Journal of Advanced Informatics in Water, Soil, and Structure

Journal of Advanced Informatics in Water, Soil, and Structure

Prediction of Compressive Strength of Fly Ash-based Geopolymer Concrete Using Artificial Neural Network Model

Document Type : Research Article

Authors
Ehsan Mohsennia
Vahab Toufigh
Department of Civil Engineering, Sharif University of Technology, Tehran, Iran.
10.22048/wss.2024.432893.1006
Abstract
Geopolymer concrete is an environmentally friendly alternative to traditional concrete, using waste materials as a cementitious material. One of the main challenges in using geopolymer concrete in the construction industry is the lack of a standard mixing design. This study presents a neural network model for predicting the compressive strength of fly ash-based geopolymer concrete. To achieve this goal, 162 architectures reported in articles published between 2000 and 2020 were collected. In this study, ten input variables (such as the water-to-solid ratio of fly ash, sodium hydroxide, and sodium silicate solution, the total ratio of sodium hydroxide and sodium silicate solution to fly ash) and one output variable (i.e. compressive strength of fly ash-based geopolymer concrete) were used. The best-presented model had R2, RMSE (MPa), MAPE (%), and MAE (MPa) indices of 0.828, 3.56 MPa, 7.74%, and 2.91 MPa, respectively, for the test data, which indicates acceptable accuracy. Finally, by comparing this model with previous studies, the proposed model showed that it can estimate the compressive strength of fly ash-based geopolymer concrete with acceptable accuracy, which can save time and money.
Keywords
Keywords: Geopolymer concrete
Fly ash
Machine learning
Artificial neural network (ANN)
Compressive strength

Subjects

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Journal of Advanced Informatics in Water, Soil, and Structure
Volume 1, Issue 1 - Serial Number 1
January 2025
Pages 98-114

  • Receive Date 28 December 2023
  • Revise Date 12 June 2024
  • Accept Date 13 June 2024
  • First Publish Date 01 January 2025
  • Publish Date 01 January 2025