RT info:eu-repo/semantics/article
T1 Non-destructive density-corrected estimation of the elastic modulus of slag-cement self-compacting concrete containing recycled aggregate
A1 Revilla Cuesta, Víctor
A1 Shi, Jin-yan
A1 Skaf Revenga, Marta
A1 Ortega López, Vanesa
A1 Manso Villalaín, Juan Manuel
K1 Self-compacting concrete
K1 Recycled aggregate
K1 Ground granulated blast-furnace slag
K1 Aggregate powder
K1 Modulus of elasticity
K1 Non-destructive testing
K1 Ingeniería civil
K1 Civil engineering
K1 Materiales de construcción
K1 Building materials
AB Non-destructive tests that cause no damage to concrete components can be used in rehabilitation works todetermine concrete mechanical properties, such as the modulus of elasticity. In this paper, models are presentedto predict the modulus of elasticity of Self-Compacting Concrete (SCC) with Recycled Aggregate (RA) and slagcement through the hammer rebound index and ultrasonic pulse velocity. Simple- and multiple-regressionmodels were developed to estimate the modulus of elasticity according to the monotonic relation betweenvariables shown by Spearman correlations. In these models, the modulus of elasticity was always inverselyproportional to the square root of the non-destructive property under consideration, and the hardened densityraised to the power of 2.5 as correction factor always increased estimation accuracy and robustness. Themultiple-regression model with density correction yielded the most precise estimations of the elastic moduluswith deviations below ±10% and ±20% in 82% and 94% of cases, respectively.
PB Elsevier
SN 2666-1659
YR 2022
FD 2022-12
LK http://hdl.handle.net/10259/7996
UL http://hdl.handle.net/10259/7996
LA eng
NO This research work was supported by the Spanish Ministry of Universities, MICINN, AEI, EU, ERDF and NextGenerationEU/PRTR [grant numbers PID2020-113837RB-I00; 10.13039/501100011033; TED2021-129715B–I00; FPU17/03374]; the Junta de Castilla y León (Regional Government) and ERDF [grant number UIC-231]; and, finally, the University of Burgos [grant number SUCONS, Y135.GI].
DS Repositorio Institucional de la Universidad de Burgos
RD 23-nov-2024