Concrete bridges in Texas have developed large cracks in bent caps and pretensioned trapezoidal bridge girders. The bridges show premature concrete deterioration due to alkali-silica reaction (ASR) and delayed ettringite formation (DEF). There is concern that deterioration due to ASR/DEF may lead to a loss of structural capacity. However, there are no quantitative guidelines to relate the level of concrete deterioration due to ASR/DEF to structural performance. Using such guidelines, the need for rehabilitation of beams with ASR/DEF cracking can be assessed.
The goal of this research was to determine the shear capacity of pretensioned trapezoidal box girder specimens exhibiting varying degrees of ASR and/or DEF cracking and to use the shear testing results to evaluate the severity of the problem that may exist in Texas bridge structures. To achieve this goal, beams that were severely deteriorated due to ASR/DEF over a period of more than ten years were transported to the University of Texas for testing to failure. Both severely deteriorated and uncracked beams were tested in shear. The test results were used to evaluate the shear performance of trapezoidal box beams affected by ASR/DEF. In addition, three different types of forensic analyses were conducted on the beams to understand the nature of the ASR/DEF cracks and severity of the deterioration.
After testing, it is found that the shear capacity of the test specimens was not significantly reduced even with heavy ASR/DEF cracking. Assessment using current US design provisions for bridges or buildings (ACI 318-08 and AASHTO LRFD 2008) and the proposed provision from an earlier project (TxDOT Project 5253) yielded conservative estimates of strength. Results from forensic analyses provided a qualitative indication of ASR/DEF damage but did not correlate with the observed levels of ASR/DEF deterioration. / text
Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/ETD-UT-2010-08-1637 |
Date | 09 November 2010 |
Creators | Wang, Tz-Wei |
Source Sets | University of Texas |
Language | English |
Detected Language | English |
Type | thesis |
Format | application/pdf |
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