Probabilistic Calibration for Shear Strength Models of Reinforced Concrete Columns
Publication: Journal of Structural Engineering
Volume 145, Issue 5
Abstract
A probabilistic calibration method is proposed for evaluating the accuracy and applicability of available deterministic models for the shear strength of shear-critical reinforced concrete (RC) columns. Shear mechanisms of RC columns were explored and a deterministic model for shear strength was developed based on the variable angle truss-arch model. Subsequently, a probabilistic shear strength model involving both aleatory and epistemic uncertainties was proposed based on the Bayesian theory and the Markov Chain Monte Carlo (MCMC) method. Meanwhile, the probabilistic characteristics of shear strength were determined according to the developed probabilistic shear strength model. Finally, a probabilistic calibration method was developed to evaluate the accuracy and applicability of available shear strength models under different conditions of the compressive strength of concrete, the transverse reinforcement ratio, the axial load ratio, the aspect ratio, and displacement ductility.
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Acknowledgments
The financial support received from the National Natural Science Foundation of China (Grant Nos. 51668008 and 51738004) is gratefully acknowledged. Use of the WinBUGS software is also acknowledged.
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Published In
Journal of Structural Engineering
Volume 145 • Issue 5 • May 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: May 10, 2018
Accepted: Oct 18, 2018
Published online: Feb 26, 2019
Published in print: May 1, 2019
Discussion open until: Jul 26, 2019
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