balaji Raghavan
    • 1
  • Guenhael Le Quilliec
    • 1
  • Piotr Breitkopf
    • 1
  • Alain Rassineux
    • 1
  • Jean-Marc Roelandt
    • 1
  • Pierre Villon
    • 1
  1. 1.Laboratoire Roberval UMR 7337 UTC-CNRSUniversite de Technologie de CompiegneCompiegneFrance

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