Mahmood, Aamir, Pechoˇciaková, Miroslava, Tomková, Blanka, Tayyab Noman, Muhammad, Gheibi, Mohammad, Behzadian, Kourosh ORCID: https://orcid.org/0000-0002-1459-8408, Wiener, Jakub and Hes, Luboš (2025) Machine Learning-Driven optimization for evaluating the durability of Basalt fibers in Alkaline environments. Fibers, 13 (10).

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Abstract

Basalt fiber-reinforced composites are increasingly utilized in sustainable construction due to their high strength, environmental benefits, and durability. However, the long-term tensile performance of these composites in alkaline environments remains a critical concern. This study investigates the degradation performance of basalt fibers exposed to different alkaline solutions (NaOH, KOH, and Ca(OH)2) with varying concentrations (5 g/L, 15 g/L, and 30 g/L) over various exposure periods (7, 14, and 28 days). The performance assessment is carried out by mechanical properties, including tensile strength and modulus of elasticity, using experimental techniques and Response Surface Methodology (RSM) to find influential factors on tensile performance. The findings indicate that tensile strength degradation is highly dependent on alkali type and concentration, with Ca(OH)2-treated fibers exhibiting superior mechanical retention (max tensile strength: 938.94 MPa) compared to NaOH-treated samples, which showed the highest degradation rate. Five machine learning (ML) models, including Tree Random Forest (TRF), Function Multilayer Perceptron (FMP), Lazy IBK, Meta Bagging, and Function SMOreg (FSMOreg), were also implemented to predict tensile strength based on exposure parameters. FSMOreg demonstrated the highest prediction accuracy with a correlation coefficient of 0.928 and the lowest error metrics (RMSE 181.94). The analysis boosts basalt fiber durability evaluations in cement-based composites.

Item Type:	Article
Identifier:	10.3390/fib13100137
Keywords:	basalt fiber; machine learning; optimization; alkaline environment; tensile strength; sustainable construction
Subjects:	Computing > Intelligent systems Construction and engineering
Date Deposited:	05 Oct 2026
Dates:	Date Publication status 28 September 2025 Accepted 11 October 2025 Published Online
School, department or research centre:	School of Computing and Engineering
Keywords:	basalt fiber; machine learning; optimization; alkaline environment; tensile strength; sustainable construction
URI:	https://repository.uwl.ac.uk/id/eprint/15456
Sustainable Development Goals:	Goal 9: Industry, Innovation, and Infrastructure	Sustainable Development Goals:	Goal 12: Responsible Consumption and Production	Sustainable Development Goals:	Goal 13: Climate Action

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