响应面法
极限抗拉强度
抗压强度
骨料(复合)
中心组合设计
材料科学
铜
实验设计
岩土工程
环境科学
结构工程
复合材料
计算机科学
地质学
冶金
工程类
数学
统计
机器学习
作者
Mohaiminul Haque,Sourav Ray,Ayesha Ferdous Mita,Anik Mozumder,Tirtha Karmaker,Sanjida Akter
出处
期刊:Heliyon
[Elsevier]
日期:2024-01-01
卷期号:10 (2): e24705-e24705
被引量:1
标识
DOI:10.1016/j.heliyon.2024.e24705
摘要
Urban growth in the developing world has prompted scientists to seek alternatives to fine aggregate due to the severe environmental impact of extensive natural sand depletion. On top of that, the accumulation of non-biodegradable dumps, solid trash such as scrapped copper wire (SCW), and industrial remnants like Granite dust (GD) has reached alarming levels. Therefore, incorporating these two waste materials in concrete offers a potentially sustainable solution. The study strives to substitute natural fine aggregate with GD, incorporate SCW, evaluate the compressive and splitting tensile strength and optimize concrete hardened properties using response surface methodology (RSM). Two independent variables-the volumetric percentages of GD (10 %, 20 %, and 30 %) and SCW (0.1 %, 0.3 %, and 0.5 %) in a concrete mix ratio of 1:1.5:3, were utilized to create probabilistic models for compressive and splitting tensile strength at 7 and 28 days. The experimental design employed Central Composite Design (CCD) of RSM and the results of both ANOVA and regression analysis in terms of several statistical functions demonstrated a strong correlation between the predicted values of the responses and the actual experimental results. The developed models were validated by conducting experiments using optimized proportions of GD (23.32 %) and SCW (0.37 %). Finally, the strengths of the optimum content mix yielding 25.116 MPa and 3.266 MPa respectively for compressive and splitting tensile at 28 days ensure the efficiency of the models due to the substantial similarity between experimental and predicted values. Therefore, Integrating GD and SCW for higher-strength concrete in mass production could be a cost-effective alternative, fostering increased recycling of waste and supporting sustainable growth in building construction.
科研通智能强力驱动
Strongly Powered by AbleSci AI