摘要
采用多尺度分形模型构建水泥基体的孔隙结构,在此基础上结合Maxwell公式,计算并预测了采用不同胶凝材料体系配制的水泥基体氯离子扩散系数.进一步采用压汞法(MIP)测试孔隙的结构参数,借助氯离子电迁移法(RCM)验证了所建立的氯离子扩散系数预测方法的有效性.该预测方法可广泛适用于采用不同胶凝材料体系配制的水泥基体氯离子扩散系数计算,为准确预测混凝土中的氯离子传输扩散过程提供了新的途径.
氯离子扩散系数对水泥基材料耐久性的设计与分析至关重
水泥基体作为典型的多孔介质,其孔隙结构呈现出复杂的非均质性与多尺度性:本征单元堆积形成纳米孔,水化产物和未水化颗粒堆积形成微米
本文提出一种利用多尺度分形模型和Maxwell公式预测水泥基体氯离子扩散系数的方
为验证提出方法的适用性,试验制备了3组含矿粉的水泥净浆作为基体样品,其配合比如

图1 水泥基体的压汞测试数据
Fig.1 MIP test data of cement paste

图2 水泥基体的氯离子电迁移测试数据
Fig.2 RCM test data of cement paste
描述非完美分形特征的理论工具主要有多重分形(Multifractal)和多尺度分形(Multiscale fractal
(1) |

图3 多尺度分形模型示意图
Fig.3 Schematic diagram of multiscale fractal model
相应地,按照孔隙尺寸由大到小计算的累计孔隙率(f(li))满足:
(2) |
或者:
(3) |
模型参数L、n、i、bi可由MIP数据通过数值分析确
非均匀介质的有效传输系数求解问题由来已

图4 关于Maxwell公式计算有效扩散系数的示意图
Fig.4 Schematic diagram of Maxwell equation to compute effective diffusion coefficient
(4) |
式中:σ为有效传输系数;ε为分散相的体积分数.
由于实际非均匀介质的组分与结构复杂多变,例如分散相的形状不一定是球体、分散相之间可能相互作用、分散相的体积分数不满足稀释极限条件等,导致Maxwell公式的计算值与实际值通常存在较大的偏差,即Maxwell公式难以直接作为预测非均匀介质有效传输系数的理论工
对照Maxwell公式和多尺度分形模型,可将孔隙相、迭代相分别视为分散相、连续相,且分散相的体积分数εi≡1-xi.由于使用迭代方法构建孔隙结构,即在实质上按孔隙尺寸对孔隙结构逐项分解,导致多尺度分形模型的迭代元自然满足εi1.研究表明,当分散相的体积分数满足稀释极限条件时,即ε1,分散相的形状和相互作用可以忽略,Maxwell公式的计算值与实际值相一致.在此角度看,多尺度分形模型和Maxwell公式具有很好的适配性.针对水泥基体的孔隙结构由i次迭代构建,相应的氯离子扩散系数也可由Maxwell公式经i次迭代计算得到.
根据MIP测试结果,水泥基体的多尺度分形模型参数的数值分析结果如

图5 水泥基体(WB030SLAG20)模拟孔隙结构的可视化
Fig.5 Visualization of modeled pore structure in cement paste (WB030SLAG20)

图6 水泥基体的孔径分布曲线测试结果与模拟结果对比
Fig.6 Comparison of pore size distribution between measured and modeled data for cement pastes
应用Maxwell公式计算水泥基体的氯离子扩散系数,需要给定5 nm孔隙相和5 nm迭代相的氯离子扩散系数.分子动力学模拟表明,氯离子在孔隙中的扩散系数受孔隙尺寸的影

