Strength optimisation of mortar with CNTs and nanoclays

Author:

Bani-Hani Khaldoon A.1,Irshidat Mohammad R.2,Al-Rub Rashid K. Abu3,Al-Nuaimi Nasser A.4,Talleh Ala'a T.2

Affiliation:

1. Department of Civil Engineering, Jordan University of Science and Technology, Irbid, Jordan (corresponding author: )

2. Department of Civil Engineering, Jordan University of Science and Technology, Irbid, Jordan

3. Mechanical Engineering, Masdar Institute of Science and Technology, Masdar City, United Arab Emirates

4. Civil and Architectural Engineering Department, Qatar University, Doha, Qatar

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.

Publisher

Thomas Telford Ltd.

Subject

Building and Construction,Civil and Structural Engineering

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