Numerical Simulation of Self-Consolidating Concrete Flow as a Heterogeneous Material in L-Box Set-Up: Effect of Rheological Parameters on Flow Performance
A computational fluid dynamics (CFD) software was used to simulate the effect of rheological parameters on the heterogeneous performance properties of self-consolidating concrete (SCC) in the horizontal and vertical directions of the L-Box set-up. These properties consist of flowability, blocking resistance, and dynamic segregation. Different suspending fluids having five plastic viscosity values (10–50 Pa.s), three yield stress values (14–75 Pa), two fluid densities (2000 and 2500 kg/m3), and two shear elasticity modulus values (100 and 1000 Pa) were considered. The suspensions consisted of a number of 135 in total spherical particles with 20-mm in diameter and 2500 kg/m3 density. The results of 25 simulations in total are found to correlate well with the rheological parameters of the suspending fluid. Plastic viscosity of the suspending fluid was shown to be the most dominant parameter affecting flow performance of SCC in the L-Box test. A new approach was also proposed to classify SCC mixtures based on the filling ability properties.
M. Hosseinpoor et al., "Numerical Simulation of Self-Consolidating Concrete Flow as a Heterogeneous Material in L-Box Set-Up: Effect of Rheological Parameters on Flow Performance," Cement and Concrete Composites, vol. 83, pp. 290 - 307, Elsevier, Oct 2017.
The definitive version is available at https://doi.org/10.1016/j.cemconcomp.2017.07.027
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Compressive strength; Computer simulation; Concretes; Numerical models; Stability; Suspensions (fluids); Viscosity; Yield stress; Blocking resistance; Flowability; Heterogeneous materials; Passing ability; Performance properties; Rheological parameter; Self-consolidating concrete; Spherical particle; Computational fluid dynamics; Dynamic stability; L-Box test; Numerical simulation
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Elsevier, All rights reserved.
01 Oct 2017