整合机器学习和微结构性特征,以预测使用二氧化烟雾和M-sand的强度,以获得可持续的混凝土
Bypaneni Krishna Chaitanya1, Chereddy Sonali Sri Durga2, Naresh Thatikonda3
1Department of Civil Engineering, R.V.R. & J.C. College of Engineering, Guntur, 522019, India.
Scientific reports
|March 11, 2026
概括
使用飞灰,烟和制造砂的可持续混凝土混合物提高了机械性能. 最佳的混合物 (10%飞灰,12%烟) 显示出优越的强度和微观结构,由机器学习预测验证.
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.
- 可持续建筑 可持续建筑
背景情况:
- 工业副产品如飞灰和烟可以纳入混凝土,以减轻水泥生产对环境的影响.
- 使用制造砂作为精细聚合物为天然砂提供了一个可持续的替代方案.
研究的目的:
- 评估可持续的三元混凝土混合物,其中含有不同含量的烟 (0-24%) 和100%的制造砂.
- 为了确定优越的机械和微观结构性质的最佳混合比例.
- 应用机器学习来预测具体的性能和减少实验试验.
主要方法:
- 混凝土混合物的制备和测试,其中含有10%的飞灰,0-24%的烟,100%的制造砂.
- 机械性能评估 (压力,分裂拉力,屈曲强度,超声波脉冲速度) 在7,28和90天.
- 使用SEM,EDS和TGA进行微结构分析.
- 机器学习模型的应用 (LASSO,随机森林,梯度提升,XGBoost,AdaBoost,ANN) 用于性能预测.
主要成果:
- 混凝土混合物含有10%的飞灰,12%的二氧化烟雾和100%的制造砂,具有最高的机械强度.
- 在90天内,压力强度在最佳混合物中增加了高达19.83%.
- 微结构分析表明,在最佳混合物中,C-S-H凝的密度更高,孔隙性更小.
- 梯度增强机器学习模型实现了压力强度的高预测精度 (R2=0.9929).
结论:
- 最佳的三元混凝土混合物 (10%飞灰,12%烟,100%制造砂) 提供了增强的机械性能和改进的微观结构.
- 机器学习有效地预测了具体的特性,简化了优化过程.
- 这种可持续的混凝土配方适用于高性能结构应用.
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