秸秆灰混凝土力学性能试验及强度预测

发布时间：2018-01-11 14:06

本文关键词：秸秆灰混凝土力学性能试验及强度预测　出处：《农业工程学报》2017年02期 　论文类型：期刊论文

【摘要】：为了优化混凝性能,减少水泥产业耗能,尝试采用以部分秸秆灰替代水泥制备混凝土。该文通过试验对油菜秸秆灰混凝土拉压性能进行了研究,得到秸秆灰质量分数和水胶比对秸秆灰混凝土拉压性能的影响规律,如当秸秆灰质量分数增大时,混凝土拉压性能呈下降趋势;当水胶比过大时,混凝土力学性能急剧下降。同时提出秸秆灰混凝土抗拉性能与抗压性能间的线性函数关系以及混凝土轴心抗压强度计算公式,并与其他混凝土抗压强度公式进行比对验证。采用小波神经网络的预测方法,引入随机函数,对试验数据抽样进行训练,而后预测数据并与试验数据进行比对,计算误差,并将预测数据用于该文提出的拉压公式进行验证,结果表明验证较好。最后试验结果表明:当秸秆灰替代掺量为10%时,秸秆灰混凝土劈裂抗拉强度下降了25%,抗压强度仅下降了8%;当替代掺量为20%时,抗压强度下降了31%。
[Abstract]:In order to optimize the coagulation performance, reduce the energy consumption of cement industry, using the part of straw ash instead of cement concrete preparation. This paper through the test of rape straw ash concrete compressive and tensile properties were obtained, effect of straw ash content and water cement ratio on the straw ash concrete tensile and compressive properties, such as when the straw ash mass fraction with the increase of concrete compressive and tensile properties decreased; when the water cement ratio is too large, the mechanical properties of concrete decreased rapidly. At the same time the linear relationship between the straw ash concrete tensile properties and compressive properties and concrete compressive strength calculation formula, and compared with other verification concrete compressive strength formula. Using the prediction method wavelet neural network, random function training on test data sampling, and forecast data and compared with the experimental data, the calculation error, and the pre The data for the proposed tension formula was verified. The result shows that the verification is better. Finally, experimental results show that: when the substitution of straw ash content is 10%, the straw ash concrete splitting tensile strength decreased by 25%, its compressive strength is decreased by 8%; when the substitution content is 20%, the compressive strength decreased 31%.

【作者单位】：中南大学防灾科学与安全技术研究所;湖南农业大学工学院;
【基金】：国家科技支撑计划课题资助(2014BAK17B02和2014BAK17B03)
【分类号】：TU528
【正文快照】： 张强,李耀庄,刘保华,徐志胜.秸秆灰混凝土力学性能试验及强度预测[J].农业工程学报,2017,33(2):259-265.doi:10.11975/j.issn.1002-6819.2017.02.036 http://www.tcsae.orgZhang Qiang,Li Yaozhuang,Liu Baohua,Xu Zhisheng.Mechanical properties and strength prediction of

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