使用神经网络估计超高性能轻质混凝土 (UHPLC) 的压力强度
Yan Zhao1, Ziyan Huang1, Huilong Zhao2
1School of Civil Engineering and Architecture, Wuyi University, Wuyishan City, Fujian Province, China.
PloS one
|July 7, 2025
概括
人工神经网络准确地预测超高性能轻质混凝土 (UHPLC) 的强度. 轻量级的沙子和水含量显著影响UHPLC的压力强度,为开发高效的混凝土复合材料提供了洞察力.
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.
- 计算力学 计算力学 计算力学
背景情况:
- 高强度和轻质混凝土对于结构效率至关重要.
- 在混凝土中平衡压力强度和密度是一个重大挑战.
- 超高性能轻质混凝土 (UHPLC) 为先进的建筑材料提供了潜力.
研究的目的:
- 使用人工神经网络 (ANN) 模型预测UHPLC的压力强度.
- 确定影响UHPLC压力强度的关键材料组件.
- 提出开发优质超高性能轻质复合材料的战略.
主要方法:
- 使用了两个ANN模型:反向传播 (BP) 和埃尔曼网络.
- 在115个UHPLC测试数据集的数据库上训练和测试模型.
- 对各种混凝土混合参数进行了相关性和灵敏度分析.
主要成果:
- 对于UHPLC的压力强度,ANN模型显示出高预测精度 (R2>0.98).
- 轻量级沙含量,沙含量和水含量被确定为最有影响力的参数.
- 飞灰含量和轻质沙类型对压力强度的影响最小.
- 与传统的混凝土和钢相比,UHPLC实现了优越的压力强度与密度比.
结论:
- ANN模型提供了一种可靠的方法来预测UHPLC的压力强度.
- 优化聚合物选择,包装密度和水粘合比是高性能轻质复合材料的关键.
- 对于未来的应用,UHPLC是一个有前途的材料,具有增强的结构效率.
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