Sensitivity Analysis of Microstructure Parameters and Mechanical Strength during Consolidation of Cemented Paste Backfill
Xuebin Qin,
Pai Wang,
Lang Liu,
Mei Wang and
Jie Xin
Mathematical Problems in Engineering, 2018, vol. 2018, 1-9
Abstract:
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.
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:5170721
DOI: 10.1155/2018/5170721
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