Journal of Environment and Earth Science www.iiste.org ISSN 2224-3216 (Paper) ISSN 2225-0948 (Online) Vol.6, No.5, 2016 110 Rock Fragmentation Prediction using Kuz-Ram Model Jethro Michael Adebola* Ogbodo David Ajayi Peter Elijah.O Department of Minerals and Petroleum Engineering, School of Engineering, Kogi State Polytechnic, Lokoja, Nigeria *P.O.Box 110, Ido Ekiti, Ekiti State, Nigeria Abstract Evaluation of fragmentation remains an ever important discussion in the mining parlance as it is the first step towards mineral recovery. Various software’s and methods of predicting and analyzing the result of blasting exists, one of such is the Kuz-Ram model. This paper studied the development of the Kuz-Ram model from inception and the modifications that have been made. The methodology of its use and the discrepancies that exist between predicted results and the actual results generated by the design for similarities and correlation were examined. Predictions were made based on the input parameters of a limestone quarry and the blast design were varied to predict new design parameters that reduced the mean fragment size from 113cm to 105cm. This result shows a significant boost in the productivity of subsequent operations when the values estimated for burden and spacing were adopted. It was observed that the trend of the results remains valid in present day application even though there are significant differences in magnitudes of values. It was concluded that Kuz-Ram Model remains viable at making fragmentation prediction and a useful tool for pre assessing the effect of optimizing certain parameters of a blast design. Keywords: Fragmentation analysis, Kuz-Ram Model, Optimization and Prediction 1.0 Introduction The efficiency of a blasting operation is determined by the degree of matching the blast outcome and the required fragment size. Requirement specifications are usually governed by loading equipment, hauling equipment, and importantly, the primary crushing units. Fragmentation is one of the most important concepts of Explosives Engineering. Blasting is the first step of the size reduction in mining and it is followed by crushing and grinding unit operations. The efficiency of these unit operations is directly related to the size distribution of muck pile. (Esen and Bilgin, 2000). Kazem and Bahareh (2006) stated that the outcome of a good blasting operation leads to the productiveness of the next stages of mining, such as loading, hauling and crushing process. Jimeno et al, (1995) observed that the outcome of blasting operations are determined by a number of indices or parameters, which can either, be controllable or uncontrollable. The controllable parameters are basic blast design parameters, which can be varied to adjust the outcome of the operations, and this produce close to accurate results assuming the rock mass is homogenous and without discontinuities. But the uncontrollable ones are inherent properties of the rock, geological structures, usually defined by fracture distributions, need to be factored and included in the blast design. They explained further that for the purposes of blast design, the controllable parameters are classified in the following groups: A- Geometric: Diameter, charge length, burden, spacing etc. B- Physicochemical or pertaining to explosives: Types of explosives, strength, energy, priming systems, etc. C- Time: Delay timing and initiation sequence. The uncontrollable factors includes but are not limited to: geology of the deposit, rock strength and properties, presence of water, joints, etc. (Hustrulid, 1999) Methods to quantify the size distribution of fragmented rock after blasting are grouped as direct and indirect methods. Sieving analysis of fragments is the only technique in direct method. Though, the most accurate technique among others but is it not practicable because it is expensive and time consuming. For this reason, indirect methods, which are observational, empirical and digital methods have been developed (Esen and Bilgin, 2000). Kanchibotla et al. (1998) pointed out that the Kuz-Ram model underestimates the contribution of fines. This deficiency of the model can be overcome by introducing a second uniformity index to describe the fines distribution, below the mean size. In the case of the finer fractions, it is hypothesized that they are produced by the pulverizing or crushing action of the explosive in a blasthole. The crushing zone radius around each blasthole is determined based on the peak blasthole pressure and the strength of the rock. Kojovic et al. (1998) state that rock in the crushed zone is assumed to be completely pulverised to generate fines, which are assumed to be less than 1mm in size. The coarse part of the distribution is predicted using the conventional uniformity index based on blast design parameters proposed by Cunningham (1987) while the finer part is based on the percentage assumed pulverized around the blasthole. Other authors have tried to develop other functions to bridge this gap occasioned by the Rossin- Rammler exponent, and this includes the TCM and CZM models both known as JKMRC models, Swebrec function, (Ouchterlony, 2005) in the KCO model. Building a mathematical or empirical model which will accommodate both the blast design variables