Zhao Junqin, Wang Xuewei, Yan Fuheng, Cai Xin, Xiao Shengcai, Cui Shengai, Liu Ping
School of Civil Engineering, Sichuan Agricultural University, Chengdu 611830, China.
School of Civil Engineering, Southwest Jiaotong University, Chengdu 610031, China.
Materials (Basel). 2025 Jul 8;18(14):3212. doi: 10.3390/ma18143212.
Recent studies primarily focus on how the fiber content and curing age influence the pore structure and strength of concrete. However, The interfacial bonding mechanism in basalt-fiber-reinforced concrete hydration remains unclear. The lack of a long-term performance-prediction model and insufficient research on multi-field coupling effects form key knowledge gaps, hindering the systematic optimal design and wider engineering applications of such materials. By integrating X-ray computed tomography (CT) with the watershed algorithm, this study proposes an innovative gray scale threshold method for pore quantification, enabling a quantitative analysis of pore structure evolution and its correlation with mechanical properties in basalt-fiber-reinforced concrete (BFRC) and normal concrete (NC). The results show the following: (1) Mechanical Enhancement: the incorporation of 0.2% basalt fiber by volume demonstrates significant enhancement in the mechanical performance index. At 28 days, BFRC exhibits compressive and splitting tensile strengths of 50.78 MPa and 4.07 MPa, surpassing NC by 19.88% and 43.3%, respectively. The early strength reduction in BFRC (13.13 MPa vs. 22.81 MPa for NC at 3 days) is attributed to fiber-induced interference through physical obstruction of cement particle hydration pathways, which diminishes as hydration progresses. (2) Porosity Reduction: BFRC demonstrates a 64.83% lower porosity (5.13%) than NC (11.66%) at 28 days, with microscopic analysis revealing a 77.5% proportion of harmless pores (<1.104 × 10 μm) in BFRC versus 67.6% in NC, driven by densified interfacial transition zones (ITZs). (3) Predictive Modeling: a two dimensional strength-porosity model and a three-dimensional age-dependent model are developed. The proposed multi-factor model demonstrates exceptional predictive capability (R = 0.9994), establishing a quantitative relationship between pore micro structure and mechanical performance. The innovative pore extraction method and mathematical modeling approach offer valuable insights into the micro-structural evolution mechanism of fiber concrete.
近期研究主要聚焦于纤维含量和养护龄期如何影响混凝土的孔隙结构和强度。然而,玄武岩纤维增强混凝土水化过程中的界面粘结机理仍不明确。缺乏长期性能预测模型以及对多场耦合效应的研究不足构成了关键的知识空白,阻碍了此类材料的系统优化设计和更广泛的工程应用。通过将X射线计算机断层扫描(CT)与分水岭算法相结合,本研究提出了一种创新的孔隙量化灰度阈值方法,能够对玄武岩纤维增强混凝土(BFRC)和普通混凝土(NC)的孔隙结构演变及其与力学性能的相关性进行定量分析。结果表明:(1)力学增强:体积掺量为0.2%的玄武岩纤维显著提高了力学性能指标。在28天时,BFRC的抗压强度和劈裂抗拉强度分别为50.78MPa和4.07MPa,分别比NC高出19.88%和43.3%。BFRC早期强度降低(3天时为13.13MPa,而NC为22.81MPa)归因于纤维通过物理阻碍水泥颗粒水化路径而引起的干扰,随着水化的进行这种干扰会减弱。(2)孔隙率降低:28天时,BFRC的孔隙率(5.13%)比NC(11.66%)低64.83%,微观分析表明,BFRC中无害孔隙(<1.104×10μm)的比例为77.5%,而NC中为67.6%,这是由致密的界面过渡区(ITZs)所致。(3)预测建模:建立了二维强度 - 孔隙率模型和三维龄期相关模型。所提出的多因素模型具有出色的预测能力(R = 0.9994),建立了孔隙微观结构与力学性能之间的定量关系。创新的孔隙提取方法和数学建模方法为纤维混凝土的微观结构演变机制提供了有价值的见解。