A manifold learning-based reduced order model for springback shape characterization and optimization in sheet metal forming

DOI10.1016/j.cma.2014.11.029zbMath1423.74780OpenAlexW2039588464MaRDI QIDQ1798588

Piotr Breitkopf, Balaji Raghavan, Guénhaël Le Quilliec

Publication date: 23 October 2018

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cma.2014.11.029

zbMATH Keywords

proper orthogonal decompositioncharacterizationlevel setmodel reductionshape optimizationspringbackEulerianmanifold learning

Mathematics Subject Classification ID

Finite element methods applied to problems in solid mechanics (74S05) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Mesh generation, refinement, and adaptive methods for boundary value problems involving PDEs (65N50) Computer-aided design (modeling of curves and surfaces) (65D17) Geometrical methods for optimization problems in solid mechanics (74P20)

Related Items (4)

Identification of material properties using indentation test and shape manifold learning approach ⋮ Nonlinear shape-manifold learning approach: concepts, tools and applications ⋮ Data-driven streamline stiffener path optimization (SSPO) for sparse stiffener layout design of non-uniform curved grid-stiffened composite (NCGC) structures ⋮ A kernel method for learning constitutive relation in data-driven computational elasticity

Uses Software

• Gmsh
• LS-DYNA

Cites Work

• A priori hyperreduction method: an adaptive approach
• An extended level set method for shape and topology optimization
• Generalizing the finite element method: Diffuse approximation and diffuse elements
• Simulation of springback
• Principal component analysis.
• Nonlinear manifold learning for model reduction in finite elastodynamics
• Towards simultaneous reduction of both input and output spaces for interactive simulation-based structural design
• Meshless methods with application to metal forming
• Implicit constraint handling for shape optimisation with POD-morphing
• A bi-value coding parameterization scheme for the discrete optimal orientation design of the composite laminate
• Nonlinear manifold learning for meshfree finite deformation thin-shell analysis
• Proper generalized decomposition of multiscale models
• Calibration of POD reduced‐order models using Tikhonov regularization
• Gmsh: A 3-D finite element mesh generator with built-in pre- and post-processing facilities
• Reduced-order modeling of parameterized PDEs using time-space-parameter principal component analysis
• An Algorithm for Finding Intrinsic Dimensionality of Data
• Shape optimization of two‐phase inelastic material with microstructure
• Unnamed Item

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