Modelling of Sodium Hydroxide Treated Rubber Crumb – Mortar’s Compressive Strength Using Multilayer Perceptron Approach
Abiodun Joseph KILANI, Bolanle Deborah IKOTUN, Rasheed ABDULWAHAB
Abstract. The structural integrity of mortar is dependent on its performance in service. The ability of mortars to withstand compressive stress solely depends on its compressive strength. Incorporation of rubber crumb (RC) in mortar is one of the approaches used in environmental waste management campaigns. The literature revealed the flaw associated with the use of untreated RC in mortar, and this requires urgent solutions. In this study, the compressive strength of RC – mortar was determined in accordance with SANS 50196 -3:2006. The RC – mortars were produced from the mixture of 1.5 – 5.0% of 0.075 – 2.0 mm RC (by the weight of cement) which has been treated with 7% of sodium hydroxide (NaOH) solution, 1:3 of cement and sand, and 0.5 water – cement ratio. The 40 x 40 x160 mm mortar cubes were used to determine the compressive strengths of the RC – mortar on Universal Testing Machine (UTM) at 7 and 28 days of standard water curing. The experimental values of mortar’s compressive strength were modelled using multilayer perceptron (MP) of artificial neural network (ANN) to predict the compressive strength of the RC – Mortar. Among the ANN model predicted values, the optimum compressive strength of RC-mortar was observed to be 61.98 MPa at 1.5% of RC. The model predicted optimum compressive strength (61.98 MPa) is in correlation with that of experimented value (61.91 MPa) at excellent performance metrics of sum of squares error (SSE), mean absolute percentage error (MAPE), root mean square error (RMSE) and coefficient of determination (R2) values of 0.0010, – 0.0125, 0.0166 and 0.988 respectively. In conclusion, MP of ANN model provided matchable prediction of RC-mortar’s property, contributing to the development of environmental management and advance the production of sustainable composite material in the global construction industries.
Keywords
Artificial Neural Network, Rubber Crumb – Mortar, Compressive Strength, Rubber Crumb, Model, Multilayer Perceptron
Published online 4/2/2026, 8 pages
Copyright © 2026 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Abiodun Joseph KILANI, Bolanle Deborah IKOTUN, Rasheed ABDULWAHAB, Modelling of Sodium Hydroxide Treated Rubber Crumb – Mortar’s Compressive Strength Using Multilayer Perceptron Approach, Materials Research Proceedings, Vol. 63, pp 30-37, 2026
DOI: https://doi.org/10.21741/9781644904053-4
The article was published as article 4 of the book Advances in Cement and Concrete Research
Content from this work may be used under the terms of the Creative Commons Attribution 3.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
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