Research of Thermodynamics of Portland Cement Curing using Data Mining Technology

Yu. A. TashkinovDonbas National Academy of Civil Engineering and ArchitectureV. N. SklonchakDonbas National Academy of Civil Engineering and ArchitectureI. S. AksenovDonbas National Academy of Civil Engineering and Architecture
Abstract: The technology for predicting heat release during hardening of Portland cement in the Statistica 6.0 software package is considered. Empirical data were collected (using the Internet as a source, because the transition to a remote training format) on the amount of heat generated during curing of thirteen samples with different ratios of tricalcium aluminate, tricalcium silicate, tetracalcium aluminoferrite, dicalcium silicate. A multiple linear regression analysis of the experimental material was carried out. The linear equation is obtained: Q = 52,57735+1,46831·m(3CaO·Al2O3)+0,66225·m(3CaO·SiO2), which allows calculating the amount of heat released from the initial empirical information on the ratio of the components of Portland cement. A statistical verification of the results was carried out using the normality of the residues. The experimental data are compared with those predicted in the regression equation. The conclusion is drawn about the effectiveness of Data Mining technologies in the activities of a technologist for the production of building materials.

Keywords: Big Data, Data Mining, production of building materials, chemical thermodynamics, thermodynamic computer modeling.

Pages: 16-20.

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For citation:
For citation: Tashkinov, Yu. A.; Sklonchak, V. N.; Aksenov, I. S. Research of Thermodynamics of Portland Cement Curing using Data Mining Technology. – Text : electronic. – In: <em>Proceeding of the Donbas National Academy of Civil Engineering and Architecture</em>. – 2020. – Issue 2020-4(144) Scientific and technical achievements of students of the construction and architectural industry. – Р. 16-20. – URL: https://donnasa.ru/publish_house/journals/vestnik/2020/2020-4(144)/st_03_taschkinov_sklonchak_aksenov.pdf (date of access: 22.12.2024). – ISSN 2519-2817.


Issue Cover
Issue 2020-4 (144)
Journal: Proceeding of the Donbas National Academy of Civil Engineering and Architecture
Publish house: Donbas National Academy of Civil Engineering and Architecture