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Shear Strength Prediction of Reinforced Concrete Beams Using Truss Analogy Approach

  • 2025
  • OriginalPaper
  • Chapter
Published in:
Authors
Sherine Stanly
Madappa V. R. Sivasubramanian
Shamsher Bahadur Singh
Published in
Proceedings of the 3rd International Conference on Advances in Concrete, Structural, and Geotechnical Engineering—Volume 2
Publisher
Springer Nature Singapore

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Abstract

This chapter introduces a cohesive analytical model for predicting the shear strength of reinforced concrete beams using the truss analogy approach. The model integrates plasticity theory to enhance accuracy and has been validated against experimental data from various beam specimens with differing shear span to depth ratios. Key topics include the assumptions considered in the analytical formulation, the step-by-step analytical approach, and the validation of the model through experimental data. The results demonstrate a high level of agreement between the analytical predictions and experimental findings, suggesting that the model effectively predicts the shear contribution in reinforced concrete beams. The chapter also provides detailed insights into the behavior of reinforced concrete beams under shear loads, making it a valuable resource for professionals seeking to understand and predict shear strength in structural design.
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previous chapter Seismic Stability Analysis of a Bamboo Grid Reinforced Slope Based on Non-linear Time History Analysis
next chapter Stress Assessment in Post-tensioned Concrete Anchorage Using a 3-Strand Anchorage Plate
Title
Shear Strength Prediction of Reinforced Concrete Beams Using Truss Analogy Approach
Authors
Sherine Stanly
Madappa V. R. Sivasubramanian
Shamsher Bahadur Singh
Copyright Year
2025
Publisher
Springer Nature Singapore
Book
Proceedings of the 3rd International Conference on Advances in Concrete, Structural, and Geotechnical Engineering—Volume 2

Print ISBN: 978-981-9607-50-1

Electronic ISBN: 978-981-9607-51-8

Copyright Year: 2025

DOI
https://doi.org/10.1007/978-981-96-0751-8_33
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