Strength and Acid Resistance of Ceramic-Based Self-Compacting Alkali-Activated Concrete: Optimizing and Predicting Assessment

Abstract

The development of self-compacting alkali-activated concrete (SCAAC) has become a hot topic in the scientific community; however, most of the existing literature focuses on the utilization of fly ash (FA), ground blast furnace slag (GBFS), silica fume (SF), and rice husk ash (RHA) as the binder. In this study, both the experimental and theoretical assessments using response surface methodology (RSM) were taken into account to optimize and predict the optimal content of ceramic waste powder (CWP) in GBFS-based self-compacting alkali-activated concrete, thus promoting the utilization of ceramic waste in construction engineering. Based on the suggested design array from the RSM model, experimental tests were first carried out to determine the optimum CWP content to achieve reasonable compressive, tensile, and flexural strengths in the SCAAC when exposed to ambient conditions, as well as to minimize its strength loss, weight loss, and UPVL upon exposure to acid attack. Based on the results, the optimum content of CWP that satisfied both the strength and durability aspects was 31%. In particular, a reasonable reduction in the compressive strength of 16% was recorded compared to that of the control specimen (without ceramic). Meanwhile, the compressive strength loss of SCAAC when exposed to acid attack minimized to 59.17%, which was lower than that of the control specimen (74.2%). Furthermore, the developed RSM models were found to be reliable and accurate, with minimum errors (RMSE < 1.337). In addition, a strong correlation (R > 0.99, R2 < 0.99, adj. R2 < 0.98) was observed between the predicted and actual data. Moreover, the significance of the models was also proven via ANOVA, in which p-values of less than 0.001 and high F-values were recorded for all equations.

Optimization of CWP-BFS Blended Geopolymer Concrete Using BWMbased Taguchi Method

“…Algaifi et al used the response surface methodology to optimize and predict the optimal content of CWP in BFSbased self-consolidating alkali-activated concrete. The authors found that the optimum content of 31% CWP satisfied the desired mechanical and durability performance, particularly when specimens were exposed to acid attack [18]. Teimortashlu et al employed the Taguchi method to optimize the compressive strength of tertiary blended selfcompacting concrete, in which three factors at four different levels were considered [19].…”

Advancing Sustainable Wastewater Treatment Using Enhanced Membrane Oil Flux and Separation Efficiency through Experimental-Based Chemometric Learning

“…Recently, researchers proposed and developed a technique for global optimization by combining experimental design with machine learning (ML) [12]. The ML approach uses various dependent and independent variables gathered from experimental design [13]. Lately, the deployment of ML and AI approaches has been reported in various chemical processes, such as separation [14], transesterification reactions [15,16], bioethanol production processes [17], electrospinning processes [18], polymerization processes [19], esterification reactions [20], and other chemical processes [21].…”

Flexural Behavior of Reinforced Concrete Beams under Instantaneous Loading: Effects of Recycled Ceramic as Cement and Aggregates Replacement

“…Currently, concrete is the most consumed human-made material, with global consumption of up to 15 billion tons of natural aggregates every year [5,6]. The utilization of waste materials can help our environment by reducing the consumption of non-renewable natural resources, lessening the problems of landfills [7,8]. Conservative usage of natural resources and reducing the waste generated by the industry are among the main strategies to attain cleaner and more sustainable productions [9][10][11][12].…”