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Computational Modelling Strategies for Nonlinear Response Prediction of Corroded Circular RC Bridge Piers
- Source :
- Kashani, M M, Lowes, L N, Crewe, A J & Alexander, N A 2016, ' Computational Modelling Strategies for Nonlinear Response Prediction of Corroded Circular RC Bridge Piers ', Advances in Materials Science and Engineering, vol. 2016, 2738265 . https://doi.org/10.1155/2016/2738265, Advances in Materials Science and Engineering, Vol 2016 (2016)
- Publication Year :
- 2016
-
Abstract
- A numerical model is presented that enables simulation of the nonlinear flexural response of corroded reinforced concrete (RC) components. The model employs a force-based nonlinear fibre beam-column element. A new phenomenological uniaxial material model for corroded reinforcing steel is used. This model accounts for the impact of corrosion on buckling strength, postbuckling behaviour, and low-cycle fatigue degradation of vertical reinforcement under cyclic loading. The basic material model is validated through comparison of simulated and observed responses for uncorroded RC columns. The model is used to explore the impact of corrosion on the inelastic response of corroded RC columns.
- Subjects :
- Pier
Materials science
Article Subject
0211 other engineering and technologies
020101 civil engineering
Fibre model
02 engineering and technology
0201 civil engineering
Corrosion
Flexural strength
021105 building & construction
lcsh:TA401-492
Cyclic loading
General Materials Science
Reinforcement
RC bridge pier
business.industry
General Engineering
Structural engineering
Low-cycle fatigue
Inelastic buckling
Rc columns
Nonlinear system
Buckling
Reinforcing steel
Cyclic behaviour
lcsh:Materials of engineering and construction. Mechanics of materials
business
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Kashani, M M, Lowes, L N, Crewe, A J & Alexander, N A 2016, ' Computational Modelling Strategies for Nonlinear Response Prediction of Corroded Circular RC Bridge Piers ', Advances in Materials Science and Engineering, vol. 2016, 2738265 . https://doi.org/10.1155/2016/2738265, Advances in Materials Science and Engineering, Vol 2016 (2016)
- Accession number :
- edsair.doi.dedup.....c82a5186808534e4c52a414a30590364