Modeling and predicting chloride diffusion in recycled aggregate concrete
Created by W.Langdon from
gp-bibliography.bib Revision:1.8194
- @Article{YU:2020:CBM,
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author = "Yong Yu and Lang Lin",
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title = "Modeling and predicting chloride diffusion in recycled
aggregate concrete",
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journal = "Construction and Building Materials",
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volume = "264",
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pages = "120620",
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year = "2020",
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ISSN = "0950-0618",
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DOI = "doi:10.1016/j.conbuildmat.2020.120620",
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URL = "http://www.sciencedirect.com/science/article/pii/S0950061820326258",
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keywords = "genetic algorithms, genetic programming, Recycled
aggregate concrete, Chloride diffusion, Mesoscale
modeling, Interfacial transition zones",
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abstract = "Application of recycled aggregate concrete (RAC) in
engineering practice today remains relatively limited.
One of the main reasons may be that the material's
durability has not been comprehensively understood. No
sufficiently accurate formulas are available for
predicting its resistance to chloride infiltration.
This study was therefore designed to investigate the
commonest factors influencing chloride penetration in
RAC using mesoscale finite element models. The
variables of interest were the geometric shape of
coarse aggregate pieces, their location distribution,
the volume content of recycled material, the relative
strength of the old to new mortar, the adhering content
of old mortar, the bonding property of interfacial
transition zones (ITZs) and the mixing method used.
After performing a series of numerical simulations, a
genetic programming (GP) method was lastly adopted to
establish an explicit expression for correlating the
RAC's effective chloride diffusivity with the
identified key factors. Numerical results indicate that
the RAC's diffusion coefficient was negligibly
influenced by the aggregate shape or the old ITZ
property, and commonly grows with increasing
water-to-cement ratio, the amount of old mortar, the
new ITZ's diffusivity as well with the replacing
content of recycled aggregates. Equivalent mortar
volume method can efficiently decrease the material's
chloride diffusivity, especially at low water-to-cement
ratios in the attached mortar. Finally, the expression
provided by the GP method can adequately predict all
these trends and is very convenient for investigating
the RAC's chloride diffusion performance",
- }
Genetic Programming entries for
Yong Yu
Lang Lin
Citations