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Optimization of concrete by minimizing void volume in aggregate mixture system
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0002-6790-2653
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0002-1365-8552
2012 (English)In: Journal of Advanced Science and Engineering Research, ISSN 2231-8844, Vol. 2, no 3, 208-222 p.Article in journal (Refereed) Published
Abstract [en]

The behavior of concrete is affected by the size, distribution of the voids, the porosity and of the granulometry of the aggregate mixture. As a consequence it necessary for engineers to consider in detail particle packing concepts and their influence on the physical performance of concrete. The present study included determination of the fineness modulus, cement paste volume based on slump test and the properties of fresh and hardened concrete. It also comprised a study of the applicability of two theoretical models Toufar’s and 4C-packing program for selecting suitable relative amounts of the concrete constituents, for obtaining a minimum void ratio. Comparison of the results was made from using these theoretical models literature-derived experimental data. The models gave similar results and suggest similar combinations of materials to give minimum void ratio. Optimization of the composition of the aggregate material in concrete is beneficial with respect to economy (low cement content), strength and durability. It was noted that minimizing the void ratio (V) tends to raise the stiffness and that the compressive strength (푓푐′) is closely related also to their molding (R) and fineness modules (FM). It was found that the compressive strength can be predicted by applying the formula;푓푐′=−2.1−63.8 푉+0.150 푅+10.4 퐹푀; R2=0.94, and two other relationships related to slump data and cement content.

Place, publisher, year, edition, pages
2012. Vol. 2, no 3, 208-222 p.
National Category
Geotechnical Engineering
Research subject
Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-10554Local ID: 960db0df-a96e-4ed2-9f43-2202422ae24cOAI: oai:DiVA.org:ltu-10554DiVA: diva2:983499
Note
Validerad; 2012; 20120830 (nadhir)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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