Prediction of the compressive strength of volcanic tuff mineral additive concrete using artificial neural network

CEYLAN H.

Arabian Journal of Geosciences, vol.14, no.21, 2021 (SCI-Expanded, Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 14 Issue: 21
  • Publication Date: 2021
  • Doi Number: 10.1007/s12517-021-08637-4
  • Journal Name: Arabian Journal of Geosciences
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aquatic Science & Fisheries Abstracts (ASFA), Geobase, INSPEC
  • Keywords: Artificial neural network, Cement, CO2 emission, Mineral additive, Volcanic tuff
  • Isparta University of Applied Sciences Affiliated: No

Abstract

In this study, the effect of volcanic tuff mineral additive in concrete manufacture on the compressive strength of concrete was investigated using the artificial neural network (ANN). Cement mixtures were produced by adding volcanic tuff (VT) in the ratio of 0% (control), 10%, 15%, and 20%. The effect of curing time was investigated by applying 28- and 90-day periods. The main inputs for the ANN model were cement, VT, super-plasticizer (SP), and aggregates with 4 different mesh sizes and outputs were 28- and 90-day compressive strengths. In the comparison of obtained results by artificial neural networks with the experimental data, good agreements have been seen. It was also seen that the optimum volcanic tuff rate was 20% in concrete in terms of compressive strengths.