Through-Thickness Residual Stress Profiles in Austenitic Stainless Steel Welds: A Combined Experimental and Prediction Study
- Submitting institution
-
The Open University
- Unit of assessment
- 12 - Engineering
- Output identifier
- 1458237
- Type
- D - Journal article
- DOI
-
10.1007/s11661-017-4359-4
- Title of journal
- Metallurgical and Materials Transactions A
- Article number
- -
- First page
- 6178
- Volume
- 48
- Issue
- 12
- ISSN
- 1073-5623
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- 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
-
5
- Research group(s)
-
-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This study, funded by the nuclear industry, has developed an artificial neural network approach for predicting through-thickness residual stress profiles in pipe girth welds based on a set of training measurements. The work is important because economic and safe management of nuclear plant components relies on accurate prediction of welding-induced residual stresses. The approach shows sufficient potential to be developed into an alternative prediction tool for structural integrity assessment engineers to use in fracture assessments of welded components. Follow-on work has been supported by EDF Energy and has been taken forward within the EU funded ATLAS+ project.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
