The paper deals with the effectiveness of various types of polymers (naphthalene formaldehyde, polycarboxylate, and lignosulfonate) as superplasticizers of concrete mixtures based on low-clinker slag Portland cement. Using the mathematical planning experimental method and statistical models of water demand of concrete mixtures with polymer superplasticizers, as well as concrete strength at different ages and under different curing conditions (normal curing and after steaming) were obtained. According to the models, the superplasticizer’s water-reducing effect and relative change in concrete strength were obtained. The proposed criterion for evaluating the effectiveness and compatibility of superplasticizers with cement takes into account the water-reducing effect of the superplasticizer and the corresponding relative change in concrete strength. The results demonstrate that the use of the investigated superplasticizer types and low-clinker slag Portland cement allows for achieving a significant increase in concrete strength. The effective contents of various polymer types, which allow the achieving of concrete strengths from 50 MPa to 80 Mpa, has been found.

This article presents experimental studies that have shown the effectiveness of using a composition of fly ash and metakaolin as an active mineral admixture to cement. It is shown that composite ash–metakaolin additives (AMAd) have on the one hand increased pozzolanic activity and surface energy, and, on the other hand, moderated water demand and provided a significant increase in strength, which is especially important for low-cement concretes. The obtained experimental–statistical models make it possible to determine the effect of the AMAd composition, its content in combination with the addition of a superplasticizer on the rheological properties, the kinetics of structure formation and the main physical and mechanical properties of cement.

This paper presents experimental results on the influence of concrete composition factors on the criterion characterizing the ratio between the compressive strength of activated low-cement concrete and clinker consumption. The investigation was carried out using mathematical planning of the experiments. Experimental and statistical models describing the influence of the fly ash, activating additive (microsilica), consumption of cement and aggregates, as well as the superplasticizer on the strength of low-cement concrete under normal hardening conditions and after steaming were obtained. The values of the clinker efficiency criterion and the mineral additive cementing efficiency coefficient were calculated, and models of these parameters were obtained for the investigated concrete compositions. It was shown that the activating effect of microsilica yields an increase in ash cementing efficiency and clinker efficiency criterion in concrete. Using the obtained models, an example for calculating the ash cementing efficiency coefficient is given.

The paper deals with composition design of self-compacting concrete containing blast furnace granulated slag and polycarboxylate type superplasticizer in a wide range of concrete strength classes. Optimal superplasticizer content, cement, and blast furnace slag consumptions are obtained from the viewpoint of minimum water demand and water-cement ratio, maximum self-compacting concrete mixture workability retention, and concrete strength. A significant effect of joint influence of superplasticizer and blast furnace slag is demonstrated. The possibility of minimizing the cement consumption at optimal superplasticizer content and slag consumption of 100120kg/m³ is shown. Dependences for calculating SCC strength at 1, 7, and 28days vs. the water-cement ratio are obtained. It is found that the nature of correlation dependences for SCC splitting and compression strengths when using the blast furnace slag and the superplasticizer is linear. Optimization of SCC compositions using mathematical programming enables to obtain compositions with a lowest possible cost while providing a set of specified parameters.