【作者】 王旻；

【导师】 朱涵；

【作者基本信息】 天津大学 ， 结构工程， 2007， 硕士

【摘要】 本文针对橡胶轻集料混凝土(CRLC)的基本力学性能进行了试验研究,试验发现CRLC具有很好的变形和阻裂性能,试件破坏时表现出很好的延性特征,有别于普通混凝土的脆性破坏特征。CRLC棱柱体抗压强度与立方体的抗压强度的比值在0.7-0.8之间,小于普通轻集料混凝土的0.9-1.0,这也表明橡胶细集料的掺入可以提高轻集料混凝土的延性,降低其脆性。通过对不同橡胶细集料掺量的CL30橡胶轻集料混凝土(CRLC)的单轴受压试验,测得了其应力-应变全曲线并进行了理论分析。其应力-应变全曲线的方程可采用过镇海提出的轻集料混凝土全曲线相同的形式,但其中的系数不同。CRLC应力-应变全曲线的峰值应变、拐点应变和收敛点应变与橡胶掺量有良好的线性关系。通过对CRLC抗渗性的试验研究,发现其渗透性随橡胶含量的增加而有所增大,其中掺量为50kg/m3时,其抗渗性能最好。采用正交试验方法,研究了CRLC中水胶比、体积砂率、橡胶细集料掺量和减水剂掺量四种因素对轻集料上浮状况的影响。研究表明轻集料上浮现象随着水胶比和减水剂掺量的增大而变的严重;随着体积砂率和橡胶细集料掺量的增大,轻集料上浮现象得到改善,混凝土的匀质性变好。各因素掺量对新拌混凝土中轻集料的质量分布率的影响主次顺序为:橡胶细集料掺量>减水剂掺量>体积砂率>水胶比。基于神经网络原理,建立3层BP网络模型,以预测不同条件下轻集料在橡胶轻集料混凝土中的分布状况。根据试验训练样本数据,对该模型进行训练,建立BP网络模型系统。结果表明,基于模型系统的拟合曲线与试验曲线符合较好,能够反映混凝土中各种因素与轻集料分布状况间复杂的非线性关系,为CRLC匀质性的预测提供参考。更多还原

【Abstract】 The paper presents the experimental study which aims at characterizing the basic mechanics property of the crumb rubber lightweight concrete(CRLC). The results show that the CRLC has good capability of distortion and arrest cracks. The disfeature of CRLC is different of normal lightweight concrete’s brittleness. It shows that the crumb rubber aggregate can improve the lightweight concrete’s tractility.The stress-strain responses of CL30 with 4 levels of rubber volumes are conducted under uniaxial compression. It is shown that those responses can be graphically interpolated to well follow the model derived by Guo Zhenhai’s but with different fitting coefficients. The peak stress, convergence stress and inflection point stress vary linearly with the mixture of crumb aggregate. The water permeability tests are also preformed and the results show adding rubber crumbs help reduce water permeability.The paper presents an experimental and analytical study on the issue of aggregate separation for crumb rubber lightweight concrete (CRLC). The systematic measures are carried out to quantify the spatial distribution of lightweight aggregates, and then the particle dynamic equation and the orthogonal design method are employed, which contains four factors: w/c ratio within the range of designed compressive strength, sand rate, crumb rubber volume and water reducers, to analyze those measurements. The results show that adding crumb rubber will reduce the aggregate velocity and effectively improve the uniformity of spatial distribution of lightweight aggregates. The sequences of the significance for the four factors on the uniformity of distribution of lightweight aggregates are: crumb rubber volume, water reducers, sand rate and w/c ratio.Based on neural network , a three layers BP neural network model was given to forecast the uniformity of crumb rubber lightweight concrete (CRLC). 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 uniformity of crumb rubber lightweight concrete.更多还原