Fatigue prediction for metallic additively manufactured lattice components using FCM based on average strain energy density approach

An accurate prediction of the fatigue life of metallic additively manufactured lattice structures is still a challenging task. The proposed work addresses this challenge of industrial relevance through the computation of an as-built geometry of a lattice structure directly from its X-ray computed tomography reconstruction. The computation is carried out by taking advantage of the Finite Cell Method and applies the average strain energy density method to predict fatigue failure. The proof of concept provided in this work shows an excellent agreement in the fatigue prediction, paving the way for a computationally accurate fatigue life prediction of other types of metamaterials.

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Published
2024-09-09
DOI
https://doi.org/10.1109/metamaterials62190.2024.10703280
Primary Topic
Additive Manufacturing and 3D Printing Technologies
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article
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article

Fatigue prediction for metallic additively manufactured lattice components using FCM based on average strain energy density approach

Filippo Zanini, Oguz Oztoprak, Filippo Berto, M. Benedetti et al.
Additive Manufacturing and 3D Printing Technologies
article

Fatigue prediction for metallic additively manufactured lattice components using FCM based on average strain energy density approach

Filippo Zanini, Oguz Oztoprak, Filippo Berto, M. Benedetti, Simone Carmignato, Raffaele De Biasi, Stefan Kollmannsberger
article en

Abstract

An accurate prediction of the fatigue life of metallic additively manufactured lattice structures is still a challenging task. The proposed work addresses this challenge of industrial relevance through the computation of an as-built geometry of a lattice structure directly from its X-ray computed tomography reconstruction. The computation is carried out by taking advantage of the Finite Cell Method and applies the average strain energy density method to predict fatigue failure. The proof of concept provided in this work shows an excellent agreement in the fatigue prediction, paving the way for a computationally accurate fatigue life prediction of other types of metamaterials.

University of Padua (IT), University of Trento (IT), Bauhaus-Universität Weimar (DE), Technical University of Munich (DE), Sapienza University of Rome (IT)
Affordable and clean energy
Openalex Percentile: Top 82%
Additive Manufacturing and 3D Printing Technologies
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