绿色混凝土与再生玻璃纤维增强聚合物的压力强度预测使用机器学习方法
Pouyan Fakharian1,2, Reza Bazrgary3, Ali Ghorbani4
1Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam.
Polymers
|October 28, 2025
概括
这项研究使用机器学习来预测混凝土与再生玻璃纤维增强聚合物 (GFRP) 废物的压力强度. 结果表明,较低的GFRP含量和特定形式 (如粉末或纤维) 提高了混凝土的强度.
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:
- 在建筑和运输行业中,纤维增强聚合物 (FRP) 的废物越来越多.
- 需要可持续的混凝土替代品和废物利用.
研究的目的:
- 使用机器学习预测回收玻璃纤维增强聚合物 (GFRP) 废料的环保混凝土的压力强度.
- 为了确定影响混凝土强度的关键因素与GFRP合并.
主要方法:
- 机器学习模型的开发和应用.
- 实验室测试了119种混凝土混合物,其GFRP废弃物含量和形式各不相同.
- 影响性参数的统计分析.
主要成果:
- 机器学习模型实现了高预测精度 (R2 = 0.8284).
- 压缩强度通常随着GFRP含量增加而下降,但在低剂量时是有利的.
- 水与水泥的比率和总GFRP含量是最有影响力的.
- 粉末和纤维形式的GFRP显示出积极的影响;聚合物的替代效果较低.
结论:
- 机器学习为使用GFRP废物设计可持续混凝土提供了定量指导.
- 突出了重复利用工业副产品在建筑材料中的潜力.
- 优化GFRP的形式和内容对于性能至关重要.
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