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Investigating the generalizability of machine learning methods for predicting the fatigue strength of butt joints in the context of rare observations

Beiler, Marten and Braun, Moritz (2023) Investigating the generalizability of machine learning methods for predicting the fatigue strength of butt joints in the context of rare observations. Master's, Technische Universität Hamburg.

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Item URL in elib:https://elib.dlr.de/212945/
Document Type:Thesis (Master's)
Title:Investigating the generalizability of machine learning methods for predicting the fatigue strength of butt joints in the context of rare observations
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Beiler, Martenmarten.beiler (at) dlr.deUNSPECIFIEDUNSPECIFIED
Braun, Moritzmoritz.braun (at) dlr.dehttps://orcid.org/0000-0001-9266-1698UNSPECIFIED
Date:2023
Open Access:No
Status:Published
Keywords:machine learning methods, fatigue strength predictions, butt joints, generalizability of machine learning
Institution:Technische Universität Hamburg
Department:Institute for Ship Structural Design and Analysis
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:other
DLR - Research area:Transport
DLR - Program:V - no assignment
DLR - Research theme (Project):V - no assignment
Location: Geesthacht
Institutes and Institutions:Institute of Maritime Energy Systems
Deposited By: Schwickardi, Marike
Deposited On:25 Feb 2025 08:39
Last Modified:25 Feb 2025 08:39

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