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[118070] Artykuł:

Intermediate Crack Debonding of Externally Bonded FRP Reinforcement—Comparison of Methods

Czasopismo: Materials   Tom: 15, Zeszyt: 20, Strony: 1-19
ISSN:  1996-1944
Opublikowano: Pażdziernik 2022
 
  Autorzy / Redaktorzy / Twórcy
Imię i nazwisko Wydział Katedra Do oświadczenia
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Paweł Tworzewski orcid logo WBiAKatedra Wytrzymałości Materiałów, Konstrukcji Betonowych i Mostowych *****Takzaliczony do "N"Inżynieria lądowa, geodezja i transport50140.00140.00  
Jeffrey Alexy Niespoza "N" jednostki025.00.00  
Robert Barnes Niespoza "N" jednostki025.00.00  

Grupa MNiSW:  Publikacja w czasopismach wymienionych w wykazie ministra MNiSzW (część A)
Punkty MNiSW: 140


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Abstract:

Many researchers around the world have made extensive efforts to study the phenomenon of fiber-reinforced polymer (FRP) debonding. Based on these efforts, code provisions and various models have been proposed for predicting intermediate crack (IC) debonding failure. The paper presents a comparison of seven selected models: fib bulletin 14 approach, Teng et al. model, Lu model, Seracino et al. model, Said and Wu model, Elsanadedy et al. model and ACI 440. The accuracy of each model was evaluated based on the test results of 58 flexural specimens with IC debonding failures of externally bonded (EB), carbon FRP plates or sheets found in the existing literature. The experimental database was prepared to include a wide range of parameters affecting the issue under consideration. A comparison of the measured and predicted load capacity values was made to evaluate the prediction accuracy of the considered models. The analysis included the limitation of the load capacity estimated based on IC debonding models as well as concrete crushing and FRP rupture types of failure. The results indicate that the latest models proposed for direct implementation in design guidelines—the Said and Wu model and the Elsanadedy et al. model—offer the best accuracy in predicting the load capacity. In contrast, the fib bulletin 14 approach shows a wide dispersion of predictions and a large proportion of highly overestimated results.