Evaluation of axial-torsional low-cycle fatigue tests using Python codes

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dc.contributor.authorNatarajan, Ajay V.
dc.contributor.authorHalama, Radim
dc.contributor.authorKořínek, Michal
dc.contributor.authorGál, Petr
dc.contributor.editorRendl, Jan
dc.date.accessioned2026-04-30T09:42:01Z
dc.date.available2026-04-30T09:42:01Z
dc.date.issued2026
dc.description.abstract-translatedThis paper introduces a suite of Python-based tools for automated post-processing of low-cycle fatigue (LCF) tests under various loading conditions, including uniaxial and axial-torsional. Designed to standardize the FABER project workflow, the tools ensure consistent data validation. A core feature is the '3D method', which uses simultaneous linear regression to determine Manson-Coffin-Basquin (MCB) and Ramberg-Osgood (RO) parameters, avoiding inconsistencies typical of independent regressions. Demonstrated on own experimental datasets, the software automates the calculation of fatigue parameters, generates standardized reports, effectively minimizes human error, and helps with efficient fatigue data analysis and numerical modelling. The data of 42CrMo4+QT steel will serve as the basis of the FABEST competition in the LCF area.en
dc.description.sponsorshipThis work was supported by COST Action CA23109 FABER, supported by COST (https://www.cost.eu/actions/CA23109/) and by the Specific Research Project SP2026/027.en
dc.format2 s.cs
dc.format.mimetypeapplication/pdf
dc.identifier.isbn978-80-261-1352-2
dc.identifier.urihttp://hdl.handle.net/11025/67903
dc.language.isoenen
dc.publisherUniversity of West Bohemia in Pilsenen
dc.rights© University of West Bohemia in Pilsenen
dc.rights.accessopenAccessen
dc.subjectnízkocyklová únavacs
dc.subjectstandardizacecs
dc.subjectcyklická křivka napětí-deformacecs
dc.subjectidentifikace parametrůcs
dc.subject.translatedlow-cycle fatigueen
dc.subject.translatedstandardizationen
dc.subject.translatedcyclic stress-strain curveen
dc.subject.translatedparameter identificationen
dc.titleEvaluation of axial-torsional low-cycle fatigue tests using Python codesen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.type.versionpublishedVersionen
local.files.count2*
local.files.size858155*
local.has.filesyes*

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Proceedings of the 27th International Conference Applied Mechanics 2026
Proceedings of the 27th International Conference Applied Mechanics 2026