Prediction of scaling resistance of concrete modified with high-calcium fly ash using classification methods

Marks, M; Marks, M

  • Procedia Computer Science (ICCS 2015);
  • Tom: 51;
  • Strony: 394-403;
  • 2015;

The goal of the study was applying machine learning methods to create rules for prediction of the surface scaling resistance of concrete modified with high-calcium fly ash. To determine the scaling durability the Bor˚as method, according to European Standard procedure (PKNCEN/TS 12390-9:2007), was used. The results of numeral experiments were utilized as a training set to generate rules indicating the relation between material composition and the scaling resistance. The classifier generated by BFT algorithm from the WEKA workbench can be used as a tool for adequate classification of plain concretes and concretes modified with high-calcium fly ash as materials resistant or not resistant to the surface scaling.

Keywords: high calcium fly ash, freeze-thaw resistance, scaling resistance, machine learning, classification, durability prediction