竹纤维增强混凝土抗压与劈裂抗拉性能试验及强度预测模型研究

Experimental study on compressive and splitting tensile properties and strength prediction model of bamboo fiber reinforced concrete

  • 摘要: 为研究竹纤维长度和体积掺量对混凝土力学性能的影响规律,本文开展了不同纤维长度(10 mm、20 mm、30 mm)和体积掺量(0.5%、1%、1.5%)下混凝土的立方体抗压和劈裂抗拉试验,并通过扫描电子显微镜(Scanning Electron Microscope, SEM)进行了微观结构分析。结果表明:竹纤维的掺入可改善混凝土的早期抗压性能并改变其破坏模式,但其28 d抗压强度随纤维长度增加而降低,随纤维体积掺量增加呈现先升后降的趋势。劈裂抗拉强度则表现出显著的纤维增强效应:当竹纤维长度为20 mm、体积掺量为1.0%时取得最优值3.80 MPa,较素混凝土提升20.8%。SEM分析表明,竹纤维分布均匀性与界面结合状态是决定其宏观力学性能的关键。基于试验数据,本研究评估了既有纤维混凝土(Fiber Reinforced Concrete, FRC)强度预测模型的适用性。通过对比模型预测值与试验值偏差,揭示了现有模型的局限性,进而构建了适用于竹纤维增强混凝土(Bamboo Fiber Reinforced Concrete, BFRC)的劈裂抗拉强度预测模型,为该类材料的配合比设计提供了理论依据。

     

    Abstract: To investigate the influence of bamboo fiber length and fiber content on the mechanical properties of concrete, this study conducted cube compressive and splitting tensile tests on fiber-reinforced concrete with varying fiber lengths (10 mm, 20 mm, 30 mm) and fiber contents (0.5%, 1.0%, 1.5%). Microstructural analysis was also performed using Scanning Electron Microscopy (SEM). The results show that the incorporation of bamboo fibers improves the early-age compressive behavior of concrete and alters its failure pattern. However, the 28-day compressive strength decreases with increasing fiber length, and exhibits a trend of first increasing and then decreasing with increasing fiber content. The splitting tensile strength of BFRC exhibits a significant fiber-reinforcing effect, reaching an optimal value of 3.80 MPa at a fiber length of 20 mm and a fiber content of 1.0%, which represents a 20.8% increase over that of plain concrete. SEM analysis reveals that the uniformity of fiber distribution and the quality of the fiber-matrix interface bonding are key factors determining the macroscopic mechanical performance. Based on the experimental data, this study evaluated the applicability of existing Fiber Reinforced Concrete (FRC) strength prediction models. By comparing the deviations between model predictions and experimental values, the limitations of current models were revealed. Consequently, a predictive model specifically suitable for BFRC was developed, providing a theoretical basis for the mix proportion design of this type of material.

     

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