Inverse computation of local fiber orientation using digital image correlation and differentiable finite element computations

  • Injection molding and compression molding are cost-effective processes for manufacturing discontinuous fiber reinforced polymer composite parts with complex geometries. The resulting properties of such parts depend on local fiber orientations, and we propose a novel approach to determine the orientation field as solution to an inverse problem: Given the deformation field of a part measured via digital image correlation (DIC), we determine the local orientations leading to that deformation. We model the structural deformation of the part with a differentiable finite element solver and mean field homogenization. Subsequently, we compute the error to the DIC measurement and minimize that error with respect to the input orientations. The gradients for optimization of the finite element model are computed efficiently using automatic differentiation with PyTorch through the entire model. The method is validated and discussed for carbon fiber sheet molding compounds under tensile loading butInjection molding and compression molding are cost-effective processes for manufacturing discontinuous fiber reinforced polymer composite parts with complex geometries. The resulting properties of such parts depend on local fiber orientations, and we propose a novel approach to determine the orientation field as solution to an inverse problem: Given the deformation field of a part measured via digital image correlation (DIC), we determine the local orientations leading to that deformation. We model the structural deformation of the part with a differentiable finite element solver and mean field homogenization. Subsequently, we compute the error to the DIC measurement and minimize that error with respect to the input orientations. The gradients for optimization of the finite element model are computed efficiently using automatic differentiation with PyTorch through the entire model. The method is validated and discussed for carbon fiber sheet molding compounds under tensile loading but can be extended to arbitrary parts with defined load cases and available DIC data.show moreshow less

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Metadaten
Author:Nils MeyerORCiDGND, Stefan Panzer
URN:urn:nbn:de:bvb:384-opus4-1146345
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/114634
ISBN:978-2-912985-01-9OPAC
Parent Title (English):Proceedings of the 21st European Conference on Composite Materials (ECCM21), 2-5 July 2024, Nantes, France, volume 8
Publisher:The European Society for Composite Materials (ESCM) and the Ecole Centrale de Nantes
Place of publication:Nantes
Editor:Christophe Binetruy, Frédéric Jacquemin
Type:Conference Proceeding
Language:English
Year of first Publication:2024
Publishing Institution:Universität Augsburg
Contributing Corporation:Blackwave GmbH
Release Date:2024/08/02
Tag:Injection Molding; Compression Molding; Differentiable Simulation
First Page:397
Last Page:404
DOI:https://doi.org/10.60691/yj56-np80
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Materials Resource Management / Juniorprofessur für Data-driven Product Engineering and Design
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 62 Ingenieurwissenschaften / 620 Ingenieurwissenschaften und zugeordnete Tätigkeiten
Licence (German):CC-BY-NC 4.0: Creative Commons: Namensnennung - Nicht kommerziell (mit Print on Demand)