首页|Sustainable use of chemically modified tyre rubber in concrete: Machine learning based novel predictive model

Sustainable use of chemically modified tyre rubber in concrete: Machine learning based novel predictive model

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  • NSTL
  • Elsevier
To encourage the consumption of crumb rubber (CR), gene expression programming (GEP) has been exercised in this paper to establish empirical models for estimation of mechanical properties of concrete made with NaOH treated CR. An extensive and reliable database of compressive strength of concrete made with NaOH treated CR is established through a comprehensive literature review. Literature review showed that compressive strength of NaOH treated CR concrete is affected by percentage of CR used as a replacement of sand (RS%), concentration of NaOH solution (NC in %), period of NaOH pre-treatment (PTP in hours), water to cement ratio (W/C), quantity of sand (S in kg/m(3)) and quantity of superplasticizer (SP in kg/m(3)). The performance of the established model is evaluated by doing parametric analysis, applying statistical checks and comparing with regression models. The R-values in the testing phase of GEP, linear and non-linear regression (LR and NLR) equations are 0.90 and 0.77 each respectively. Furthermore, objective function (OF) of GEP model is 25%, and 33% better than LR and NLR model. Thus, results reflected that the proposed GEP model is more accurate and possess a high generalization and prediction capability than LR and NLR equations with resolved overfitting issue. The results of this research can boost the re-usage of CR for expansion of green concrete leading to environmental safety and economic advantages.

Crumb rubberNaOH treatmentGene expression programmingSensitivity analysisParametric studiesARTIFICIAL NEURAL-NETWORKSELF-COMPACTING CONCRETECOMPRESSIVE STRENGTH PREDICTIONMECHANICAL-PROPERTIESCRUMB RUBBERWASTE RUBBERSILICA FUMEPERFORMANCEDURABILITYAGGREGATE

Li, Piyu、Khan, Mohsin Ali、Galal, Ahmed M.、Awan, Hamad Hassan、Zafar, Adeel、Javed, Muhammad Faisal、Khan, M. Ijaz、Qayyum, Sumaira、Malik, M. Y.、Wang, Fuzhang

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Xuzhou Univ Technol

Natl Univ Sci & Technol NUST

Prince Sattam Bin Abdulaziz Univ

COMSATS Univ Islamabad

Riphah Int Univ

Quaid I Azam Univ

King Khalid Univ

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2022

10.1016/j.cplett.2022.139478

Chemical Physics Letters

Chemical Physics Letters

EISCI
ISSN：0009-2614
年,卷(期)：2022.793
  • 5
  • 121