2018
DOI: 10.1002/suco.201700169
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Uncertainty in shear resistance models of reinforced concrete beams according to fib MC2010

Abstract: Load bearing capacity can be predicted by appropriate modeling of material properties, geometry variables, and uncertainties associated with an applied model for the failure mechanism under consideration. The submitted study investigates shear resistance model uncertainties for reinforced concrete beams with and without shear reinforcement, considering large test databases and various levels of approximation offered by fib Model Code 2010. Model uncertainty is treated as a random variable and its characteristi… Show more

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Cited by 33 publications
(21 citation statements)
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“…The correlation and regression analysis ( Table 4) reveals that MF MC − 10(III) has a strong decreasing trend with the member depth d (r = − 0.41), evident in Figure 5d and Table 5c. This trend was also identified by other researchers 15,18,21,22,38 (This implies that the MC-10 (III) formulation does not adequately account for the size effect on shear resistance. The risk of insufficient reliability for beams with large depth should be investigated.…”
Section: Discussion Of Mf Statistical Results and Trendssupporting
confidence: 56%
See 1 more Smart Citation
“…The correlation and regression analysis ( Table 4) reveals that MF MC − 10(III) has a strong decreasing trend with the member depth d (r = − 0.41), evident in Figure 5d and Table 5c. This trend was also identified by other researchers 15,18,21,22,38 (This implies that the MC-10 (III) formulation does not adequately account for the size effect on shear resistance. The risk of insufficient reliability for beams with large depth should be investigated.…”
Section: Discussion Of Mf Statistical Results and Trendssupporting
confidence: 56%
“…Model factors may be statistically characterized by a probability distribution function with corresponding mean value and variance. In accordance with the MF x associated with a single experiment, x , is calculated from the ratio of the experimentally observed capacity to the best estimate predictions of the analytical model under consideration. 0.25emMFx=VExp,xVModel,x()X …”
Section: Assessment Of Model Uncertainty and Biasmentioning
confidence: 99%
“…The results in Figures and and in Tables and should be seen against the backdrop of monotonic test‐to‐model comparisons by Sigrist et al and Sykora et al: LoA II and III were found by Sigrist et al to provide median test‐to‐prediction ratios in 243 rectangular or T‐beams with stirrups (79 of which had axial force, normally due to prestress) equal to 1.34 and 1.195, respectively, and corresponding coefficients of variation of 17 and 13%. In Sykora et al 459 beams gave median test‐to‐prediction ratios of 1.58 and 1.125 for LoA II and III, respectively, and corresponding coefficients of variation of 25 and 23%. …”
Section: The Three Levels Of Approximation In Mc2010 and The Ec2‐2018mentioning
confidence: 74%
“…• Of the beneficial contribution of the axial load, outlined in Section 3 • Of the reduction in shear resistance due to cycling of the load, see Section 5.2. Tables 3 and 4 should be seen against the backdrop of monotonic test-tomodel comparisons by Sigrist et al 15 and Sykora et al 16 :…”
Section: Introductionmentioning
confidence: 98%
“…This clearly shows that if filter is not applied COV increases because of diverse shear behavior, for a given a v / d , exhibited by beams in unfiltered database. This is also true for higher order moments like skewness and kurtosis which gets significantly affected by filtering criteria (see Figure ) as pointed out by Sykora et al In the study conducted by Sykora et al, the aim was to address the biases and scatters in the predictions using fib shear capacity equation. Therefore, distribution of shear capacity was not discussed and was considered as an open area of research.…”
Section: Modeling Errormentioning
confidence: 92%