Quantification of the resistance modeling uncertainty of 19 alternative 2D nonlinear finite element approaches benchmarked against 101 experiments on reinforced concrete beams

Journal Article (2022)
Author(s)

Arjen de Putter (Witteveen+Bos, Student TU Delft)

MAN Hendriks (Norwegian University of Science and Technology (NTNU), TU Delft - Concrete Structures)

J.G. Rots (TU Delft - Applied Mechanics)

Y Yang (TU Delft - Concrete Structures)

Morten Engen (Norwegian University of Science and Technology (NTNU), Multiconsult Norge AS)

Ab van den Bos (DIANA FEA )

Research Group
Concrete Structures
Copyright
© 2022 Arjen de Putter, M.A.N. Hendriks, J.G. Rots, Y. Yang, Morten Engen, Ab A. van den Bos
DOI related publication
https://doi.org/10.1002/suco.202100574
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Arjen de Putter, M.A.N. Hendriks, J.G. Rots, Y. Yang, Morten Engen, Ab A. van den Bos
Research Group
Concrete Structures
Issue number
5
Volume number
23
Pages (from-to)
2895-2909
Reuse Rights

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Abstract

Nineteen 2D nonlinear finite element analysis (NLFEA) solution strategies were benchmarked against a wide variety of 101 experiments on reinforced concrete beams failing in bending, flexural shear, or shear compression. The relatively high number of solution strategies was motivated by the conviction that choices for the constitutive models, the finite element kinematics and equilibrium settings will interact, and must therefore be tested in conjunction. Modeling uncertainty distribution parameters are presented for the 19 solution strategies, using all beams, and using beams with and without stirrups separately. The resulting statistics are discussed against the correctness of the simulated failure modes and failure loads, revealing that rotating crack models perform well for the relatively ductile failures in beams with stirrups, while fixed crack models perform better for the more brittle failures in beams without stirrups. The tailored solution strategies that predict failure modes correctly, imply a log-normal distribution of the modeling uncertainty with relatively low coefficients of variation. The outlook is that these estimates of the statistical properties of the modeling uncertainties could serve as a basis within safety formats.