Probabilistic Shear Strength Model of Reinforced Concrete Exterior Beam-Column Joints
Publication: Journal of Structural Engineering
Volume 149, Issue 5
Abstract
A major disadvantage of the existing joint shear strength models is that they cannot consider the shear-resistance mechanisms and various uncertainties comprehensively. In order to overcome this limitation, a probabilistic shear strength model of reinforced concrete (RC) exterior beam-column joints was proposed. A simplified deterministic shear strength model for RC exterior beam-column joints was derived first by considering the contributions of the diagonal strut mechanism and truss mechanism. Then the probabilistic shear strength model for RC exterior beam-column joints was developed by taking into account both aleatory and epistemic uncertainties. Furthermore, the posterior distributions of probabilistic model parameters were updated by means of the Bayesian theory and the Markov chain Monte Carlo method. Finally, the proposed model was verified by comparison with 135 sets of experimental data and existing shear strength models. The results show that the proposed model has satisfactory prediction accuracy and low dispersion, which not only calibrates the influencing parameters on the prediction accuracy of the existing models, but also provides a probabilistic method to calibrate the confidence interval of the existing models.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The financial support received from the National Natural Science Foundation of China (Grant Nos. 52278162, 62266005, and 51738004), the Guangxi Science Fund for Distinguished Young Scholars (2019GXNSFFA245004), and the Innovation Project of Guangxi Graduate Education (YCBZ2022011) is gratefully acknowledged.
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Published In
Journal of Structural Engineering
Volume 149 • Issue 5 • May 2023
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Jul 9, 2022
Accepted: Dec 29, 2022
Published online: Feb 25, 2023
Published in print: May 1, 2023
Discussion open until: Jul 25, 2023
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