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Construction & building materials, 2018-09, Vol.182, p.550-560
2018
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Autor(en) / Beteiligte
Titel
Statistical modelling of the resistance to chloride penetration in concrete with recycled aggregates
Ist Teil von
  • Construction & building materials, 2018-09, Vol.182, p.550-560
Ort / Verlag
Elsevier Ltd
Erscheinungsjahr
2018
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • •Statistical modelling of chloride-penetration in recycled aggregate concrete.•Statistical modelling performed using a multiple linear regression.•A proposed model allows estimating the charge passed in the Rapid Chloride Penetration Test.•A proposed model allows estimating the diffusion coefficient of chlorides.•The influential factors on chloride-penetration in concrete are identified. Steel corrosion is one of the biggest threats to the service life of reinforced concrete structures and chloride penetration favours the corrosion process. Due to sustainability and environmental issues, the use of recycled aggregate in concrete production has been growing. The aim of this study is to develop analytical models that allow predicting the performance of concrete incorporating recycled aggregates regarding chloride penetration. Multiple linear regression analysis was applied to a dataset collated from the literature. The dataset comprised 942 case studies from 33 publications. The analyses allowed identifying the explanatory variables and developing two mathematical models. One of these models is intended to predict the chloride diffusion coefficient from accelerated non-steady state migration tests, while the other predicts the charge transfer in rapid chloride permeability tests. The obtained correlation coefficients and analysis of variance (ANOVA) test results evidence the adequacy of both models. Thus, it is possible to estimate the resistance to chloride penetration in concrete incorporating recycled aggregates through the proposed models.
Sprache
Englisch
Identifikatoren
ISSN: 0950-0618
eISSN: 1879-0526
DOI: 10.1016/j.conbuildmat.2018.06.125
Titel-ID: cdi_gale_infotracmisc_A551963539

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