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Abstract

Summary

Within the EraMin 3 project “Artificial Intelligence Characterization Ornamental Stones Quarry Optimization (AI-COSTSQO)” we completed the following work stages: field measurements, identification of discrete fracture network (DFN) in marble quarries and determination of Block Size Distribution Curves (BSDC). In this paper we present examples from each stage of work. Thus, we started with non-destructive geophysical methods (GPR -Ground penetration radar, electrometry and seismic) in the Ruschita, Pietroasa, Carpinis, Botticino and Finike quarries. These contain fractures with various characteristics that negatively influence the quality of the extracted blocks. The Discrete Fracture Network (DFN) was the next step, after interpreting the results of the geophysical measurements, and simulates the distribution of natural fractures in a 3D model. Finally, we presented BSDC and Commercial Boundaries, which represents the preliminary result for the input data in the AI-based software program for the optimization of quarry exploitation.

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/content/papers/10.3997/2214-4609.202449BGS21
2024-05-28
2026-02-15
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References

  1. Wenli, Y., Sharifzadeh, M., Zhen, Y. (2020). Assessment of block size distribution in fractured rock mass and its influence on rock mass mechanical behavior. AIP Advances10, 035124; doi: 10.1063/1.5143906, 10p
    https://doi.org/10.1063/1.5143906 [Google Scholar]
  2. Arpaslan, T., Erkan, U. (2014). Using the distribution curves to optimize the block exploitation in natural stone quarries. Rock Engineering and Rock Mechanics: Structures in and on Rock Masses, Alejano, Perucho, Olalla & Jimenez (Eds) © 2014 Taylor & Francis Group, London, 978-1-138-00149-7 https://fractorylab.org/dfnlab-software/http://ai-costsqo-project.com/
    [Google Scholar]
/content/papers/10.3997/2214-4609.202449BGS21
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