Artificial neural network for random fatigue loading analysis including the effect of mean stress
- Submitting institution
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Oxford Brookes University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 185750721
- Type
- D - Journal article
- DOI
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10.1016/j.ijfatigue.2018.02.007
- Title of journal
- International Journal of Fatigue
- Article number
- -
- First page
- 321
- Volume
- 111
- Issue
- -
- ISSN
- 0142-1123
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2018
- URL
-
-
- Supplementary information
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- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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3
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The novelty of the work lies in the use of artificial neural network (ANN) approach as a new viable spectral based method including the effect of mean stress for predicting fatigue damage with greater resolution than other available methods. The materials considered in this work were metallic alloys. Since its publication in 2018 the work has been cited well (impact on the state of the art related to deep machine learning), received a recommendation and its Research Interest is higher than 72% of research items on ResearchGate.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -