Towards simultaneous meta-modeling for both the output and input spaces in the context of design shape optimization using asynchronous high-performance computing

Balaji Raghavan (1, 2) , Piotr Breitkopf (2) , Pierre Villon (2)

1 LGCGM - Laboratoire de Génie Civil et Génie Mécanique
2 Roberval - Roberval

. In this paper, we propose a simultaneous meta-modeling protocol for both input and output spaces. We perform a reparametrization of the input space using constrained shape interpolation by introducing the concept of an α-manifold of admissible meshed shapes. The output space is reduced using constrained Proper Orthogonal Decomposition. By simultaneously using meta-modeling for both spaces, we facilitate interactive design space exploration for the purpose of design. The proposed approach is applied to several industrial problems.

Mots clés: manifold learning; design; reduced order model; optimization; high performance computing

Domaines: Analyse numérique [math.NA]; Mécanique [physics]; Sciences de l'ingénieur [physics]

Balaji Raghavan, Piotr Breitkopf, Pierre Villon. Towards simultaneous meta-modeling for both the output and input spaces in the context of design shape optimization using asynchronous high-performance computing. 2nd ECCOMAS Young Investigators Conference (YIC 2013), Sep 2013, Bordeaux, France. ⟨hal-00855842⟩