Compressive stress–strain model for the estimation of the flexural capacity of reinforced geopolymer concrete members


Structural Concrete, vol.24, no.4, pp.5102-5121, 2023 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 24 Issue: 4
  • Publication Date: 2023
  • Doi Number: 10.1002/suco.202200914
  • Journal Name: Structural Concrete
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Page Numbers: pp.5102-5121
  • Keywords: flexural capacity, geopolymer concrete, load estimation, low carbon, stress–strain model
  • Hacettepe University Affiliated: Yes


Global warming triggered efforts on sustainable materials in any area of production. Thus, the construction materials were also at the edge of a sharp change to achieve less harm to the environment by reducing the carbon print. Consequently, researchers have been trying to replace the cement from the mixtures of reinforced concrete as cement production causes large amounts of carbon dioxide emissions. Alkali-activated binders are proved to be versatile alternatives to cementitious binders; however, accurate mathematical models to predict the capacities of these structural elements are limited in number. Therefore, in this study, a new stress–strain model has been developed to estimate the flexural capacity of geopolymer structural elements originated from construction and demolition waste. The study was initiated by formulating a novel stress–strain model applicable for defining the compressive behavior of geopolymer concrete. The formulation was based on recent experimental findings on flexural behavior of geopolymer beam specimens. Then, the performance of the proposed stress–strain model in estimating the ultimate moment capacities was investigated by using 36 bending tests from the literature. The results showed that the proposed model had very little deviations and enhanced accuracy compared with the literature available estimation method recommended by the ACI318. In addition, a soft database composed of 50 different beam specimens with varying mechanical properties and reinforcement patterns was formed. Numerical models corresponding to all possible combinations of each parameter were generated, and their load capacities were determined. After that, the estimation performances of the proposed method and the stress–strain models from the literature, and also the ACI318 procedure were examined. The conclusion of this check also yielded promising results with an absolute mean percentage error of 5.13% regardless of the mode of failures.