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  Kuz-Ram Calibration Dataset for 12 Rock Types
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DEFINITION
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The Kuz-Ram Calibration Dataset for 12 Rock Types provides measured fragmentation
data and model calibration parameters for applying the Kuz-Ram fragmentation
prediction model across a range of common rock types encountered in mining and civil
excavation. It includes sieve analysis results, Kuz-Ram uniformity coefficient (n),
characteristic size (Xc), and in-situ block size distribution for each rock type.

OVERVIEW
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The Kuz-Ram model is the most widely used fragmentation prediction tool in blast
engineering, combining the Kuznetsov energy-based fragmentation equation with the
Rosin-Rammler distribution function to estimate the size distribution of fragmented
rock. This dataset provides empirical calibration data for 12 rock types—including
granite, basalt, limestone, sandstone, iron ore, copper porphyry, and coal—enabling
engineers to validate model predictions against measured field data. Each entry
includes the mean fragment size (X50), uniformity index (n), characteristic size (Xc
at 63.2% passing), and the in-situ block size distribution parameters (JRC, JCS,
RQD). The dataset supports sensitivity analysis by providing multiple calibration
points at different powder factors and charge configurations. Engineers use this data
to back-calculate the Kuz-Ram model constants for site-specific conditions, improving
prediction accuracy for production blast designs. The CSV format enables direct
import into spreadsheet-based blast design tools and fragmentation analysis software.

KEY COMPONENTS
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1. Rock Type Classification & Geomechanical Properties
2. Sieve Analysis Data (passing percentages at various mesh sizes)
3. Kuz-Ram Model Parameters (n, Xc, X50)
4. In-Situ Block Size Distribution (JRC, JCS, RQD)
5. Powder Factor vs. Fragmentation Correlation Data

APPLICATIONS
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  - Blast design optimization for fragmentation control
  - Kuz-Ram model calibration for site-specific conditions
  - Mill throughput prediction based on ROM fragmentation
  - Comparison of predicted vs. measured fragmentation

KEY FORMULAS
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Kuznetsov Mean Fragment Size: X50 = A × (V/Q)^0.8 × Q^(1/6) × (115/RFD)^0.63
  -> Predicts mean fragment size (X50 in cm) where A is rock factor, V is volume, Q is charge weight, and RFD is relative density factor.

RELATED CONCEPTS
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  - Rock Mass Rating (RMR)
  - Fragmentation Analysis
  - Powder Factor Optimization

REFERENCES
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Cunningham, C.V.B. (2011): The Kuz-Ram fragmentation model (https://www.rungetechnology.com/downloads/whitepapers/kuz-ram.pdf)
US Bureau of Mines: Fragmentation Analysis (https://www.cdc.gov/niosh/mining/)
Kuz-Ram Model Calibration Guide (https://www.isee.org/publications)

TAGS
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blasting, fragmentation, Kuz-Ram, calibration, CSV-data