图7 氯离子在5 nm孔隙中的扩散系数
Fig.7 Chloride diffusivity in 5 nm‑sized pore

图8 水泥基体的氯离子扩散系数实测值(电迁移法)与预测值对比
Fig.8 Comparison of chloride diffusivity between measured(RCM) and predicted data for cement paste
当前联合多尺度分形模型和Maxwell公式的方法主要考虑的是氯离子在水泥基体中的扩散性能,不包含物理吸附、化学胶结等其他传输过程,因此也是以RCM测试结果作为参照.Garboczi
(1)多尺度分形模型可以准确重构水泥基体的孔隙结构,与压汞法测得的累计孔隙体积吻合度较高.
(2)针对当前使用的水泥矿粉胶凝材料体系,多尺度分形模型中本征单元的氯离子扩散系数为4.25×1
(3)多尺度分形模型和Maxwell公式具有很好的适配性,二者联合可用于具有多相、多尺度孔隙结构的硬化水泥石中的介质传输过程.本文建立的根据孔隙结构数据预测硬化水泥石基体氯离子扩散系数的方法,原则上适用于广泛的胶凝材料体系.
参考文献
ZHENG J J, ZHOU X Z. Effective medium method for predicting the chloride diffusivity in concrete with ITZ percolation effect[J]. Construction Building Materials, 2013, 47:1093‑1098. [百度学术]
LIU Q F, EASTERBROOK D, YANG J, et al. A three‑phase, multi‑component ionic transport model for simulation of chloride penetration in concrete[J]. Engineering Structures, 2015, 86:122‑133. [百度学术]
TONG L, GJORV O E. Chloride diffusivity based on migration testing[J]. Cement and Concrete Research, 2001, 31(7):973‑982. [百度学术]
HE Z X, SHI C J, HU X, et al. Development on migration characteristic and interactions of chloride ion in cement‑based materials under applied voltage[J]. Journal of the Chinese Ceramic Society, 2015, 43(8):1111‑1119. [百度学术]
HOU D S, LI Z J. Molecular dynamics study of water and ions transported during the nanopore calcium silicate phase:Case study of jennite[J]. Journal of Materials in Civil Engineering, 2014, 26(5):930‑940. [百度学术]
MA H Y, HOU D S, LI Z J. Two‑scale modeling of transport properties of cement paste:Formation factor, electrical conductivity and chloride diffusivity[J]. Computational Materials Science, 2015, 110:270‑280. [百度学术]
LIU Z Y, CHEN W W, ZHANG Y S, et al. A three‑dimensional multi‑scale method to simulate the ion transport behavior of cement‑based materials[J]. Construction Building Materials, 2016, 120:494‑503. [百度学术]
GAO Y, JIANG J Y, WU K. Modeling of ionic diffusivity for cement paste with solid mass fractal model and lattice Boltzmann method[J]. Journal of Materials in Civil Engineering, 2017, 29(5):1‑10. [百度学术]
JENNINGS H M, BULLARD J W, THOMAS J J, et al. Characterization and modeling of pores and surfaces in cement paste:Correlations to processing and properties[J]. Journal of Advanced Concrete Technology, 2008, 6(1):5‑29. [百度学术]
JI X, CHAN S Y N, FENG N. Fractal model for simulating the space‑filling process of cement hydrates and fractal dimensions of pore structure of cement‑based materials[J]. Cement and Concrete Research, 1997, 27(11):1691‑1699. [百度学术]
PIA G, SANNA U. A geometrical fractal model for the porosity and thermal conductivity of insulating concrete[J]. Construction and Building Materials, 2013, 44:551‑556. [百度学术]
GAO Y, WU K, JIANG J Y. Examination and modeling of fractality for pore‑solid structure in cement paste:Starting from the mercury intrusion porosimetry test[J]. Construction and Building Materials, 2016, 124:237‑243. [百度学术]
PAVLIN M, SLIVNIK T, MIKLAVCIC D. Effective conductivity of cell suspensions[J]. IEEE Transactions on Biomedical Engineering, 2002, 49(1):77‑80. [百度学术]
VALENTINI L, ARTIOLI G, VOLTOLINI M, et al. Multifractal analysis of calcium silicate hydrate(C‑S‑H) mapped by X‑ray diffraction microtomography[J]. Journal of American Ceramic Society, 2012, 95(8):2647‑2652. [百度学术]
GAO Y, WU K, YUAN Q. Limited fractal behavior in cement paste upon mercury intrusion porosimetry test:Analysis and models[J]. Construction and Building Materials, 2021, 276:122231. [百度学术]
TRAN B V. A simple model to predict effective conductivity of multicomponent matrix‑based composite materials with high volume concentration of particles[J]. Composites Part B:Engineering, 2019, 173:106997. [百度学术]
TIAN W L, FU M W, QI L H, et al. Micro‑mechanical model for the effective thermal conductivity of the multi‑oriented inclusions reinforced composites with imperfect interfaces[J]. International Journal of Heat and Mass Transfer, 2020, 148:119167. [百度学术]
CLARK C L, WINTER C L, CORLEY T. Effects of percolation on the effective conductivity of irregular composite porous media[J]. Advances in Water Resources, 2020, 137:103507. [百度学术]
KERISIT S, LIU C. Molecular simulations of water and ion diffusion in nanosized mineral fractures[J]. Environmental Science and Technology, 2009, 43:777‑782. [百度学术]
GARBOCZI E J, BENTZ D P. Computer simulation of the diffusivity of cement‑based materials[J]. Journal of Materials Science, 1992, 27(8):2083‑2092. [百度学术]