复合材料科学与工程 ›› 2024, Vol. 0 ›› Issue (12): 87-95.DOI: 10.19936/j.cnki.2096-8000.20241228.013

• 应用研究 • 上一篇    下一篇

纤维增强复合材料加强混凝土的约束效应研究

千银敏1, 沈寒峰1, 王涛2, 张开金3   

  1. 1.郑州城市职业学院 建筑工程学院,郑州 452370;
    2.中交第一公路勘察设计研究院有限公司,西安 710075;
    3.武汉理工大学 硅酸盐建筑材料国家重点实验室,武汉 430070
  • 收稿日期:2023-08-28 出版日期:2024-12-28 发布日期:2025-01-14
  • 作者简介:千银敏(1982—),女,讲师,从事复合材料工程、土木工程材料技术等方面的研究,hanfengs18@126.com。
  • 基金资助:
    国家自然科学基金(51978545)

Research on the confinement effect of fiber-reinforced polymer materials reinforced concrete

QIAN Yinmin1, SHEN Hanfeng1, WANG Tao2, ZHANG Kaijin3   

  1. 1. School of Architectural Engineering, City University of Zhengzhou, Zhengzhou 452370, China;
    2. CCCC First Highway Consultants Co., Ltd., Xi’an 710075, China;
    3. State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan 430070, China
  • Received:2023-08-28 Online:2024-12-28 Published:2025-01-14

摘要: 为准确预测纤维增强复合材料应用于混凝土中的约束效应,提出了基于随机森林算法和CatBoost算法的纤维增强复合材料约束混凝土的强度效应模型和应变效应模型。本文收集了502个纤维增强复合材料沿侧面缠绕圆柱体混凝土试件的数据,其参数包括混凝土截面尺寸、纤维增强复合材料缠绕厚度、断裂应变和弹性模量、无约束混凝土强度和应变、约束强度效应和约束应变效应,并对已有的经验性约束强度效应和约束应变效应模型进行对比评估。选取了决定系数(R2)、均方根误差和平均绝对误差这三个评估指标,对所建立的随机森林模型和CatBoost模型进行对比评估。结果表明:在约束强度效应方面,随机森林模型和CatBoost模型的R2基本在0.84以上,均大于已有经验性模型R2(0.78~0.83);在约束应变效应方面,随机森林模型和CatBoost模型的R2基本在0.87以上,均大于已有经验性模型R2(0.65~0.75)。由此可知所建立的随机森林模型和CatBoost模型性能优于已有经验性模型性能,均可较为准确地预测纤维增强复合材料应用于混凝土中的约束效应,其中CatBoost模型的准确性更高。

关键词: 复合材料, 纤维增强, 混凝土, 约束强度效应, 约束应变效应

Abstract: To accurately predict the confinement effect of fiber-reinforced composite materials applied to concrete, strength and strain effect models for fiber-reinforced composite-constrained concrete were proposed based on Random Forest and CatBoost algorithms. Data of 502 concrete specimens with fiber-reinforced composite wrapping along the lateral side were collected, including parameters such as concrete cross-sectional dimensions, fiber-reinforced composite wrapping thickness, fracture strain and elastic modulus, unconstrained concrete strength and strain, constrained strength effect, and constrained strain effect. Existing empirical models for confinement strength and strain effects were compared and evaluated. Three evaluation metrics, namely determination coefficient (R2), root mean square error, and mean absolute error, were selected for the comparative evaluation of the developed Random Forest and CatBoost models. The results showed that for the confinement strength effect, the R2 values of the Random Forest model and CatBoost model were generally above 0.84, higher than the existing empirical models (0.78 to 0.83). Regarding the confinement strain effect, the R2 values of the Random Forest model and CatBoost model were generally above 0.87, also higher than the existing empirical models (0.65 to 0.75). This indicated that the performance of the developed Random Forest and CatBoost models was superior to the existing empirical models, and both models could provide relatively accurate predictions of the confinement effect of fiber-reinforced composite materials applied to concrete. Particularly, the CatBoost model demonstrated higher accuracy.

Key words: composite materials, fiber-reinforced, concrete, confinement strength effect, confinement strain effect

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