使用机器学习模型,优化使用回收聚合物和CFRP的RC梁的屈曲强度
Thanh-Hung Nguyen1, Hoang-Thach Vuong1, Jim Shiau2
1Faculty of Civil Engineering, Ho Chi Minh City University of Technology and Education, Ho Chi Minh City, Vietnam.
Scientific reports
|November 20, 2024
概括
本研究探讨了使用循环聚合物和碳纤维增强聚合物 (CFRP) 的环保混凝土梁. 优化的机器学习模型预测了增强的结构性能,显示了强度和承载能力的显著改善.
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
- 计算力学 计算力学 计算力学
背景情况:
- 混凝土梁的结构性能对基础设施至关重要.
- 可持续的建筑材料,如回收聚合物和CFRP提供潜在的好处.
- 了解这些材料的梁的曲行为需要先进的分析.
研究的目的:
- 为了研究含有回收聚合物和CFRP的钢筋混凝土梁的柔性轴承行为.
- 开发和评估结构性性能的先进机器学习预测模型.
- 量化可持续材料对梁强度和承载能力的影响.
主要方法:
- 实验测试八个混凝土梁的不同材料组成.
- 使用实验数据开发机器学习模型 (随机森林回归器,XGBoost,LightGBM).
- 数据预处理,特征选择,通过帕雷托优化进行超参数调整,并使用MSE,MAE和R2进行模型评估.
主要成果:
- 优化的机器学习模型展示了出色的预测性能.
- 使用70%回收聚合物和10%烟的梁显示压力强度增加了53.03%.
- 与控制梁相比,这些梁的承载能力也增加了7%.
结论:
- 整合回收聚合物和CFRP显著提高了混凝土梁的性能.
- 先进的机器学习模型有效地预测了使用可持续材料的梁的结构行为.
- 这项研究有助于开发环保和高性能建筑材料.
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