PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
July 3, 2024Geomatics Natural Hazards and Risk8 citationsOpen Access

Large dump critical zone of interest identification and slope failure prediction using realistic 3D numerical modelling

View Full Paper
KCKapoor ChandRKRadhakanta Koner

Key Points

Key points are not available for this paper at this time.

Abstract

Dump failure is one of the most catastrophic hazards in the opencast mining industry and involves sudden and violent failures. Therefore, susceptible region identification is essential for slope failure mitigation in the large dump. This study proposed a sustainable approach for large dump critical zone of interest (CZI) identification, stability monitoring and slope failure prediction. UAV close-range photogrammetry survey and structure-from-motion (SfM) approach were used for the dump realistic 3D model reconstruction. 3D numerical modelling was employed for dump stability analysis. In this investigation, the dump critical zone, slope factor of safety (FOS), displacement and slope failure prediction were analysed using the 3D numerical modelling. The results indicate that maximum displacement was found in the critical zone I. However, the dump was stable under static conditions. Dump critical slope failure time is predicted using the inverse velocity method. The results of this investigation are reliable and establish the scope of UAV photogrammetry for realistic 3D modelling. In addition, the slope stability state and failure model were consistent with field observations. The proposed approach can be used for the mine, hill, and roadcut slopes. UAV technology and 3D modelling approaches have substantially reduced data collection time and expense.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Chand et al. (2024) studied this question.

synapsesocial.com/papers/68e61806b6db6435875aa7cfhttps://doi.org/10.1080/19475705.2024.2361809
Ask AI
Helpful
Bookmark
Share
View Full Paper