Steel bridges and structures often need strengthening due to increased live loads, or repair due to corrosion or fatigue cracking. This thesis explores the use of adhesively bonded prestressed carbon fibre reinforced polymers (CFRP) strips in retrofitting intact steel girders, through experimental and analytical investigations. The first part of the research program investigates the behaviour of CFRP-strengthened steel beams comprised of W Structural Sections (W ) with cover plates welded to the tension flange. Six beams, 2000 mm long, were tested under cyclic loads to examine the effects of CFRP strip strengthening on the fatigue life. The CFRP strip prestressing process, type of CFRP strip, level of prestressing, and the location of the CFRP strips were the main parameters examined in this study.
Debonding at the end of strip was a significant problem that can be controlled by applying a proper end clamp. The maximum increase in fatigue life observed in the experiments was 125 percent, for a specimen strengthened using high modulus CFRP strips bonded onto the cover plates with the highest level of prestressing. An analytical model and a finite element model were developed for analyzing the strengthened beams. A fracture mechanic analysis was performed to investigate the effects of prestressing on the crack growth rates at the critical weld toe. The models were verified using experimental results, and then used to perform parametric studies. It is shown that the effectiveness of reinforcement is greatest for beams with strips on the cover plate, higher CFRP elastic modulus, and higher prestressing level.
In general, this study demonstrates that steel beams can indeed be successfully strengthened or repaired using prestressed CFRP materials.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OWTU.10012/5211 |
Date | January 2010 |
Creators | Vatandoost, Farhad |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | Thesis or Dissertation |
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