含有聚氨材料的U型混凝土的冲击和故障分析:深度学习和数字成像基于相关性的方法
Saleh Ahmad Laqsum1, Han Zhu1,2, Sadi I Haruna3
1School of Civil Engineering, Tianjin University, Tianjin 300350, China.
Polymers
|May 14, 2025
概括
这项研究表明,20%的聚氨 (PU) 含量优化了混凝土的混凝土.
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.
- 人工智能的人工智能
背景情况:
- 在冲击负载下混凝土的断裂行为对于结构安全至关重要.
- 聚氨改造提供了增强混凝土性能的潜力.
- 需要自动化裂评估来提高效率和准确性.
研究的目的:
- 为了研究聚氨改性混凝土在冲击下的断裂行为.
- 评估卷积神经网络 (CNN) 对于裂分类的有效性.
- 为了确定最佳的聚氨含量,以抗冲击和屈曲强度.
主要方法:
- 17个具有不同PU含量 (0-30%) 的U形混凝土样本在低重量冲击负载下进行了测试.
- 数字图像相关性 (DIC) 和机械测试被用来分析材料的行为.
- 三个CNN架构 (InceptionV3,MobileNet,DenseNet121) 在1655个破解图像上进行了训练,以进行故障阶段分类.
主要成果:
- 20%的PU含量提供了最佳的抗冲击和屈曲强度;30%的PU含量显著降低了机械性能.
- DIC分析显示,矩阵凝聚力降低,PU含量更高,表明潜在的结构完整性问题.
- 在分类裂阶段方面,InceptionV3 CNN取得了最高的准确性 (96.67%),超过了MobileNet和DenseNet121.
结论:
- 聚氨改造可以提高混凝土的抗冲击能力,高达20%的含量.
- 深度学习模型,特别是InceptionV3,提供了一个高度准确和高效的自动化框架,用于具体的裂评估.
- 保持PU含量低于20%至关重要,以防止损害改性混凝土的结构完整性.
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