Combined shear and flexure performance of prestressing concrete T-shaped beams: Experiment and deterministic modeling

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Abstract

The development of a nonlinear numerical computational model for the detailed description of destructive tests generally requires a multiple-stage, strategic model updating procedure. In this contribution, a model updating procedure is applied to the simulation of prestressed reinforced concrete (RC) beams. The combined ultimate shear and flexure capacity of the beams is affected by many complex phenomena, such as the multi-axial state of stress, the anisotropy induced by diagonal concrete cracking, the interaction between concrete and reinforcement (bond), and the brittleness of the failure mode. In this research, a series of material, small-scale component fracture tests were carried out by two collaborating laboratories. These tests provided advanced statistical identification of the fracture-mechanical parameters of the optimized concrete mixtures for the prestressed laboratory-tested beams mentioned above (with a span of 5.00 m) and associated field-tested, long-span concrete TT roof elements (with a span of 30.00 m). Ten scaled laboratory-tested beams with heights of 0.30, 0.45, and 0.60 m were used in a procedure for the comprehensive updating of the nonlinear numerical model with respect to shear resistance performance. The objectives of this research are, in addition to the analysis, the effective development of an updating process for nonlinear numerical modeling which is based on the information from different monitoring systems. Hence, this contribution focuses on the presentation of a comprehensive updating procedure for the shear capacity of nonlinear numerical models of prestressed beam elements using information about fracture-mechanical material parameters gained from (a) different monitoring systems and (b) code-based methods.

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Strauss, A., Krug, B., Slowik, O., & Novak, D. (2018). Combined shear and flexure performance of prestressing concrete T-shaped beams: Experiment and deterministic modeling. Structural Concrete, 19(1), 16–35. https://doi.org/10.1002/suco.201700079

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