Probabilistic-based characterisation of the mechanical properties of CFRP laminates

Gomes, S.; Dias-da-Costa, D.; Neves, Luís; Hadigheh, S. Ali; Fernandes, Paulo; Júlio, Eduardo

doi:10.1016/j.conbuildmat.2018.02.190

Cited by 19 publications

(10 citation statements)

References 26 publications

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“…Recently, the parameter uncertainties in the bond resistance of CFRP–concrete composite specimens, such as concrete compressive strength, concrete modulus, FRP strength, FRP modulus, and FRP thickness, have been explored and found to fit Normal, Lognormal, Weibull, or Gamma distribution [ 24 , 32 , 34 , 36 ]. However, few studies have been conducted on the type of statistical distribution that best fits G f .…”

Section: Discussion Of Fracture Energy G F mentioning

confidence: 99%

Reliability Analysis of Bond Behaviour of CFRP–Concrete Interface under Wet–Dry Cycles

Liang

et al. 2018

Materials

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Effective bonding between adherents plays a key role in retrofitting concrete structures in civil engineering using fibre-reinforced polymers (FRPs). To ensure structural safety, it is critical to develop design codes, which account for uncertainties of materials, the environment, and load, to estimate bond behaviour under long-term exposure to harsh environments. Therefore, a reliability analysis was performed to study the bond behaviour of FRP–concrete interface under wet–dry cycles and sustained loading. Thirty double-lap, shear-bonded carbon FRP (CFRP)–concrete composite specimens were tested after wet–dry cycles and sustained loading exposure. The fracture energy Gf of the bond behavior between CFRP and concrete was directly obtained from the measured local bond-slip curves. Five widely used test methods were adopted to verify the possible distribution types of Gf. Based on the best fit distribution of Gf, a reliability index β was then calculated for the specimens. The effects of wet–dry exposure and sustained loading on β were analysed separately. The effects of the mean and standard deviation of the load on β were compared. It was found that the mean had a greater impact on reliability than the standard deviation, but neither changed the regulation of the exponential reduction of β with increasing wet–dry cycle time. Their impact was significant for a small number of wet–dry cycles but insignificant for more than 4000 wet–dry cycles.

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Section: Discussion Of Fracture Energy G F mentioning

confidence: 99%

Reliability Analysis of Bond Behaviour of CFRP–Concrete Interface under Wet–Dry Cycles

Liang

et al. 2018

Materials

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“…The steel strand strength model was selected based on the study from Jacinto et al (2012). The CFRP laminates strength model was defined after a probabilistic study by Gomes et al (2018), where the Weibull distribution was shown to be accurate for probabilistic analyses. The dead loads corresponding to the weight of sidewalks, guard rails and asphalt are considered uniformly distributed over the girder, following a normal distribution with a COV of 0.10 (von Scholten and Vejdirektoratet 2004).…”

Section: Probabilistic Modelsmentioning

confidence: 99%

Partial Safety Factors for Prestressed Concrete Girders Strengthened with CFRP Laminates

et al. 2020

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This paper provides a framework for the calibration of partial safety factors in prestressed concrete (PC) girders strengthened in flexure with carbon fibre-reinforced polymer (CFRP) laminates. A hybrid approach was proposed to take advantage of comprehensive non-linear numerical models in reliability analysis using a first order reliability method (FORM) in conjunction to the response surface method (RSM). The PC girders selected for analyses were taken from real structures designed and built since the 1980s, based on old standards, now requiring strengthening and upgrade due to partial corrosion of prestressing strands. Using the proposed approach, a sensitivity analysis was performed to identify the most relevant variables and assess the area of CFRP laminates needed to restore the capacity to new design standards. Following this study, a partial safety factor was proposed for strengthening PC girders using CFRP laminates. A sensitivity analysis also showed the traffic loads and model uncertainties to be the most important variables for calibration.

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“…Although a normal distribution is assumed in current guidelines for the characterization of FRP’s tensile properties, many studies have revealed that a Weibull distribution is more appropriate as the describing model, especially for the tensile strength [24,25,26,27]. Zureick et al compared the normal, log-normal, and Weibull distribution based on more than 600 samples, and recommended the Weibull distribution for the characterization of FRP’s tensile strength and tensile modulus [24].…”

Section: Introductionmentioning

confidence: 99%

“…The same research team also studied the two-parameter and three-parameter Weibull distribution, and recommended the two-parameter model after taking into account the fitting goodness and the computational efficiency [28]. Gomes et al conducted tensile tests on 1368 coupon samples [27]. It is confirmed that an overall good fit can be achieved by any of the normal, log-normal, or Weibull distribution.…”

Section: Introductionmentioning

confidence: 99%

“…It is symmetric and therefore is not suitable for the characterization of many engineering properties which show skewness to some extent. So far, the Weibull distribution has been adopted in the Composite Materials Handbook-MIL [32] and used by many researchers for the design strength (the 5th percentile value) analysis of FRP composites [24,27,33,34]. Nevertheless, limited efforts have been devoted to the sample size analysis using a normal distribution for mean value assessment.…”

Section: Introductionmentioning

confidence: 99%

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Sample Sizes Based on Weibull Distribution and Normal Distribution for FRP Tensile Coupon Test

Yang

Tang

et al. 2019

Materials

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Current guidelines stipulate a sample size of five for a tensile coupon test of fiber reinforced polymer (FRP) composites based on the assumption of a normal distribution and a sample coefficient of variation (COV) of 0.058. Increasing studies have validated that a Weibull distribution is more appropriate in characterizing the tensile properties of FRP. However, few efforts have been devoted to sample size evaluation based on a Weibull distribution. It is not clear if the Weibull distribution will result in a more conservative sample size value. In addition, the COV of FRP’s properties can vary from 5% to 15% in practice. In this study, the sample size based on a two-parameter Weibull distribution is compared with that based on a normal distribution. It is revealed that the Weibull distribution results in almost the same sample size as the normal distribution, which means that the sample size based on a normal distribution is applicable. For coupons with COVs varying from 0.05 to 0.20, the sample sizes range from less than 10 to more than 60. The use of only five coupons will lead to a prediction error of material property between 6.2% and 24.8% for COVs varying from 0.05 to 0.20.

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Probabilistic-based characterisation of the mechanical properties of CFRP laminates

Cited by 19 publications

References 26 publications

Reliability Analysis of Bond Behaviour of CFRP–Concrete Interface under Wet–Dry Cycles

Reliability Analysis of Bond Behaviour of CFRP–Concrete Interface under Wet–Dry Cycles

Partial Safety Factors for Prestressed Concrete Girders Strengthened with CFRP Laminates

Sample Sizes Based on Weibull Distribution and Normal Distribution for FRP Tensile Coupon Test

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