使用实验和机器学习方法评估废玻璃粉对提高水泥砂压力强度的有效性
Kaffayatullah Khan1, Waqas Ahmad2, Muhammad Nasir Amin1
1Department of Civil and Environmental Engineering, College of Engineering, King Faisal University, Al-Ahsa, 31982, Saudi Arabia.
Heliyon
|May 26, 2023
概括
废玻璃粉 (WGP) 增强了水泥砂的压力强度 (CS). 实验结果显示,最佳的CS是10%的WGP取代水泥,15%的WGP取代沙子. 机器学习模型准确地预测了这些改进.
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:
- 建筑材料面临着日益增长的需求,需要可持续的替代品.
- 废玻璃粉 (WGP) 为水泥复合材料提供了一个可行的pozzolanic材料.
- 优化WGP整合需要了解其对压力强度 (CS) 等机械性能的影响.
研究的目的:
- 实验评估WGP对水泥砂CS的影响.
- 开发和验证机器学习 (ML) 模型,用于预测WGP修改的水泥砂CS.
- 为了确定最佳的WGP替代水平,以增强CS.
主要方法:
- 对水泥砂进行实验测试,使用不同的WGP替代百分比 (0-15%) 替代水泥和沙子.
- 应用ML算法 (决策树,AdaBoost) 来根据实验数据预测CS.
- 使用R2,统计测试和k-fold验证来评估ML模型的性能.
主要成果:
- 加入WGP通常会提高水泥砂的CS.
- 通过10%的WGP替代水泥和15%的WGP替代沙子,实现了最大的CS.
- 与决策树模型相比,AdaBoost ML模型在预测CS方面显示出更高的准确性.
结论:
- WGP是一种有效的添加剂,用于改善水泥砂CS.
- 机器学习技术,特别是AdaBoost,为建筑中的材料属性预测提供了高效和准确的方法.
- 该研究为可持续建筑实践和材料开发提供了宝贵的见解.
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