Effect of Graphene Oxide as a Nanomaterial on the Durability Behaviors of Engineered Cementitious Composites by Applying RSM Modelling and Optimization

Abstract

Engineered Cementitious Composites (ECC) are widely used in various structures due to their high strength, durability, and ductility. However, they are still vulnerable to environmental factors such as sulphate and acid attack. These attacks damage the concrete matrix, which leads to cracking and corrosion of the reinforcing steel. To mitigate these issues, various techniques have been developed, including the addition of graphene oxide to the ECC mix. Graphene oxide has shown potential in improving the mechanical properties and durability of ECC. The purpose of this study was to use multi-objective optimization to identify an appropriate GO by the weight of the cement and polyvinyl alcohol (PVA) fiber volume fraction in an ECC mixture. Using RSM’s central composite design (CCD), thirteen mixtures of various possible combinations of variables (GO: 0.05 percent to 0.08 percent, PVA: 1–2 percent) were established, and eight response responses (compressive strength, change in length, weight loss, pH test, weight gain, expansion, rapid chloride permeability test and water absorption) were examined. However, analysis of variance was used to effectively design and evaluate eight (six quadratic and two linear) response models. All the models had extremely high R2 values, ranging from 84 percent to 99 percent. The multi-objective optimization produced ideal variable values (GO: 0.05 percent and PVA: 1%) and projected optimum response values. The predicted values were verified experimentally and found to correlate extremely well with the experimental data, with less than a 5% error. The outcome showed that the maximum increase of 30% in the compressive strength was recorded at 0.05% of GO as a nanomaterial in ECC. In addition, the expansion due to sulfate resistance and change in length due to acid attack were decreased by 0.0023% and 0.28%, respectively, when the use of 0.08% of GO as a nanomaterial in the ECC matrix was reinforced with 1% PVA fiber for 28 days. Moreover, the weight loss and weight gain of ECC combined with 1% of PVA fiber due to chemical attack decreased by 66.70% and 77.80%, respectively, at 0.08% of GO as a nanoscale particle than that of the reference mix for 28 days. In addition, the pH value due to acid attack, rapid chloride permeability test value, water absorption, and slump flow of the fresh mixture were decreased as the concentration of GO rose in ECC. The results indicated that the incorporation of 0.05% GO as a nanomaterial and 1 to 1.5% of PVA fiber will provide the best outcomes for the construction industry.

Effect of seawater salinity, pH, and temperature on external corrosion behavior and microhardness of offshore oil and gas pipeline: RSM modelling and optimization

“…The observed ARD was calculated using Eq. ( 4 ), allowing for an evaluation of the precision of the predicted model for each parameter 55 , 56 . The results outlined in Table 11 demonstrate a high level of conformity between the experimental and predicted outcomes, affirming the reliability and predictability of the model, largely owing to minimal variance.…”

Research on a Multi-Objective Optimization Design for the Durability of High-Performance Fiber-Reinforced Concrete Based on a Hybrid Algorithm

“…It evaluates the impact of interaction among factors on response values, determines the optimal response values, and offers advantages over orthogonal experiments, such as requiring fewer trials, lower costs, and higher predictive accuracy [32]. Naraindas Bheel et al [33] employed RSM's central composite design (CCD) to establish a relationship between 13 different raw material contents and eight target values in engineered cementitious composites (ECC). They validated the predicted values through experiments, and the results showed a strong correlation between the predicted values and the experimental data.…”