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In the Name of God

Comparison of Empirical Fragmentation Models at the Gol-Gohar Iron Ore Mine

th International Symposium on Rock Fragmentation by Blasting

Dr. Mohammad Taji

24-26 August 2015 Sydney, Australia

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Contents


• Fragmentation surely is one of the most important and sensitive result of blasting.

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Introduction


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1- Introduction

• Empirical models are the first series which have been presented. • In recent years, due to proceeding computer science, hypothetical

models such as fuzzy logic systems, artificial neural network based systems and etc. were improved in order to increase accuracy and decreasing errors.

• Despite this, empirical models still are used because they have

high speed in achieving the result and they do not need to have special software or algorithms.


• Empirical fragmentation models predict size distribution by making

connections between effective parameters of fragmentation.

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Review of Blast Fragmentation Models

Denis & Gama (1970)

Larson Kuznetsov

(1973)

SveDeFo (1974)

Kuz-Ram (1983)

Modified Kuz-Ram (1987)

Kou & Rustan (1993)

CZM TCM

(1999)

CK (2003)

KCO Cunningham

(2005)

Gheibi et al (2009)


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3- Case Study on Gol-Gohar Iron Ore Mine

The Gol-Gohar iron mine is located some 55 km southwest of Sirjan in the province of Kerman.


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Case Study on Gol-Gohar Iron Ore Mine

The total ore reserve: 1135 million ton The Gol-Gohar deposit forms in six separate anomalies

at a confinement of about 10 km length and 4 km width.


• Used initiation system is Nonel. • The used explosive is ANFO or Emulan (Mixed of Bulk

Emulite and ANFO). • Delay time between different rows is 50 ms. • Number of rows and holes per blast is 2-7 and 50-120,

respectively. • Bench heights vary 15 m. • Blast holes of 251 mm are vertically drilled. • The drilling operation is performed carefully without any

deviation.

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Case Study on Gol-Gohar Iron Ore Mine


• The 20 blast blocks containing Magnetite and Hematite was chosen and examined.

• On the average for each blast 14 images in three different phases of fragmented muckpile (over, middle, end) were taken.

Measuring Fragmentation

Analyzed by: split-Desktop software

9 th International Symposium on Rock Fragmentation by Blasting

Blast No. Rock Type

11-234 Magnetite 20.58 44.01

13-76 Magnetite 17.91 60.89 14-13 Magnetite 18.66 42.63 12-155 Magnetite 25.40 60.61

14-14 Magnetite 22.81 45.44 13-78 Magnetite 20.60 51.12 12-156 Magnetite 32.09 59.96

12-162 Magnetite 25.25 56.01

12-164 Magnetite 33.80 91.13

12-167 Hematite 15.99 32.42

13-85 Magnetite 47.07 153.49 9-320 Hematite 14.20 33.94 10-321 Hematite 08.98 14.89

11-239 Magnetite 18.54 35.99

11-240 Hematite 07.67 18.49

13-87 Magnetite 18.74 49.87 11-241 Hematite 15.85 90.30

14-18 Magnetite 22.56 57.45 11-242 Magnetite 27.14 72.27 12-171 Hematite 22.60 44.71

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o Split-Desktop has a better than GoldSize.

o As by doing sieve analyze, the level of

relative inaccuracy for Split-Desktop was

15% and for GoldSize was 55.1%.

o Also, Split-Desktop software could

analyze fines.


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Discussion


• In modified Kuz-Ram model (2005) assigned timing is taken into account. Also, some changes have been done on scoring rock factor. Considering delays of blasts in the model, it did not present acceptable result and just made the model complex.


• SveDeFo model is based on the Larson model in which hole depth and stemming are considered has small flexibility; as remarkable changes in entrance values does not affect on output values.

• The process of its curve in compare with others is like a flat line which should not be like this. To sum up, this is a cautious model which anticipates values far smaller than real values.


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5-2- Studying size of distribution functions in models

Swebrec function Rosin-Rammler function


• Kuz-Ram model did not present good values for uniformity index (n).

• These values in some blasting patterns have heavy differences; the reason can be the land. Differences in BI of blasting patterns can be one of the most effective factor on uniformity index.

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Values of real uniformity index, calculating by some models for 20 blast.


• SveDeFo model has recommended a stable value (n=1.35) for all blasting patterns.

• It means that this model for all blasting patterns with different type and pattern geometry, present a specific slope for their size distribution curve.

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n= 1.35 (fixed)


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Comparison actual curve and each predictive fragmentation curves



• After studying 20 blasts in Gol-Gohariron ore mine, it was observed that any of empirical prediction fragmentation models did not present an acceptable performance, except Kuz-Ram model which presented closer result to reality for Magnetite in some blasting patterns.

• The comparison between Rosin-Rammler function and Swebrec function indicates that the performance of Swebrec in fines was better than Rosin-Rammler.

• This result for the upper part of fragment size distribution curve, coarse, is the reverse. Presented blastability index in 2002 gets large number in some blasting patterns in quantitative to comparison with blastability index in 1986 achieved by Lilly which is good. But in some patterns it does not work well and makes the conditions more complex.

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Conclusions


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Thanks for your attention


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