2012
DOI: 10.1016/j.conbuildmat.2012.04.121
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Probabilistic models for mechanical properties of prestressing strands

Abstract: This study focus on the probabilistic modelling of mechanical properties of prestressing strands based on data collected from tensile tests carried out in Laboratório Nacional de Engenharia Civil (LNEC), Portugal, for certification purposes, and covers a period of about 9 years of production. The strands studied were produced by 6 manufacturers from 4 countries, namely Portugal, Spain, Italy and Thailand. Variability of the most important mechanical properties is examined and the results are compared with the … Show more

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Cited by 18 publications
(7 citation statements)
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“…deriving from an imperfect initial knowledge [16]) and represented by random variables following appropriate statistical distributions. Several studies provide statistical distributions derived from statistical analysis for parameters affecting the probabilistic structural assessment of existing bridges [8,17,18].…”
Section: Modelling Uncertaintiesmentioning
confidence: 99%
“…deriving from an imperfect initial knowledge [16]) and represented by random variables following appropriate statistical distributions. Several studies provide statistical distributions derived from statistical analysis for parameters affecting the probabilistic structural assessment of existing bridges [8,17,18].…”
Section: Modelling Uncertaintiesmentioning
confidence: 99%
“…In the definition of the distribution types and coefficients of variation (COV) for each variable, available bibliography was considered. 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.…”
Section: Probabilistic Modelsmentioning
confidence: 99%
“…Additionally, the corrosion variables include the surface chloride concentration, C s , threshold chloride concentration, C th , chloride diffusion coefficient, D cl , concrete cover, c, corrosion rate, i c and corrosion model error, γ ic . Table 1 summarises the models and values for each variable [2,4,5,19,[49][50][51][52][53]. It should be mentioned that other material properties not mentioned in the table below, such as the compressive strength of concrete, cm , are considered deterministic with their average design value since they were shown in a previous study not to be significant for the reliability analyses [54].…”
Section: Random Variablesmentioning
confidence: 99%