在使用ANN和GRA技术的中心压缩静态负荷下,估计与CFRP相结合的圆形短柱的轴应变
Ammar T Al-Sayegh1, Nasim Shakouri Mahmoudabadi2, Lamis J Behbehani3
1Department of Civil Engineering, College of Engineering & Petroleum, Kuwait University, Kuwait.
Heliyon
|August 2, 2024
概括
本研究介绍了使用人工神经网络 (ANN) 和通用回归分析 (GRA) 的先进模型,以准确预测碳纤维增强聚合物 (CFRP) 封闭混凝土中的轴向应变. 这些模型增强了对抗地震能力的结构完整性评估.
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
- 结构工程 结构工程
背景情况:
- 碳纤维增强聚合物 (CFRP) 的限制对于增强混凝土的结构完整性至关重要,特别是在地震区.
- 在CFRP混凝土中精确预测轴向应变对于可靠的结构设计和安全评估至关重要.
- 现有的预测模型往往缺乏复杂的地震负载条件所需的精度.
研究的目的:
- 开发和验证先进的预测模型,用于在CFRP封闭的混凝土气中进行轴向应变估计.
- 在地震相关的负载场景下提高应变预测的准确性和可靠性.
- 为在易发生地震的地区设计和加强混凝土结构提供一个强大的框架.
主要方法:
- 使用了708个实验观测的综合数据集.
- 用于复杂模式识别和预测的人工神经网络 (ANN).
- 应用通用回归分析 (GRA) 来完善预测关系并提高模型可靠性.
主要成果:
- 开发了增强的预测模型,证明了卓越的性能.
- 达到0.85的高R平方值,表明强大的模型适合.
- 获得了1.42的根平均平方误差 (RMSE),表示高预测准确度.
- 与现有模型相比,在模拟和预测轴向应变行为方面表现出卓越的能力.
结论:
- 开发的ANN和GRA模型在预测CFRP混凝土的轴向应变方面取得了重大进展.
- 这些模型提供了更高的准确性和可靠性,这对于地震环境中的结构完整性至关重要.
- 这项研究建立了一个新的基准,为抗震结构工程和未来研究提供了有价值的工具.
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