The main objective of this publication is the description of an unsophisticated methodology to predict caving and cave propagation for mining purposes based on numerical simulations. The aim of the methodology is to create a user-friendly tool which requires little effort to set up and analyse and which facilitates understanding of cave propagation for practical applications.The methodology is defined as an algorithm which is performed in FLAC3D, version 7.0 (Itasca 2019). The constitutive modelling is based on model elastic behaviour, due to its simplicity and low running times. The algorithm utilises a series of routines that describe and quantify the failure process of rock during caving.The emphasis of the methodology is on simplicity, which is reached by implementing reasonable assumptions regarding the caving situation and the rock mass behaviour. The caving propagation is driven by plastic behaviour; however, to simplify the model the caving algorithm is based on an elastic behaviour and specific functions mimicking the plastic behaviour, namely the degradation processes occurring in the rock mass during caving are accounted for by reducing the mechanical properties of the rock mass and the stress state in degraded zones in a controlled and systematic manner. Sensitivity tests are performed to analyse the weight of the mechanical parameters involved in the caving processes, as well as to optimise the reduction rate of the mechanical properties of the rock mass.The calibration of the caving algorithm is the current stage of the development. The calibration is carried out by analysing the results obtained in the numerical models and the outcome of the semi-empirical methods available in the literature.The unsophisticated caving predicting tool is being developed for its application on the novel raise caving mining method (Ladinig et al. 2022). The caving tool will supply understanding regarding the caving initiation and propagation for the novel raise caving method.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.