An EPR-based self-learning approach to material modelling
- Submitting institution
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The University of West London
- Unit of assessment
- 12 - Engineering
- Output identifier
- 12053
- Type
- D - Journal article
- DOI
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10.1016/j.compstruc.2013.06.012
- Title of journal
- Computers & Structures
- Article number
- -
- First page
- 63
- Volume
- 137
- Issue
- -
- ISSN
- 0045-7949
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- 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
-
-
- Research group(s)
-
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- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research presents a revolutionary idea in numerical modelling and inverse-analysis. This work resulted in collaboration with University of Exeter through a PhD project on development of advanced autonomous self-learning finite element method to characterise materials with complex behaviour and joint research work with Queen’s University on condition assessment of buried pipelines. This paper has been used as scientific support for EPSRC project EP/P010415 and an interdisciplinary innovate-UK/EPSRC project EP/R043574 on condition assessment of underground utilities. The developed tool in this work is generic with application in condition assessment of infrastructure hence has a significant and far-reaching global impact.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
