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Title: Load Testing of a Deteriorated Prestressed Concrete Girder Bridge without Plans

Author(s): Sebastian Castellanos-Toro

Publication: Web Session

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Issue:

Appears on pages(s):

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DOI:

Date: 10/17/2021

Abstract:
In this study, a prestressed girder bridge without plans and severe levels of deterioration, located in Cali, Colombia, was load-tested to quantify, experimentally, its live-load behavior. The bridge consists of seven prestressed I-girders covered with a reinforced concrete deck slab and four diaphragm beams. A geometric survey was performed to obtain the dimensions for a shell-based linear finite-element model (LFEM) representing the bridge superstructure and an initial basic finite-element analysis of deformations and modal properties. In this survey, it was observed that the diaphragm beams in the span are geometrically inadequate to contribute to the structural system. Based on the experimental modal properties and the design regulations in force at the time of bridge design and construction a first update was made. Modifying the effective stiffness of some elements to model the girder's deterioration, a second update was performed based on strain gauges information from three load tests and visual inspection (VI) of the elements. The three models (basic, modal updated, and load-test/VI updated) were compared with the distribution load factor (LDF) obtained from the load test and AASHTO distribution factors estimations. Visual inspection, dynamic characterization, and load testing response of this structure indicated some severely deteriorated girder stems and null effect of transverse beams. The results show that AASHTO recommendations overestimate the LDF in comparison with the LFEM without girder’s deterioration. When the girder’s deterioration is included in the model, the LDFs change drastically showing that AASHTO estimations are not in line with the experimental results. As such, for cases of bridges with severe levels of deterioration, it is recommended to use field data to estimate the distribution factors.