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Related Concept Videos

Quarrying of Stone01:15

Quarrying of Stone

Quarrying is the process of extracting stone from a quarry, where specialized techniques are employed to remove large blocks of stone safely and efficiently. This process can involve controlled explosions or more precision-oriented methods such as cutting and drilling.
One common method involves using a diamond belt saw to cut large blocks from the quarry face. These blocks can be about 50 feet long and 12 feet high. After the initial vertical cut, drilling is performed at the base of the block.
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Microcracking in concrete refers to the tiny cracks that can form within the material even before any external load is applied. These microcracks typically occur at the interface between the coarse aggregate and the hydrated cement paste, often as a result of differential volume changes prompted by variations in stress-strain behavior, as well as thermal and moisture movement. Initially, these microcracks remain stable and do not grow substantially until the concrete is stressed to about 30...

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Related Experiment Video

Updated: Jul 1, 2026

Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
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An Enhanced RIME Optimizer with Horizontal and Vertical Crossover for Discriminating Microseismic and Blasting

Wei Zhu1, Zhihui Li1, Ali Asghar Heidari2

  • 1School of Resources and Safety Engineering, Central South University, Changsha 410083, China.

Sensors (Basel, Switzerland)
|November 14, 2023
PubMed
Summary

This study introduces a novel algorithm (CCRIME) and its binary variant (BCCRIME) for optimizing rock stability monitoring in mining. The BCCRIME-FKNN model effectively predicts rock mass stability using real-world data.

Keywords:
RIMEblastingfeature selectionmachine learningmicroseismicswarm intelligence

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Area of Science:

  • Mining Engineering
  • Computational Intelligence
  • Geotechnical Engineering

Background:

  • Real-time monitoring of rock stability is crucial for safe and efficient mining operations.
  • Existing algorithms may require enhancement for improved solution quality and search capabilities in complex mining environments.

Purpose of the Study:

  • To develop and validate an enhanced optimization algorithm for real-time rock stability monitoring.
  • To optimize parameters for a classification model using the proposed algorithm.
  • To assess the model's performance on benchmark functions and real-world mining data.

Main Methods:

  • Proposed a Cross-over RIME (CCRIME) algorithm with enhanced search strategies.
  • Developed a binary version (BCCRIME) for parameter optimization via binary conversion.
  • Utilized an S-shaped function for feature selection in BCCRIME.
  • Optimized Fuzzy K-Nearest Neighbors (FKNN) parameters using BCCRIME.
  • Validated performance using IEEE CEC2017 benchmark functions and real microseismic/blasting data.

Main Results:

  • The CCRIME algorithm demonstrated improved solution quality and search capabilities.
  • The BCCRIME-FKNN model achieved effective classification prediction on real mining data.
  • Comparative experiments confirmed the efficacy of the proposed algorithms over basic and variant approaches.

Conclusions:

  • The BCCRIME-FKNN model offers a robust solution for real-time rock mass stability monitoring in deep well mining.
  • The developed algorithms provide novel computational approaches for geotechnical and mining applications.
  • This research contributes to enhanced safety and resource extraction through advanced data analysis.