Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Prediction of Portland cement strength using statistical methods
The Portland cement strength is the most important mechanical property that should be tested for quality control. Because 28 days represents a very long period for the cement industry, a faster determination of the cement strength represents a favorable research objective of the recent research in the cement industry. In the present work, a mathematical model for the prediction of cement strength is developed based on a standard specifications for Portland cement: chemical-mineralogical synthesis of the cement (% C3S, % C2S, % C3A, % C4AF), fineness by air permeability apparatus, lime saturation factor (LSF), particle size distribution, position parameter, and uniform factor. The strength values predicted were validated with consistently high accuracy, based on a linear regression of selected physical and chemical characteristics routinely obtained in the cement laboratory. The maximum errors were 4.54 %, 2.66 %, and 4.86 % at 3, 7, and 28 days, respectively. The proposed model provides the opportunity to predict the compressive strength in a very short time and this will save cost and make a competitive advantage in the Portland Cement production market.
Prediction of Portland cement strength using statistical methods
The Portland cement strength is the most important mechanical property that should be tested for quality control. Because 28 days represents a very long period for the cement industry, a faster determination of the cement strength represents a favorable research objective of the recent research in the cement industry. In the present work, a mathematical model for the prediction of cement strength is developed based on a standard specifications for Portland cement: chemical-mineralogical synthesis of the cement (% C3S, % C2S, % C3A, % C4AF), fineness by air permeability apparatus, lime saturation factor (LSF), particle size distribution, position parameter, and uniform factor. The strength values predicted were validated with consistently high accuracy, based on a linear regression of selected physical and chemical characteristics routinely obtained in the cement laboratory. The maximum errors were 4.54 %, 2.66 %, and 4.86 % at 3, 7, and 28 days, respectively. The proposed model provides the opportunity to predict the compressive strength in a very short time and this will save cost and make a competitive advantage in the Portland Cement production market.
Prediction of Portland cement strength using statistical methods
Garcia-Casillas, P.E. (Autor:in) / Martinez, C.A. (Autor:in) / Camacho Montes, H. (Autor:in) / Garcia-Luna, A. (Autor:in)
Materials and Manufacturing Processes ; 22 ; 333-336
2007
4 Seiten, 3 Bilder, 2 Tabellen, 7 Quellen
Aufsatz (Zeitschrift)
Englisch
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