Strength optimisation of mortar with CNTs and nanoclays

Khaldoon A. Bani-Hani, Mohammad R. Irshidat, Rashid K.Abu Al-Rub, Nasser A. Al-Nuaimi, Ala’A T. Talleh

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

This study explores the use of carbon nanotubes (CNTs) and nanoclays in cement mortars. The paper presents modelling and optimisation of the compressive and flexural strengths of cement mortars containing CNTs and the compressive, tensile and flexural strengths of cement mortars including nanoclays. The CNT ratio, CNT aspect ratio and functionalisation effects are optimised, as are the montmorillonite nanoclay ratio and temperature effect. Mechanical strengths are modelled using two cascade feed-forward neural networks (NNs), designated CSNN-CNTs and CSNN-CLY for CNTs and nanoclays, respectively. The trained NN CNT and nanoclay models both successfully replicated experiments with significant accuracy. Inputs to the NN models were different mix combinations, optimised using a genetic algorithm to achieve optimal strength results. The optimisation process for mortars with CNTs revealed increases of 20·96% and 54·27% for compressive and flexural strengths, respectively. Similarly, optimisation of the mortar with nanoclays achieved increases of 63·7%, 199% and 133% for compressive, tensile and flexural strengths, respectively. These results demonstrate that the NN integrated genetic algorithm based optimisation is an effective way of determining the best recipe for CNT and nanoclay mortars for optimum strength.

Original languageBritish English
Pages (from-to)340-356
Number of pages17
JournalProceedings of the Institution of Civil Engineers: Structures and Buildings
Volume169
Issue number5
DOIs
StatePublished - 1 May 2016

Keywords

  • Concrete structures
  • Mathematical modelling
  • Strength & testing of materials

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