Computational Geosciences

, Volume 14, Issue 1, pp 83–103 | Cite as

Computation of influence functions for automatic mining subsidence prediction

  • M. E. Díaz-Fernández
  • M. I. Álvarez-Fernández
  • A. E. Álvarez-Vigil
Original paper

Abstract

This paper presents a computer tool that automatically predicts mining subsidence using the generalized n-k-g influence function detailed in (González Nicieza et al. Int J Rock Mech Min Sci 42(3):372–387, 2005). This function depends on two physical concepts: the first is gravity, which characterizes the forces acting on the ground, and the second, the convergence of the roof and floor of the mine workings due to the stress state of the ground. The developed tool also allows other influence functions to be used to predict subsidence, namely the spatial influence function (Ramírez Oyanguren et al. 2000) and the normal-type classical (Knothe, Arch Gór Hut 1, 1952) and modified (González Nicieza et al. Bull Eng Geol Environ 66(3):319–329, 2007) time functions. Moreover, the inputting and periodic updating of data from subsidence monitoring surveys is controlled by one of the tool’s modules using a method that minimizes errors resulting from time discontinuities in landmarks measurements. In addition, when actual landmarks measurements exist, the developed tool allows calibration of the subsidence parameters, minimizing the errors between actual measurements and those obtained by prediction. The tool includes a viewer, developed using OpenGL, which enables the results of the calculations carried out to be viewed, allowing the point of view to be varied. It also includes the option of viewing and saving the results of the calculations carried out over the original topographic plane defined in the AutoCAD DXF data file format. The efficacy of the tool is demonstrated via its application to a real case of mining work carried out in a village in the Principality of Asturias, Spain.

Keywords

Computer tool Mining Subsidence Prediction Influence functions 

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Copyright information

© Springer Science+Business Media B.V. 2009

Authors and Affiliations

  • M. E. Díaz-Fernández
    • 1
  • M. I. Álvarez-Fernández
    • 2
  • A. E. Álvarez-Vigil
    • 3
  1. 1.Department of Computing, Polytechnic School of EngineeringUniversity of OviedoGijónSpain
  2. 2.Department of Mining Engineering, Mining Engineering SchoolUniversity of OviedoAsturiasSpain
  3. 3.Department of Mathematics, Mining Engineering SchoolUniversity of OviedoAsturiasSpain

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