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An FFT-based homogenization scheme for cohesive zones with an application to adhesives and the core material of thin metal sandwich plates
University of Applied Sciences Mittelhessen, Germany.
University of Applied Sciences Mittelhessen, Germany.
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Engineering and Physics (from 2013).ORCID iD: 0000-0001-8335-0855
Lamera AB, Sweden; Research Institutes of Sweden, Sweden.
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2024 (English)In: Theoretical and applied fracture mechanics (Print), ISSN 0167-8442, E-ISSN 1872-7638, Vol. 129, article id 104186Article in journal (Refereed) Published
Abstract [en]

Cohesive Zone Models with finite thickness are widely used for the fracture mechanical modeling of material layers, e.g., adhesive layers. Within this approach, the whole layer is modeled as a cohesive zone. Moreover, computational homogenization techniques are crucial for the development of advanced engineering materials, which are often heterogeneous. Compared to the commonly used Finite Element Method (FEM), solvers based on the Fast Fourier Transform (FFT) are expected to reduce the computational effort needed for the homogenization. Originated from an existing method for the computational homogenization of cohesive zones using FEM, a novel FFT-based homogenization scheme for cohesive zone models is presented. Our implementation of the FFT solver uses a displacement-based Barzilai–Borwein scheme and a non-local ductile damage model for the fracture behavior. Finally, the practical application of the method is discussed using an adhesive layer and the core material of HybrixTM metal sandwich plates as examples. 

Place, publisher, year, edition, pages
Elsevier, 2024. Vol. 129, article id 104186
Keywords [en]
Computational homogenization, Cohesive Zone Modeling, HybrixTM metal sandwich plates, FFT-based homogenization, Non-local damage, Adhesive layer
National Category
Applied Mechanics
Research subject
Materials Science; Materials Engineering; Mechanical Engineering
Identifiers
URN: urn:nbn:se:kau:diva-97647DOI: 10.1016/j.tafmec.2023.104186ISI: 001124401000001Scopus ID: 2-s2.0-85177618840OAI: oai:DiVA.org:kau-97647DiVA, id: diva2:1816636
Funder
Vinnova, 2019-02063Available from: 2023-12-04 Created: 2023-12-04 Last updated: 2024-01-03Bibliographically approved

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Biel, Anders

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