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A robust methodology for dataset preparation and algorithm performance assessment in machine learning prediction of the fatigue life of additive manufactured components

Crossref DOI link: https://doi.org/10.1007/s00366-025-02139-7

Published Online: 2025-04-18

Published Print: 2025-10

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Di Maggio, Luigi Gianpio

Gastaldi, Chiara

Renzo, Danilo Antonello

Delprete, Cristiana

Furgiuele, Franco
Funding

Funding for this research was provided by:

ICSC – Italian Research Center on High Performance Computing, Big Data and Quantum Computing, funded by the European Union – NextGenerationEU.

Politecnico di Torino
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Text and Data Mining valid from 2025-04-18

Version of Record valid from 2025-04-18
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Article History

Received: 2 July 2024

Accepted: 25 March 2025

First Online: 18 April 2025

Declarations

:

: No potential conflict of interest is reported by the authors when submitting the work.

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