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Data · dataset · 2022

Fatigue life prediction of aluminum alloy materials based on surface damage and internal defects

Listed in Teesside University Research Data Repository

The effects of internal defects and surface damage on fatigue life of periodically damaged specimens are analyzed by means of microscopic computed tomography and microscopic observation.

Description

A three-dimensional reconstruction model based on surface damage and internal defects was established, which was confirmed by the experimental data of fatigue damage accumulation during the stages of damage, and a statistical regression model was established by using surface roughness and stress concentration coefficient of the specimens to predict fatigue life.

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Computed tomography 75%
Provenance · 1 source records, 7 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/s733mm3njb.316 h agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:earth-environmentalmapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[modality].local:modality:ctenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (75%)
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