RT info:eu-repo/semantics/article
T1 Shrinkage prediction of recycled aggregate structural concrete with alternative binders through partial correction coefficients
A1 Revilla Cuesta, Víctor
A1 Evangelista, Luís
A1 Brito, Jorge de
A1 Skaf Revenga, Marta
A1 Manso Villalaín, Juan Manuel
K1 Recycled aggregate structural concrete
K1 Reactive magnesium oxide
K1 Ground granulated blast furnace slag
K1 Shrinkage-prediction model
K1 Partial correction coefficient
K1 Prediction interaction
K1 Materiales de construcción
K1 Building materials
K1 Ingeniería civil
K1 Civil engineering
AB Estimating the shrinkage of structural concrete is essential to calculate, at the design stage, the stresses that astructure may experience due to this phenomenon. Nevertheless, changes in composition, as well as the use ofwastes as raw materials, alter the shrinkage behaviour of concrete and render invalid shrinkage-predictionmodels from the standards. This paper shows a procedure to estimate the shrinkage of recycled aggregateconcrete made with alternative binders. This procedure is based on modifying the shrinkage estimated throughthe Eurocode 2 or ACI 209.2R models by multiplying it by a partial correction coefficient for every change inconcrete composition. The application of this procedure to high-performance and self-compacting concretesmade with various contents of recycled aggregate of different maturity, reactive magnesium oxide and groundgranulated blast furnace slag showed that it is suitable for estimating long-term shrinkage with maximum deviations of ±10%. However, to obtain an adequate accuracy, it is necessary to bear in mind some tips, such as theneed to consider the prediction interactions between the factors, the usefulness of the natural logarithm of theconcrete age to improve the estimation accuracy or the convenience of introducing a concrete-age-dependentcoefficient to reach accurate shrinkage estimations at early ages. Finally, the partial correction coefficients arefound to be of a simpler nature for the ACI 209.2R model, so this model is recommended for predicting theshrinkage of recycled aggregate concrete.
PB Elsevier
SN 0958-9465
YR 2022
FD 2022-05
LK http://hdl.handle.net/10259/7468
UL http://hdl.handle.net/10259/7468
LA eng
NO This work was supported by the Spanish Ministry of Universities, MICINN, AEI, EU and ERDF [grant numbers PID2020-113837RB-I00; 10.13039/501100011033; FPU17/03374; EST19/00263]. Moreover, the authors acknowledge the support of the Junta de Castilla y León [grant number UIC231]; the University of Burgos [grant number Y135. GI]; and the Foundation for Science and Technology, CERIS Research Centre and Instituto Superior Técnico.
DS Repositorio Institucional de la Universidad de Burgos
RD 09-may-2024