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Optimization of support parameters for reusable mining excavations based on a neuro-heuristic prognostic model

Babets Dmytro, Sdvyzhkova Olena, Dyczko Artur, Gliwiński Łukasz

Mining Machines

2023

vol. 41, iss. 3

200--211

This publication delves into geomechanical processes encountered during sequential longwall mining of coal seams, with a unique focus on reusing the conveyor track of the prior longwall as the ventilation pathway for the subsequent longwall. An in-depth geomechanical rationale is provided for the reuse of excavations within jointed rock formations.To ascertain the critical roles played by various support and protective elements at each distinct mining stage, a comprehensive analysis is performed using finite element techniques to delineate thethree-dimensional stress-strain characteristics of the rock mass.Employing an innovative methodology integrating multifactorial analysis, contemporary structural identification algorithms, and a neuro-heuristic approach for predictive mathematical modeling, an integral stability metric for reusable mining excavations isintroduced. Specifically, this metric quantifies the relative preservation of theexcavation's cross-sectional area following its connection to thesecond longwall.Furthermore, the study tackles the challenge of nonlinear optimization through the application of the generalized reduced gradient method (Frank-Wolfe), ultimately deriving the optimal combination of factors that maximizes the preservation of the cross-sectional area for these reusable excavations.