Date of Award

Spring 2018

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Mining Engineering

Committee Chair

Scott Rosenthal

First Advisor

Chris Roos

Second Advisor

Das Avimanyu

Abstract

The mining process begins with drilling and blasting activities. The efficiency of blasting affects all downstream operations such as loading, hauling, crushing and milling. Therefore drilling and blasting activities should be designed to ensure that designed parameters produce the desired fragmentation. The Kuz-Ram model is a fragmentation prediction model and is widely used for predicting the fragmentation distribution from blasting in the mining industry. This research evaluates the performance of the Kuz-Ram and Modified Kuz-Ram models to determine the most accurate models applicable to a Western US open pit copper mine’s fragmentation data. The performance assessment was done using the Root Mean Square Error and correlation and regression analyses. A general trend of under estimation of the fines (< 0.75 inch) and over estimation of oversize (≥ 25 inch) was observed using the Kuz-Ram and Modified Kuz-Ram models as compared to the Split image analysis obtained in the field. From the image analysis, the average actual amount of fines produced from the eight blasts studied was 27.62% with an insignificant amount of oversize material less than 5%. Though all the models had high correlation coefficient, R and coefficient of determination, R2 values (above 95%) in predicting the fragmentation distribution, the Modified Kuz-Ram model performed well in six out of the eight blasts considered while the Kuz-Ram model performed best in two out of the eight blasts considered.

Comments

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Mining Engineering

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