Published on: 2026-09-29
Source: Saint Petersburg State University of Architecture and Civil Engineering –
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Device for determining the stretchability of the mixture
A mathematical model has been developed at the Saint Petersburg State University of Architecture and Civil Engineering that allows forecasting the plasticity of cement paste and more accurately selecting the properties of construction mixtures for additive manufacturing.
The study was conducted by an associate professor of the Department of Building Materials Technology and Metrology, Candidate of Technical Sciences Georgy Khrenov under the scientific supervision of Doctor of Technical Sciences, Professor, Corresponding Member of the Russian Academy of Architecture and Construction Sciences Yuri Pukharenko.
The work is aimed at solving one of the key challenges of construction 3D printing – obtaining a mixture with specified plasticity characteristics.
In additive manufacturing, the material must simultaneously retain the ability to deform during application and ensure the stability of the formed layer. Until now, the selection of the composition of such mixtures has largely been based on experimental search. The mathematical model developed at SPbGASU allows this process to be based on a more precise scientific foundation.
The model links the ultimate elongation of the cement paste to its water-to-cement ratio (W/C), as well as to the viscosity and surface tension of the liquid phase. This allows evaluating how changes in the mixture composition affect its deformability, and predicting the material’s behavior before conducting a large number of practical tests.
To verify theoretical dependencies, SPbGASU developed a special device and methodology for determining the extensibility of finely dispersed construction mixtures. During the experiment, a thin layer of the mixture is applied to a silicone sheet, which is then evenly stretched until the first cracks appear. This approach allows for determining the ultimate extensibility of the material and comparing the experimental data with calculations based on the mathematical model.
The conducted tests showed a high convergence of theoretical dependencies with the results of experiments. This confirms the possibility of using the developed model to predict the behavior of construction mixtures.
The obtained results create a foundation for targeted control of the plasticity of materials used in construction 3D printing. In the future, this approach may contribute to more precise selection of mixture compositions and improved stability of the additive manufacturing process.
The study was conducted as part of the 2026 Saint Petersburg State University of Architecture and Civil Engineering scientific and pedagogical staff grant competition.
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