Abstract

In this study, a C-ALS underground cavity scanner was used to detect the shapes of mining goafs. In addition, GTS software was adopted to establish a three-dimensional geological model based on the status of the stopes, geological data, and mechanical parameters of each rock mass and to analyze the roof areas of the goafs. In regard to the morphology of the study area, based on a thin plate theory and the obtained field sampling data, a formula was established for the thicknesses of the reserved protective layers in the goafs. In addition, a formula for the thicknesses of the protective layers in the curved gobs was obtained. The thickness formula of the protective layers was then successfully verified. The detection results showed that the roof shapes of the goafs in the Yuanjiacun Iron Mine were mainly arc-shaped, and the spans of the goafs were generally less than 20 m. The stability of the arc-shaped roofs was found to be greater than that of the plate-shaped roofs. Therefore, by reducing the thicknesses of the protective layers in mining goafs, the ore recovery rates can be increased on the basis of safe production conditions. The formula of the thickness of the security layers obtained through the thin plate theory was revised based on the statistical results of the roof shapes of the goafs and then combined using GTS and FLAC3D. The modeling method successfully verified the stability of the mined-out areas. It was found that the verification results were good, and the revised formula was able to improve the recovery rate of the ore under the conditions of meeting safe production standards. Also, it was found that the revised formula could be used in the present situation. At the same time, it was also determined that the complexity of the rock masses obstructed the full identification of the joints and fissures in the present orebodies. Therefore, it is necessary to incorporate C-ALS underground cavity scanners to regularly observe the shapes of the goafs in order to ensure that stability and safety standards are maintained.

Highlights

  • Cave mining practices have the advantages of simple production technology, low production costs, and production safety and are widely used in the field of metal ore mining [1]

  • En, a three-dimensional geological model was established based on the status of the stopes, geological data, and mechanical parameters of the various rock masses using GTS software. e shapes of the goaf roofs in the mined-out areas were obtained from the analysis results

  • A thin-layer theory was used to establish a formula for the thicknesses of the reserved protective layers in goafs

Read more

Summary

Introduction

Cave mining practices have the advantages of simple production technology, low production costs, and production safety and are widely used in the field of metal ore mining [1]. In order to protect ecological environments and ensure the safety of mining personnel, during the stable rock formation stages, horizontal isolation pillars of sufficient size are required. Determining the optimal size of the isolated pillars is vital for safe mining practices in metal ore mines. One of the main factors affecting the calculations of the thicknesses of the safety layers is the selection of the rock layer mechanical parameters. E rock layer parameters were measured by comprehensively using both field and laboratory instruments, and a model for predicting the safe thicknesses of isolated mining pillars was established in combination with an elastic plate theory. En, based on the obtained results, this study’s prediction model for the safe thicknesses of isolated mining pillars was revised A numerical simulation analysis was performed based on the on-site detection results. en, based on the obtained results, this study’s prediction model for the safe thicknesses of isolated mining pillars was revised

Analysis of the Occurrence Conditions of Mining Goafs
Amendments to the Security Layers of the Goaf Roofs
Validation of Calculation Methods for the Goaf Protection Layers
Findings
Conclusions
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.