实验分析和基因表达编程优化含有矿物填充剂的可持续混凝土的优化
Ayesha Rauf1, Usama Asif2,3, Kennedy Onyelowe4,5
1Department of Civil Engineering, Nazarbayev University, Nazarbayev, Kazakhstan.
Scientific reports
|November 26, 2024
概括
采石场灰尘有效地取代了混凝土中的河流沙子,其中40%的替代物显示出最佳的机械性能. 基因表达编程模型准确地预测具体的性能,帮助可持续的建筑实践.
科学领域:
- 土木工程 土木工程是指土木工程.
- 材料科学 材料科学 材料科学
- 计算智能是一种计算智能.
背景情况:
- 快速的城市化增加了对混凝土的需求,耗尽了诸如河沙之类的自然资源.
- 可持续的替代品对于混凝土中的细聚合物至关重要.
- 采石粉 (QD) 为微型聚合物提供了一个环保的替代品.
研究的目的:
- 调查采石场粉尘作为混凝土中细聚合物的部分替代品的可行性.
- 开发和验证先进的机器学习模型,用于预测混凝土的性能.
- 加强可持续混凝土混合设计的实际应用.
主要方法:
- 混凝土的实验研究,采石场灰尘含量 (0-60%) 和超级可塑剂含量各不相同.
- 机械性能测试,包括压力和拉伸强度.
- 开发基因表达编程 (GEP) 模型用于性能预测.
- 针对多线性回归 (MLR) 和统计指标验证GEP模型.
- 敏感性分析和创建一个图形用户界面 (GUI).
主要成果:
- 混凝土用40%的采石场灰尘替代物表现出最佳的机械性能.
- GEP模型实现了高精度 (CS的R2=0.96,TS的R2=0.92),表现优于MLR模型.
- 灵敏度分析确定了关键成分对混凝土性能的影响.
- 开发的图形用户界面有助于实际的混凝土混合设计.
结论:
- 采石灰是混凝土中可行的和可持续的替代细聚合物.
- 基因表达编程为预测具体的机械性质提供了一个强大的工具.
- 该研究提供了可持续混凝土混合设计的实际解决方案,使用采石场粉尘和超级可塑剂.
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