泵送混凝土可泵性评价

发布时间：2019-06-13 14:40

【摘要】：泵送混凝土施工工艺是目前最常采用的施工方法之一,其施工质量的好坏关系重大。但是目前一些地方的施工对泵送混凝土配合比设计不够精确,在一些特殊地区配合比的设计仍然循规蹈矩,致使工程事故频发。另外,泵送剂并不是灵丹妙药,在特殊环境中泵送剂的性能会发生某些改变,这些问题都是急需要研究与解决的。本文以解决上述问题为基本出发点,通过建立可泵性的评价指标,以可泵性优劣为评价标准,以配合比要素为参数,来求解配合比各个要素的可泵性范围。正交试验法以C50泵送混凝土为研究对象,研究了C50泵送混凝土的坍落度、扩展度、倒坍时间、压力泌水率、容重、7d劈拉强度、28d劈拉强度、7d抗压强度、28d抗压强度等指标的主要影响因素,并且得到了各个因素与指标之间的增减关系,估计边缘均值图给出了各个因素之间的交互作用,最终确定了C50泵送混凝土在满足强度前提下达到最佳可泵性的配合比。另外,本文使用了统计学软件SPSS对试验结果给出了完整的数学分析。在回归分析中,通过对试验结果的拟合,得出了C50泵送混凝土坍落度、扩展度、倒坍时间、压力泌水率、容重、7d劈拉强度、28d劈拉强度、7d抗压强度、28d抗压强度线性回归公式,这对于今后同类问题的解决提供了一条快速、简便的研究方法。在使用BP神经网络预测时,本文选取了C50泵送混凝土的28d抗压强度为预测指标,将通过回归方程得到的28d抗压强度作为实测值进行预测,预测误差不大,这说明该模型是可行的。因此,该模型也可以用来预测其它强度等级的泵送混凝土指标,再结合泵送混凝土的可泵性评价体系,就可以评价任何强度等级泵送混凝土的可泵性。
[Abstract]:Pumping concrete construction technology is one of the most commonly used construction methods at present, and its construction quality is of great importance. However, at present, the design of pumping concrete mix ratio is not accurate enough in some places, and the design of mix proportion in some special areas is still in accordance with the rules, resulting in frequent engineering accidents. In addition, pumping agent is not a panacea, the performance of pumping agent will change in special environment, these problems need to be studied and solved urgently. In this paper, to solve the above problems as the basic starting point, by establishing the evaluation index of pump ability, taking the pump performance as the evaluation standard, and taking the mix proportion element as the parameter, the pumping range of each element of the mix proportion is solved. Taking C50 pumping concrete as the research object, the main influencing factors of slump, expansion, collapse time, pressure bleeding rate, bulk density, 7 d split tensile strength, 28 d split tensile strength, 7 d compressive strength and 28 d compressive strength of C50 pumped concrete are studied by orthogonal test, and the relationship between each factor and index is obtained, and the interaction between each factor is given by the estimated edge mean diagram. Finally, the mixture proportion of C 50 pumping concrete to meet the strength is determined. In addition, the statistical software SPSS is used to give a complete mathematical analysis of the test results. In regression analysis, the linear regression formulas of slump, expansion, collapse time, pressure bleeding rate, bulk density, 7 d split tensile strength, 28 d split tensile strength, 7 d compressive strength and 28 d compressive strength of C50 pumping concrete are obtained by fitting the test results, which provides a rapid and simple research method for solving the same problems in the future. When using BP neural network to predict, the 28d compressive strength of C50 pumping concrete is selected as the prediction index, and the 28d compressive strength obtained by regression equation is used as the measured value to predict, and the prediction error is small, which shows that the model is feasible. Therefore, the model can also be used to predict the pumping concrete index of other strength grades, and combined with the pumping performance evaluation system of pumping concrete, the pumping performance of any strength grade pumping concrete can be evaluated.
【学位授予单位】：河北工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TU528

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