Assessment of models to predict surface subsidence in the Czech part of the Upper Silesian Coal Basin - Case study

0535483 - ÚGN 2021 RIV CZ eng J - Journal Article
Jiránková, Eva - Waclawik, Petr - Němčík, J.
Assessment of models to predict surface subsidence in the Czech part of the Upper Silesian Coal Basin - Case study.
Acta geodynamica et geomaterialia. Roč. 17, č. 4 (2020), s. 469-484. ISSN 1214-9705. E-ISSN 2336-4351
Institutional support: RVO:68145535
Keywords : longwall mining * surface subsidence * great depth * finite element method * Knothe method
OECD category: Mining and mineral processing
Impact factor: 1.176, year: 2020
Method of publishing: Open access
https://www.irsm.cas.cz/materialy/acta_content/2020_doi/Jirankova_AGG_2020_0034.pdf

This case study presents the verification of two surface subsidence prediction models for longwallmining at depths greater than 400 m. The surface subsidence points were surveyed and comparedfor both models. The first model uses empirical calculations to predict the surface subsidence. This method is reliable for predicting surface subsidence at shallower depths. At present, however, coalmining has progressed to great depths. The second model is the 2-dimensional finite elementmethod to predict surface subsidence. In contrast to the first method, this method is based on the regional parameters and uses the rock mass properties to evaluate surface subsidence for multi-seams at any depth. Results show that the finite element method gives a better approximation ofthe measured surface subsidence than the Knothe method. The maximum surface subsidence,which was determined by the FEM method, was used to adjust the extraction coefficient in theKnothe's method. The predicted value differs from the measured value by 8 %. The slope ofthe predicted subsidence trough was within the range of 2‒8 % from the surveyed subsidence. This case study proposes a procedure for using both models to successfully predict the surface subsidence.
Permanent Link: http://hdl.handle.net/11104/0313494