Statistical Modeling of Sulfate Resistance and Carbon Footprint for Optimization of Multi-Component Cements

Introduction. Cement production is responsible for approximately 8% of anthropogenic CO₂ emissions, while annual losses from sulfate corrosion account for 2–4% of the global GDP [1]. Studies have confirmed the influence of SiO₂ and additives on the sulfate resistance of multi-component cements (MCCs). However, there is a lack of high-SiO₂ systems, and there is no consensus on the effects of individual additives. The absence of long-term field experiments hinders an empirical solution to this problem. The present study addresses these gaps. The aim of this research is to develop predictive models to substantiate the optimal composition of MCCs based on their sulfate resistance and environmental performance. The tasks include: synthesizing data on MCC compositions, performing ANOVA and regression analysis, and constructing and validating the models.

Materials and Methods. The data sources were thematically structured and analyzed. Experiments were conducted on eight compositions in accordance with patent RU 2079458 C1 and standards GOST 310.1.76 and GOST 310.4.81. The samples were grouped by SiO₂ levels. ANOVA and linear regression were used to model the dependence of sulfate resistance and self-stress on SiO2 content.

Results. The statistical significance of SiO₂ influence on the sulfate resistance and strength of MCCs was proven (F = 248.6795, p = 3.5612e–25). The regression model (Sr = 6.2644 + 0.08 ∙ SiO₂, R² = 0.983) demonstrated a linear dependence of sulfate resistance (ranging from 8.04 to 9.62 conventional units) on SiO₂ content (21–44%). For SiO₂ content > 22%, the addition of pozzolans was recommended to compensate for reduced strength at early stages of hardening. Compressive strength ranged from 35.0 to 44.0 MPa. The reduction of C₃A content to ≤8% enhanced sulfate resistance. The introduction of 50% granulated blast-furnace slag as a binder optimized the cement structure and reduced the carbon footprint by 27.5% (to 388.2 kg CO₂/t). An increase in silica in the composition:

• by 22.15–28% enhanced sulfate resistance by 0.468 units;
• by 37–40% — 6.2644;
• 42% — 9.6244.

Discussion. The model explains 98.3% of the variance in sulfate resistance through changes in silicon dioxide content. The model remains robust with an increased number of observations, as indicated by the adjusted R₂ of 0.981.
The F-statistic indicates the high statistical significance of the model. The normal distribution of residuals and the high precision of the coefficient estimates were confirmed. The limitations on additives in cement specified by GOST 22266-2013 are no longer up to date. This new approach will allow for an increase in cement durability in sulfate environments, a reduction in production costs by 30–50%, and a decrease in CO₂ emissions by 27.5%. It enables the selection of a concrete composition based on either economic or environmental priorities.

Conclusion. SiO₂ content is the key factor in enhancing sulfate resistance. This approach offers a new methodological perspective by overcoming the shortcomings of the GOST standard. Variations in slag composition and the absence of thermal activation may limit the model's reproducibility, necessitating further research.

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