Title of article
INFLUENCE OF FIBER ASPECT RATIO ON SHEAR CAPACITY OF DEEP BEAMS USING ARTIFICIAL NEURAL NETWORK TECHNIQUE
Author/Authors
naik, u. savitribai phule pune university (s.p. pune university) - k.k. wagh institute of engineering and research centre - department of civil engineering, India , kute, s. savitribai phule pune university (s.p. pune university) - k.k. wagh institute of engineering and research centre - department of civil engineering, India
From page
81
To page
91
Abstract
This paper deals with the effect of fiber aspect ratio of steel fibers on shear strength of steel fiber reinforced concrete deep beams loaded with shear span to depth ratio less than two using the artificial neural network technique. The network model predicts reasonably good results when compared with the equation proposed by previous researchers. The parametric study involves deep beams of M55 grade concrete with fiber volume fraction 0.5% to 2% of fiber aspect ratio ranging from 50 to 100 and longitudinal steel percentage varying from 0% to 2.5%. The analysis reveals that the fiber aspect ratio also affects the shear strength and needs to be combined with fiber volume fraction.
Keywords
fiber aspect ratio , steel fibre reinforced concrete , volume fraction , deep beam , shear span , neural network
Journal title
International Journal of Optimization in Civil Engineering
Journal title
International Journal of Optimization in Civil Engineering
Record number
2566692
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