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Sensitivity Analysis of Microstructure Parameters and Mechanical Strength during Consolidation of Cemented Paste Backfill

机译:粘结粘贴回填过程中微观结构参数和机械强度的敏感性分析

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摘要

Parameter sensitivity is an important part of the quantitative model uncertainty, which helps to effectively identify the key parameters, reduce the uncertainty of the parameters, and then improve the efficiency of parameter optimization. In order to accurately and intuitively analyze the influence of the microscopic parameters and the mechanical response of consolidation process of cemented paste backfill (CPB), a method is used to characterize the geometric and morphological features of the CPB. In this paper, digital image processing technology is used to propose a method for the identification and quantitative analysis of microscopic pore images based on CPB. The pore images on the microscopic scale of CPB are obtained by the microscopic analysis of SEM images, binarization, denoising, and other operations; further, several microscopic parameters are calculated on the pore image, such as the porosity, uniformity coefficient, fractal dimension, probability entropy, and other quantitative parameters, realizing quantitative analysis of pore images. The microstructure of pore images of CPB is extracted under different curing times and then the parameter sensitivity between the microstructure parameters and the mechanical response based on the finite-difference method is analyzed. Set microstructure parameter software of consolidation process of CPB is developed based on this idea, which can be used to identify microscopic pore images and analyze the morphology quantitatively. The microcosmic parameters of CPB with strong sensitivity are uniformity coefficient, average shape coefficient, sorting coefficient, fractal dimension, average length of long axis, average pore area, weighted probability entropy, pore number, and porosity. The sensitivity of the remaining parameters is relatively low. Therefore, the CPB is preferably used in the strength testing process. The method provides a new method for the quantitative analysis of parameter sensitivity on the microscale of CPB.
机译:参数灵敏度是定量模型不确定性的重要组成部分,有助于有效地识别关键参数,降低参数的不确定性,然后提高参数优化的效率。为了准确和直观地分析微观参数的影响和固结浆料回填(CPB)的固结过程的机械响应,方法用于表征CPB的几何和形态特征。在本文中,数字图像处理技术用于提出基于CPB的微观孔隙图像的识别和定量分析的方法。通过SEM图像,二值化,去噪和其他操作的微观分析来获得CPB微观规模的孔隙图像;此外,在孔隙图像上计算若干微观参数,例如孔隙率,均匀系数,分形尺寸,概率熵和其他定量参数,实现了对孔图像的定量分析。分析了CPB孔隙图像的微观结构在不同的固化时间内提取,然后分析了基于有限差分法的微结构参数与机械响应之间的参数灵敏度。设置CPB的整合过程的组织参数软件是基于该想法开发的,可用于识别微观孔隙图像并定量分析形态。 CPB的微观参数具有强敏感性的均匀系数,平均形状系数,分选系数,分形尺寸,长轴的平均长度,平均孔面积,加权概率熵,孔数和孔隙率。剩余参数的灵敏度相对较低。因此,CPB优选用于强度测试过程。该方法提供了一种新方法,用于定量分析CPB的微观尺寸的参数灵敏度。

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