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The selection of structural and insulation concrete based on granulated foam glass with the use of mathematical planning of the experiment

Abstract

The selection of structural and insulation concrete based on granulated foam glass with the use of mathematical planning of the experiment

Sopegin G.V., Semeynykh N.S.

Incoming article date: 27.06.2019

The factors that must be taken in the selection of lightweight concrete composition with the use of granulated foam glass (GFG-concrete). In addition, the effect of the composition of concrete mixture on the physical, mechanical and thermal properties of the obtained material is shown. Portland cement CEM II / A-S-32,5 B, produced by PAO «Gornozavodskcement», was used as a binder when selecting the composition of GFG-concrete; quartz sand of the Zaostrovsky opencast mine of Perm with a particle size module of 1.96 was used as fine aggregate; granulated foam glass of fractional composition of 5-10 and 10-20 mm was used as a coarse aggregate. Determination of physical, mechanical and thermal properties of GFG-concrete was carried out according to standard methods. The obtained mathematical models allowed us to establish a functional relationship between technological factors of variation (content of granulated foam glass and water-cement ratio) and output optimization parameters (average density and compressive strength). The highest compressive strength (9,0-10,93 MPa) of HPS-concrete was obtained with a content of coarse aggregate of 20-40% and a water-cement ratio of 0,4-0,6. The average density does not exceed 1500 kg / m3, and thermal conductivity varies from 0,207 to 0,375 W/m⸱K. The optimal composition is the content of GFG from 20 to 40% and water-cement ratio of 0,4-0,6. Research have also shown that by changing technological factors, it is possible to obtain GFG-concrete with a density class D500-D1500.

Keywords: water-cement ratio, granulated foam glass, lightweight concrete, mathematical experiment planning, response surface, compressive strength, average density, regression equation