Applied Sciences (Mar 2024)

Optimizing Retention Bunkers in Copper Mines with Numerical Methods and Gradient Descent

  • Piotr Bortnowski,
  • Robert Król,
  • Natalia Suchorab-Matuszewska,
  • Maksymilian Ozdoba,
  • Mateusz Szczerbakowicz

DOI
https://doi.org/10.3390/app14062612
Journal volume & issue
Vol. 14, no. 6
p. 2612

Abstract

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This study examines the optimization of ore receiving bins in underground copper mines, targeting the reduction of rapid wear and tear on bin components. The investigation identifies the primary wear contributors as the force exerted by the accumulated ore and the velocity at which ore particles move. By altering design and operational parameters, the objective is to decrease wear at key points such as transfer areas, thereby improving the efficiency and service life of retention bunkers. A Discrete Element Method (DEM) model of the bin was created and validated against actual mining conditions to study the impact of material flow on wear. The optimization approach used a constrained gradient descent algorithm to minimize factors like particle velocity and pressure force, while maintaining the efficiency of the bin. The findings provide valuable insights for the future design enhancements, potentially improving the operational performance of retention bunkers in the mining industry.

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