基于Monte-Carlo原理及Fuller级配理论,依据PYTHON算法及COMSOL软件建立由天然骨料、老界面区、老砂浆、新界面区及新砂浆组成的再生混凝土三维球形细观模型,模拟计算了不同骨料体积分数、老砂浆扩散系数及老砂浆厚度的再生混凝土内氯离子扩散过程,对比研究了再生混凝土抗氯离子侵蚀影响规律。研究表明:以随机理论建立的再生混凝土三维球形随机骨料模型接近真实再生混凝土细观结构,满足一般工程需要;基于该模型的氯离子细观数值模拟结果同试验结果吻合;再生骨料体积分数从10%增至30%、50%时,再生混凝土表观扩散系数分别增加了6.56%和19.43%;老砂浆扩散系数增加4倍,表观氯离子扩散系数增加19.28%;老砂浆厚度增加2倍,表观氯离子扩散系数增加8.1%,增加老砂浆的厚度和扩散系数会弱化再生混凝土抗氯离子侵蚀的能力。
Abstract
Using PYTHON algorithm and COMSOL software , we have developed a three-dimensional spherical mesoscopic model for recycled aggregate concrete (RAC) based on the Monte-Carlo principle and Fuller gradation theory. The model encompasses natural aggregate, old interface transition zones (OITZ), old mortar, new interface transition zones (NITZ), and new mortar. By simulating and calculating the chloride diffusion process in RAC with varying aggregate volume fractions, old mortar diffusion coefficients, and old mortar thickness, we have examined and compared the chloride resistance of RAC. Our research demonstrates that the three-dimensional spherical random aggregate model of RAC, established through random theory, closely resembles the actual mesostructure of RAC and fulfills the requirements of general engineering. Moreover, the mesoscopic numerical simulation results for chloride diffusion based on this model are consistent with experimental findings. Specifically, when the recycled aggregate content increases from 10% to 30% and 50%, the apparent diffusion coefficients of the recycled concrete increase by 6.56% and 19.43% respectively. Additionally, the diffusion coefficient of the old mortar is quadrupled, resulting in a 19.28% increase in the apparent chloride diffusion coefficient. Furthermore, the old mortar thickness doubles, leading to an 8.1% increase in the apparent chloride diffusion coefficient. Overall, the chloride resistance of RAC weakens as the thickness and diffusion coefficient of the old mortar increase.
关键词
再生混凝土 /
随机球形骨料 /
氯离子扩散 /
细观性能 /
数值模拟
Key words
recycled aggregate concrete /
random spherical aggregate /
chloride diffusion /
mesoscopic performance /
numerical simulation
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基金
国家自然科学基金项目(51208422);陕西省教育厅资助项目(20JS092)
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