橡胶集料混凝土渗透性能研究
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摘要
橡胶集料混凝土(砂浆)作为一种新型混凝土(砂浆)材料,已有的研究结果表明,其具有低弹模、大变形、高阻尼、能量耗散多及很好的抗裂性等诸多优点。在橡胶集料混凝土表现出良好的力学性能下,对橡胶集料混凝土的抗渗性,抗冻性,耐腐蚀性等混凝土的耐久性研究就很有必要。本文对橡胶集料混凝土的抗渗性能进行了初步研究。通过对掺入较高比例的橡胶集料混凝土(最高可达150kg/m3)进行的抗渗试验,分析较高掺量的橡胶集料混凝土的抗渗性能。
     为研究橡胶微粒对混凝土渗透性的影响以及各种类型混凝土的强度与渗透性之间的关系,作者测试了不同橡胶微粒掺量的普通混凝土与粉煤灰混凝土,不同水灰比的橡胶混凝土的渗透性。以橡胶取代砂石,橡胶微粒的掺量(体积比)分别为0、5%、10%、15%,即每立方米中橡胶微粒的含量。试验结果表明,实验所用的橡胶集料混凝土的抗渗性能较普通混凝土有较大的提高。其中掺量为5%的一组橡胶集料混凝土的抗渗性能较好。
     讨论了橡胶集料混凝土的渗透性与强度之间的关系,橡胶集料混凝土的渗透性能与其强度仍具有一定的线性相关性。并对橡胶集料在改变混凝土的微观孔结构,阻止液体渗入混凝土内部的机理进行了初步的探索。认为由于橡胶微粒的存在,改变了混凝土的微观孔结构,对混凝土的渗透性能产生了一定的影响。
     根据神经网络原理,建立一个3层的BP神经网络模型,通过的对试验数据的训练,得到混凝土渗透系数的拟合曲线,试验曲线和拟合曲线对比较好的反映了橡胶集料混凝土渗透性的变化规律。
Crumb Rubber Concrete (CRC) or Mortar (CRM) is a new type of concrete or mortar with the characteristics of low Young’s Modulus, large deformation, high energy dissipation and great crack resistance. It is necessary to study the permeability of Crumb Rubber Concrete. The primary study on permeability of Crumb Rubber Concrete was included .The permeability of Crumb Rubber Concrete was analyzed by the study on permeability of Crumb Rubber Concrete with more crumb rubber (max to 150kg/m3).
     Because I want to know influence on permeability of Crumb Rubber Concrete and the relation between the intensity of pressure and permeability of Crumb Rubber Concrete. The rubber replaces the stone and sand. And the rubber motes’volume ratio is 0、5%、10%、15%, is the contents of rubber mote in every stere. The outcome of the study indicated the resistance to permeation of Crumb Rubber Concrete is improved remarkably. And the 5% Crumb Rubber Concrete has better permeability.
     It was discussed that the correlation between permeability and compressive strength of Crumb Rubber Concrete. And have a primary research on the microstructure of Crumb Rubber Concrete and the mechanism of preventing liquid into concrete.
     Based on neural network, a three layers BP neural network model was given to forecast the permeability of Crumb Rubber Concrete. The model was trained according to the test date. The results show that curves obtained by BP neural network model have preferable accuracy. So it could be used to predict the permeability of Crumb Rubber Concrete.
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