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A NEW STATISTICAL MODEL FOR THE ESTIMATION OF AUTOCLAVE EXPANSION OF PORTLAND CEMENT
This paper presents the predictive functional control of an autoclave expansion of Portland cement, using non-linear regression equation. This is in order to save time and expense also for quality control assurance for produced cement (in cement factories). The autoclave expansion test (ASTM C151- 05) is one of the internationally used tests in detecting the unsoundness of Portland cement. The factors affecting test results were reviewed. A statistical analysis was built and based on 50 different cement samples taken from 8 different Iraqi cement factories. Thirty three of the samples were ordinary Portland cement while the other seventeen samples were sulfate resisting Portland cement. The model examines different variables such as; chemical composition (phase composition and oxides percentages), and physical properties such as fineness. Regression analysis was performed to establish a mathematical formula. According to the analysis the model provide good estimation of autoclave expansion and yielded good correlations with the data used in this study. It was found that the multiple linear regressions are very suitable for predicting the autoclave expansion of Portland cement. Study results indicate that the correlation coefficient may reach 0.9797, indicating that the proposed method has referential value. The model was tested with collected new raw data and the predictions were highly correlation to the experimental results (R2=0.9535).
A NEW STATISTICAL MODEL FOR THE ESTIMATION OF AUTOCLAVE EXPANSION OF PORTLAND CEMENT
This paper presents the predictive functional control of an autoclave expansion of Portland cement, using non-linear regression equation. This is in order to save time and expense also for quality control assurance for produced cement (in cement factories). The autoclave expansion test (ASTM C151- 05) is one of the internationally used tests in detecting the unsoundness of Portland cement. The factors affecting test results were reviewed. A statistical analysis was built and based on 50 different cement samples taken from 8 different Iraqi cement factories. Thirty three of the samples were ordinary Portland cement while the other seventeen samples were sulfate resisting Portland cement. The model examines different variables such as; chemical composition (phase composition and oxides percentages), and physical properties such as fineness. Regression analysis was performed to establish a mathematical formula. According to the analysis the model provide good estimation of autoclave expansion and yielded good correlations with the data used in this study. It was found that the multiple linear regressions are very suitable for predicting the autoclave expansion of Portland cement. Study results indicate that the correlation coefficient may reach 0.9797, indicating that the proposed method has referential value. The model was tested with collected new raw data and the predictions were highly correlation to the experimental results (R2=0.9535).
A NEW STATISTICAL MODEL FOR THE ESTIMATION OF AUTOCLAVE EXPANSION OF PORTLAND CEMENT
Kadhum, Mohammed Mansour (author)
2014-02-28
doi:10.19044/esj.2014.v10n5p%p
European Scientific Journal, ESJ; Vol 10 No 5 (2014): ESJ February Edition ; Revista Científica Europea; Vol. 10 Núm. 5 (2014): ESJ February Edition ; 1857-7431 ; 1857-7881
Article (Journal)
Electronic Resource
English
Fly ash portland cement for autoclave concrete
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