基于骨料形貌参数修正的可压缩堆积模型及其在混凝土材料中的应用研究

发布时间：2018-05-01 10:05

本文选题：可压缩堆积模型 + 堆积密实度　；参考：《深圳大学》2017年硕士论文

【摘要】：颗粒堆积理论在医学制药、陶瓷工艺、粉末冶金等不同材料应用领域被广泛地用于进行经济分析和优化,近年来也将其应用于混凝土材料的优化设计中,尤其是被众多研究者认可的可压缩堆积模型(Compressible Packing Model,简称CPM模型)。但目前颗粒堆积模型的应用技术仍处于试验研究阶段,尚未形成较为完善的适用于混凝土材料设计的应用理论,系统研究颗粒堆积模型在绿色生态混凝土中的应用理论及设计方法,将有利于低水泥用量绿色混凝土在混凝土工程中的健康、可持续发展。通过国内外文献的查阅,对已有的颗粒堆积模型发展进行了综述,通过分析研究表明,在这些颗粒堆积模型的理论推导中,均没有直接考虑到颗粒形貌特性对颗粒体系堆积密实的影响,这也是利用颗粒堆积模型对混合料颗粒体系堆积密实度的预测值与实验值间存在一定差异的主要原因之一。因此,本课题着重对骨料颗粒形貌特性进行研究,并对CPM模型中的作用效应系数进行优化和完善,以进一步提高CPM模型预测混合料颗粒体系堆积密实度的精确性。首先,从已有的颗粒形貌特征参数量化指标中选取8个最具有代表性的量化参数指标(扁平度、针状度、分形维数、凸形度、球形度、形状因子、棱角性和圆形度)并对其进行系统分析,然后采用数字图像分析处理技术(Image Pro-Plus,简称IPP)对选取的骨料样品颗粒进行图像处理,以提取与这8个颗粒形貌量化指标有关的参数。同时,为了验证这些量化参数指标的合理可行性,研究了这8个形貌特征量化参数指标与混合颗粒体系堆积密实度的关联性,结果表明,除了形状因子量化参数指标外,其它7个量化参数指标与颗粒体系堆积密实度的相关性都较高。其次,基于可压缩堆积模型的理论推导和发展及前期对骨料颗粒形貌特征研究,选取球形度和棱角性这两个参数作为修正和完善CPM模型中松动效应和附壁效应的最佳量化形貌参数指标,结合数值回归分析的方法,提出了两个与骨料颗粒形貌特性相关的形貌函数。最后,利用修正后的CPM模型对三元混合料颗粒体系进行了研究,并比较CPM修正模型和CPM模型分别对三元混合颗粒体系堆积密实度预测值与实验值的相对误差,以验证CPM修正模型对混合颗粒体系堆积密实度预测的精确性,同时结合工作性能预测模型和力学性能预测模型以更进一步地验证CPM修正模型的有效可行性和精准性,为后续研究CPM修正模型对混凝土混合材料进行优化设计奠定基础;根据对CPM修正模型在混凝土中的应用研究,推荐了一种基于CPM修正模型的绿色混凝土的性能优化设计方法,是推动具有良好综合性能的低碳绿色混凝土经济可持续发展的前进动力。
[Abstract]:Particle accumulation theory is widely used for economic analysis and optimization in the fields of medical pharmacy, ceramic technology, powder metallurgy and so on. In recent years, it has also been applied to the optimization design of concrete materials. In particular, the compressible Packing Model (CPM Model), which has been recognized by many researchers, is also known as Compressible Packing Model. However, the application technology of particle accumulation model is still in the stage of experimental study, and a relatively perfect application theory for concrete material design has not yet been formed. A systematic study on the application theory and design method of particle accumulation model in green ecological concrete will be beneficial to the healthy and sustainable development of green concrete with low cement content in concrete engineering. Through the reference of domestic and foreign literature, the development of existing particle stacking models is summarized. The analysis and research show that, in the theoretical derivation of these particle stacking models, The effect of particle morphology on particle compactness is not considered directly, which is one of the main reasons for the difference between the prediction value and experimental value of particle compactness by particle accumulation model. Therefore, this paper focuses on the study of aggregate particle morphology, and the optimization and improvement of the action effect coefficient in CPM model, in order to further improve the accuracy of CPM model in predicting the compactness of mixture particle system. Firstly, eight most representative quantization parameters (flatness, acicular degree, fractal dimension, convexity, globality, shape factor) are selected from the existing quantization index of particle morphology characteristic parameters, which include: flatness, acicular degree, fractal dimension, convexity, globality, shape factor. Then, image Pro-Plus (IPP) was used to process the selected aggregate particles to extract the parameters related to the quantitative indexes of the eight particles. At the same time, in order to verify the feasibility of these quantitative parameter indexes, the correlation between the eight morphologic characteristic quantization parameters and the stacking density of mixed particle system is studied. The results show that, except for the shape factor quantization parameter index, The correlation between the other seven quantitative parameters and the density of particle system is high. Secondly, based on the theoretical derivation and development of compressible stacking model and previous studies on the morphology of aggregate particles, Two parameters, sphericity and prism, are selected as the best quantitative morphologic parameters to modify and perfect the loosening effect and the wall attachment effect in the CPM model, and the numerical regression analysis method is used. Two morphology functions related to the morphology characteristics of aggregate particles were proposed. Finally, the modified CPM model is used to study the particle system of ternary mixture, and the relative errors between the CPM modified model and the CPM model are compared between the prediction value and the experimental value of the piling density of the ternary mixture particle system, respectively. In order to verify the accuracy of the CPM modified model for predicting the stacking compactness of the mixed particle system, combined with the working performance prediction model and the mechanical performance prediction model, the validity and accuracy of the CPM modified model can be further verified. It lays a foundation for the further study on the optimization design of concrete mixed material with CPM modified model, and recommends a performance optimization design method of green concrete based on CPM modified model according to the application of CPM modified model in concrete. It is the driving force to promote the sustainable development of low carbon green concrete economy with good comprehensive performance.
【学位授予单位】：深圳大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TU528

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