Mita Ayesha Ferdous, Ray Sourav, Haque Mohaiminul, Saikat Md Hadiuzzaman
Department of Civil and Environmental Engineering, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh.
Heliyon. 2023 Mar 11;9(3):e14436. doi: 10.1016/j.heliyon.2023.e14436. eCollection 2023 Mar.
Over-extraction of aggregates from natural sources with rapid urbanization as well as massive waste generation in construction industry have imposed the need to utilize waste material as concrete constituent. Crushed Stone Dust (CSD) is such a supplementary material that can be utilized for the production of sustainable concrete. This study attempts to predict and optimize fresh and hardened properties of concrete utilizing CSD as a partial replacement of natural fine aggregate and Nylon Fiber (NF) as fiber reinforcement using Response Surface Methodology (RSM). A three-level factorial design of Box-Behnken was incorporated to investigate the effect of CSD, NF and W/C as three independent variables on compressive strength, splitting tensile strength, fresh density and workability of concrete as desired responses. All the developed probabilistic models were found to be significant in predicting the responses at 95% confidence level. Regression analysis in terms of correlation coefficient, coefficient of determination, coefficient of variation, adequate precision, chi-square, mean square error, root mean square error, and mean absolute error also indicated the accuracy and functionality of the developed models. The results reveal that both compressive and splitting tensile strength increase with increased NF content, but the rise in CSD percentages beyond a certain level has negative impact on strength of concrete. However, fresh density and workability of concrete show a declining trend with rise in both CSD and NF levels. From multi-objective optimization, 20% CSD, 0.75% NF and W/C of 0.49 have been found to be the optimum proportions for concrete mixture with a desirability of 0.915. Finally, an experimental validation was carried out with optimum mixture contents and relative error between the experimental and predicted optimized values was observed to be less than 5%.
随着城市化进程的加快，从天然资源中过度开采集料以及建筑业产生大量废弃物，使得有必要将废料用作混凝土成分。碎石粉（CSD）就是这样一种可用于生产可持续混凝土的补充材料。本研究试图采用响应面法（RSM），预测并优化以CSD部分替代天然细集料以及以尼龙纤维（NF）作为纤维增强材料的混凝土的新拌性能和硬化性能。采用Box-Behnken三水平析因设计，研究CSD、NF和水灰比（W/C）这三个自变量对作为期望响应的混凝土抗压强度、劈裂抗拉强度、新拌密度和工作性的影响。结果发现，所有建立的概率模型在95%置信水平下对响应的预测均具有显著性。相关性系数、决定系数、变异系数、足够精度、卡方、均方误差、均方根误差和平均绝对误差等回归分析也表明了所建立模型的准确性和功能性。结果表明，抗压强度和劈裂抗拉强度均随NF含量的增加而提高，但CSD百分比超过一定水平后会对混凝土强度产生负面影响。然而，混凝土的新拌密度和工作性随CSD和NF含量的增加呈下降趋势。通过多目标优化，发现20%的CSD、0.75%的NF和0.49的水灰比是混凝土混合料的最佳比例，合意度为0.915。最后，对最佳混合料含量进行了试验验证，试验值与预测优化值之间的相对误差小于5%。
