Case Studies in Construction Materials (Dec 2024)
Enhancing the performances of self-consolidating composite mortars with Alfa fibers and slag: A combined Taguchi-ANN optimization
Abstract
Alfa fiber-reinforced self-compacting mortars (SCMs) offer enhanced workability. Thus, the potential of combining natural Alfa fibers and ground granulated blast furnace slag (GBFS) to optimize the rheological and mechanical properties was ascertained. The effect of fibers and GBFS on the properties of SCMs after treatment with linseed oil and NaOH was also evaluated. Partial substitution of cement by slag (10 % and 30 %.) was achieved. Mini cone spreading, V-funnel flow tests as well as compressive and bending tests at 7 days and 28 days were performed on the prepared mixtures. For optimization and predictive purposes, both Taguchi optimization and Artificial Neural Network modeling were employed. Our results indicated that, according to Taguchi experimental design, the use of 1 % fiber in the initial mixture achieved a good distribution within the paste and improved flexural strength. In addition, the treatment of fibers with NaOH actually improved the structure and bonding surface. Fiber content and GBFS replacements achieved the desired rheological and mechanical characteristics. Prediction of both compressive and flexural strengths was successfully achieved by an accurate application of machine a learning algorithm based on six inputs, one hidden layer and four outputs. The combined ANN-Taguchi approach provided accurate predictions of SCM performances and identified a robust mix-design that was less prone to fluctuations in the initial material properties. Alfa fibers and GBFS promoted both fresh and hardened properties. This study demonstrated the effectiveness ML and statistical optimization in developing high-performance, sustainable-SCMs with superior workability and strengths, making them ideal for various construction applications.
