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Computer simulation models for the gravity flow of ore in sublevel caving

In recent years a number of research centres have endeavoured to provide a mathematical model that indicates the chief characteristics of ore flow in the sublevel caving mining method. Optimization of the design parameters for sublevel caving has ensued with the objective of maximizing ore recovery while minimizing waste dilution. Past studies have been confined by two simplifying assumptions: that the region of flow be approximated by a simple mathematical function, and that the flow analysis is static, ie extraction is calculated by employing an idealized ore-waste boundary position for each ring. Further investigation into models of ore flow has been stimulated on two counts.1. full scale tests have indicated that a more complex description is required;2. as a design tool, a dynamic analysis that monitors the displacement of the broken rock mass during extraction would yield more realistic recovery predictions under operating conditions, and enable variations on the method to be evaluated.This study reviews the various formulations currently available, or being developed to describe the flow of granular material. A viable solution in a mining context would be three dimensional, time dependent, and incorporate stress conditions. Although workers in diverse fields have analyzed the problem no solution exists at present. The majority of studies are either empirical in nature, or deficient in one or other of the above criteria. Two approaches are developed and implemented on a digital computer:(i) stochastic flow model(ii) empirical flow model based on the results of modelling studies, and full scale test. Although a number of concepts introduced in these models remain to be verified, the validity of these models would be measured by their success or failure as a simulation tool in a mining environment.

Identiferoai:union.ndltd.org:ADTP/245092
CreatorsAlford, Christopher Grant
Source SetsAustraliasian Digital Theses Program
LanguageEnglish
Detected LanguageEnglish
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