Shear strength code models uncertainties assessment based on probabilistic simulation

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Date
2025-09-05
Authors
Novák, Drahomír
Večeře, Jakub
Sadílková Šomodíková, Martina
Kotynia, Renata
Advisor
Referee
Mark
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Publisher
Wiley
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Abstract
In the paper, a shear strength probabilistic assessment of concrete members with steel reinforcement is performed. The shear strength is analyzed by modelling with lowfidelity models – analytical formulas based on two main approaches to predict the shear strength of reinforced concrete beams with and without shear reinforcement: the modified compression field theory and the truss model. Based on a comparison of these lowfidelity analytical models and experimental data, model uncertainties can be evaluated. The aim of the analysis performed is to verify the existing code analytical formulas for shear strength calculation using stochastic models, to perform uncertainty propagation, sensitivity analysis and model uncertainty assessment. The code models of EN 199211, ACI 318 and fib Model Code 2010 are examined with respect to uncertainties involved and the reliability of the design value determination.
In the paper, a shear strength probabilistic assessment of concrete members with steel reinforcement is performed. The shear strength is analyzed by modelling with lowfidelity models – analytical formulas based on two main approaches to predict the shear strength of reinforced concrete beams with and without shear reinforcement: the modified compression field theory and the truss model. Based on a comparison of these lowfidelity analytical models and experimental data, model uncertainties can be evaluated. The aim of the analysis performed is to verify the existing code analytical formulas for shear strength calculation using stochastic models, to perform uncertainty propagation, sensitivity analysis and model uncertainty assessment. The code models of EN 199211, ACI 318 and fib Model Code 2010 are examined with respect to uncertainties involved and the reliability of the design value determination.
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Peer-reviewed
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en
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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
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