通过实验和机器学习方法分析制造砂和飞灰对混凝土强度的影响
S Sathvik1, Solomon Oyebisi2, Rakesh Kumar1
1Department of Civil Engineering, Dayananda Sagar College of Engineering, Bengaluru, 560111, Karnataka, India.
Scientific reports
|February 10, 2025
概括
这项研究通过用回收飞灰和制造砂代替河流沙和水泥来增强混凝土,提高压力强度. 机器学习,特别是XGBoost,准确地预测了这种优势,提供了一个可持续的建筑解决方案.
科学领域:
- 材料科学 材料科学 材料科学
- 土木工程 土木工程是指土木工程.
- 环境科学 环境科学
背景情况:
- 由于过度开采和非法采矿,河流沙的可用性正在下降.
- 常规波特兰水泥 (OPC) 生产的显著二氧化碳排放.
- 需要在混凝土生产中找到可持续的替代品.
研究的目的:
- 调查用飞灰和混凝土中的制造砂 (M砂) 取代河流沙和OPC的可行性.
- 为了评估混凝土的压力强度,这些回收材料.
- 使用机器学习模型来预测混凝土的压力强度.
主要方法:
- 设计的M40级混凝土混合物含有不同百分比的飞灰 (0-85重量%) 和M砂 (0-100重量%) 取代了OPC和河沙.
- 测试了混凝土的压力强度,固化时间为3 - 90天.
- 使用极端梯度提升 (XGBoost),LSTM,SVM和GPR模型来预测压力强度.
- 使用扫描电子显微镜与能量分散光谱学 (SEM-EDS) 描述了微观结构和元素组成.
主要成果:
- 加入飞灰和M砂提高了混凝土的压力强度.
- 使用25%飞灰和50%M砂替代的混凝土在28天后达到M40级强度.
- XGBoost模型在预测压力强度方面表现出卓越的准确性 (R2=0.9999训练,R2=0.9964测试).
- 在SEM-EDS分析中,发现了具有高和含量的紧型微结构.
结论:
- 飞灰和M砂是混凝土中常规材料的有效可持续替代品.
- 25%飞灰和50%M砂的部分替代水平符合M40等级强度要求.
- XGBoost是一个非常准确和可行的工具,用于预测可持续混凝土混合物的压力强度.
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