Abstract

The post-tensioned concrete I-girder superstructure bridge made by high-performance concrete (HPC) typically exhibits deceptive time-dependent behavior issues with age of concrete. The most common changes are observed deformation, top and bottom fiber stress variation and loss of pre-stress in I-girder due to the secondary effects of shrinkage and creep in concrete. However, in design optimistic expectation of the time-dependent behavior of several post-tensioned concrete I-girder bridges are premature by the existing bridge code, design specification and available prediction models. Nevertheless, about 1–10 years the time-dependent behavior is observed inaccurate in prediction and introduced serviceability and sustainability problems. Consequently, more study is needed toward the time-dependent behavior prediction of the concrete bridges using HPC shrinkage and creep dataset and existing material prediction models. In the present study author’s own an experimentally measured HPC shrinkage and creep database is considered from the literature Gedam et al. 2015 and for same shrinkage and creep are predicted using existing material models such as the American Concrete Institute (ACI), the fib model code 2010 (fib), the Bazant and Bawaja (B3) and the Gardner and Lockman (GL). The results experimentally measured of the shrinkage and creep and predicted by existing material models are incorporated in incremental time-step analysis method to obtain time-dependent behavior results of the simply supported post-tensioned I-girder up to 800 days. Furthermore, outcome long-term behavior results from both an experimental and models are comparatively studied. It has been observed in comparative studies that the existing shrinkage and creep prediction models are not found sophisticated in prediction of the HPC shrinkage and creep properties. Also, it has a probability that in the conventional analysis, design and regional construction, use of any one out of the four existing material models may be produced serviceability and sustainability issues in long-term behavior prediction. In fact, these material models needed re-evaluation and modification, especially local environmental condition and indigenously sourced concrete materials properties.

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