Probabilistic Studies on the Shear Strength of Slender Steel Fiber Reinforced Concrete Structures

Abstract

Shear failure is a brittle and undesirable mode of failure in reinforced concrete structures. Many of the existing shear design equations for steel fiber reinforced concrete (SFRC) beams include significant uncertainty due to the failure in accurately predicting the true shear capacity. Given these, adequate quantification and description of model uncertainties considering the systematic variation in the model prediction and measured shear capacity is crucial for reliability-based investigation. Reliability analysis must account for model uncertainties in order to predict the probability of failure under prescribed limit states. This study focuses on the quantification and description of model uncertainty related to the current shear resistance predictive models for SFRC beams without shear reinforcement. The German (DAfStB) model displayed the lowest bias and dispersion, whereas the fib Model 2010 and the Bernat et al., model displayed the highest bias and dispersion. The inconsistencies observed in the resistance model uncertainties at the variation of shear span to effective depth ratio are a major cause for concern, and differentiation with respect to this parameter is advised. Finally, in line with the EN 1990 semi-probabilistic approach for reliability-based design, the global partial safety factors related to model uncertainties in the shear resistance prediction of SFRC beams are proposed.

Shear capacity prediction of slender reinforced concrete structures with steel fibers using machine learning

“…The derived model uncertainty statistics and related partial safety factors are associated with the specific database considered in this study, which may change noticeably should the database change. The use of partial factors ensures a consistent level of reliability over a range of structures [73]. • Trend analysis was conducted to discern any trend/bias in the performance of the various models concerning their input variables.…”

Quantification of Model Uncertainty Based on Variance and Entropy of Bernoulli Distribution

“…The importance of model uncertainties has been confirmed in numerous studies. Model uncertainties in the shear resistance of reinforced concrete beams were studied in [35,36]. The statistical analysis of model uncertainties was evaluated in [37] by comparing the resistance data from experiments and models of reinforced concrete members.…”