Wide-ranging Probabilistic Physics-guided Machine Learning Approach to Break Down the Limits of Current Fatigue Predictive Tools for Metals

Project Information

BREAKDOWN

Grant agreement ID: 101162848

DOI

10.3030/101162848

EC signature date 31 October 2024

Start date 1 December 2024

End date 30 November 2029

Funded under

• European Research Council (ERC)

Total cost

€ 1 499 954,00

EU contribution

€ 1 499 954,00

Coordinated by

UNIVERSITA DEGLI STUDI DI UDINE
Italy

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Peer reviewed articles (2)

Resolving the fundamentals of the J-integral concept by multi-method in situ nanoscale stress-strain mapping

Author(s): Michael Meindlhumer; Markus Alfreider; Noel Sheshi; Anton Hohenwarter; Juraj Todt; Martin Rosenthal; Manfred Burghammer; Enrico Salvati; Jozef Keckes; Daniel Kiener
Published in: Communications Materials, 2025, ISSN 2662-4443
Publisher: Nature
DOI: 10.1038/S43246-025-00752-Z

Materials Science & Engineering A: Structural Materials: Properties, Microstructure and Processing

Author(s): Marco Pelegatti; Enrico Salvati; Nicolò Grilli
Published in: Materials Science and Engineering: A, 2025, ISSN 0921-5093
Publisher: Elsevier BV
DOI: 10.2139/SSRN.5379080