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Microscopic Parameter Extraction and Corresponding Strength Prediction of Cemented Paste Backfill at Different Curing Times

Author(s):




Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2018
Page(s): 1-9
DOI: 10.1155/2018/2837571
Abstract:

To accurately and intuitively study the influence of microscopic parameters and mechanical responses of the consolidation process of cemented paste backfill (CPB), a method is proposed for characterizing its geometric and morphological characteristics and its mechanical response. A set of microstructure parameter software is developed for analyzing the CPB consolidation process, which quantitatively analyzes the mechanical response of CPBs at a microscopic scale. Based on the fuzzy clustering method, CPB microscopic pore images are extracted via digital image processing technology. Microscopic CPB pores are extracted from images via cluster analysis, binarization, and denoising techniques. Then, images are evaluated for porosity, number of pores, average pore width, fractal dimension, weighted probability entropy, and 11 more indicators to quantitatively analyze pores. Thus, the proposed method forms nonlinear relationships between microstructure parameters and mechanical responses based on a deep learning TensorFlow framework under different curing times. Results show that the multiparameter predictive mechanical response at the microscopic scale has a good effect, and the predicted average error is 9.51%. The accuracy of the proposed method is higher than that of the traditional method. Therefore, the proposed method provides a new method to quantitatively analyze the mechanical response strength prediction at a microscale.

Copyright: © 2018 Xuebin Qin et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10176622
  • Published on:
    30/11/2018
  • Last updated on:
    02/06/2021
 
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