Abstract
In this work we follow a multiscale methodology to characterize the structural performance of post-tensioned steel fiber-reinforced concrete dry joints. At the material level, we use an experimentally validated lattice-particle model whose input parameters are the properties of the different phases themselves (i.e., mortar, aggregates, fibers) and mixing information. This model is used to obtain the mechanical properties used in the structural-level simulations of the joints in terms of constitutive laws. The structural analyses are performed using the concrete damage plasticity model, which allows us to quantify the effect of fiber addition on the shear strength of the dry joints and their ductility. Our simulations agree well with other macroscopic models in the case of plain concrete and show, once again, that the American Association of State Highway Transportation Officials (AASHTO) code overestimates the nominal shear capacity of multiple-keyed joints. Regarding the fiber addition, we observe that it promotes an important increase in the shear capacity, but the prestress level is still more relevant in this sense. Based on our simulations, we propose an updated shear capacity estimate accounting for the fiber volume fraction. Finally, a clear increase in the ductility of the joint is observed when the fiber volume content is increased.
Highlights
Recent computational advances have led to a substantial improvement in numerical modeling of reinforced concrete structures
Its application in large concrete structures is more recent, see for instance references [15,16]. It is within this new scenario that we present an application of multiscale analysis in large concrete structures, namely the numerical evaluation of the shear strength of dry joints between two segments in a post-tensioned concrete box girder
We propose a multiscale methodology based on reference [12], analyzing the effect of fiber volume fraction, as well as prestressing values and number of keys
Summary
Recent computational advances have led to a substantial improvement in numerical modeling of reinforced concrete structures. Its mechanical properties are strongly dependent on microstructural features (e.g., degree of hydration, sieve curve, water to cement ratio), and their influence can be directly observed on the structural performance of concrete elements [5,6] It seems that advanced modeling techniques are useful for understanding the subjacent principles that govern their structural behavior, and improve structural designs [7]. The lowest scale of observation is the so-called mesoscale (i.e., ~1 mm) At this scale, we use the lattice-particle model developed by the authors [12], which accounts for mixing information such as water to cement (w/c) and aggregate to cement (a/c) ratios; sieve curve; fiber size, shape, orientation, and volume content; and mechanical properties such as elastic moduli or tensile strength of the different phases. The material information required at the macroscale can be derived from mesoscale simulations that are completed in terms of input parameters
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