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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.
Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), Institutionen för ingenjörsvetenskap och fysik (from 2013).ORCID-id: 0000-0001-8335-0855
Lamera AB, Sweden; Research Institutes of Sweden, Sweden.
Vise andre og tillknytning
2024 (engelsk)Inngår i: Theoretical and applied fracture mechanics (Print), ISSN 0167-8442, E-ISSN 1872-7638, Vol. 129, artikkel-id 104186Artikkel i tidsskrift (Fagfellevurdert) 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. 

sted, utgiver, år, opplag, sider
Elsevier, 2024. Vol. 129, artikkel-id 104186
Emneord [en]
Computational homogenization, Cohesive Zone Modeling, HybrixTM metal sandwich plates, FFT-based homogenization, Non-local damage, Adhesive layer
HSV kategori
Forskningsprogram
Materialvetenskap; Materialteknik; Maskinteknik
Identifikatorer
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
Forskningsfinansiär
Vinnova, 2019-02063Tilgjengelig fra: 2023-12-04 Laget: 2023-12-04 Sist oppdatert: 2024-01-03bibliografisk kontrollert

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