Nonlinear analysis of load-deflection testing of reinforced one-way slab strengthened by carbon fiber reinforced polymer (CFRP) and using artificial neural network (ANN) for prediction

• Main Authors: Far, M.R.H., Jumaat, Mohd Zamin, Vahid Razavi T., S., Mohammadi, P., Mohammadi, H.
• Format: Article
• Language: English
• Published: International Journal of Physical Sciences 2011
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/5987/1/Nonlinear_analysis_of_load-deflection_testing_of_reinforced_one-way_slab_strengthened_by_carbon_fiber_reinforced_polymer_%28CFRP%29_and_using_artificial_neural_network_%28ANN%29_for_prediction.pdf; http://eprints.um.edu.my/5987/; http://www.scopus.com/inward/record.url?eid=2-s2.0-79960866995&partnerID=40&md5=f6558dd00b68f216853648866202b5f7
• Institution: Universiti Malaya

Load-deflection curve is the most important part of the structural analysis of RC beam and slab. The load-deflection analysis of the RC one-way slab strengthened by CFRP using experimental work, finite element analysis (FEA), artificial neural network (ANN), and a comparison of them together are the important objective of this study. The dimension of the one-way slab was 1800�400�120 mm which was strengthened by different length and width of carbon fiber reinforced polymer (CFRP). The experimental results sufficiently adapted with FEA and ANNs output. The feed forward back-propagation (FFB) was the best ANN for prediction of load-deflection curve with minimum error below 1, and maximum correlation coefficient close to 1.