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A platform for research: civil engineering, architecture and urbanism
Highlights Mesoscale simulation is an effective way to study RAC’s chloride diffusion responses. RAC’s penetration resistance is largely affected by relative strength of old to new mortar. The old ITZ’s property and the shape of aggregates affect RAC’s diffusivity slightly. A GP method-based formulas is proposed for predicting RAC’s diffusion coefficient.
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.
Highlights Mesoscale simulation is an effective way to study RAC’s chloride diffusion responses. RAC’s penetration resistance is largely affected by relative strength of old to new mortar. The old ITZ’s property and the shape of aggregates affect RAC’s diffusivity slightly. A GP method-based formulas is proposed for predicting RAC’s diffusion coefficient.
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.
Modeling and predicting chloride diffusion in recycled aggregate concrete
2020-08-14
Article (Journal)
Electronic Resource
English
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