WP2 – ROCK/EXPLOSIVE INTERACTION

UPM (lead), ARNÓ, VA Erzberg GmbH, LTU, MINERA ORGIVA

The objectives of WP2 are:

  • To improve the understanding of the non-ideal detonation properties of civil explosives, the energy release pattern and
    the detonation gas components under the conditions of non-ideal detonation.
  • To evaluate explosive performance during blasting.
  • To improve and implement knowledge about the effects of rock mass characteristics (hardness, fracturing and geology)
    and how this can be used in: production planning, fragmentation, mill performance, and environmental effects (blast
    damage, vibrations).
  • To assess, with a reasonable accuracy, the effect of explosive properties, rock mass properties and blast layout on
    fragmentation by blasting and to improve current fragmentation prediction models. To do this, good non-ideal explosives
    material models are required as well as rock material properties.

2.1. EXPLOSIVE CHARACTERISATION

The objective of this task is to evaluate the energy release of common civil explosives and assess their performance in the field. The components of toxic fumes including oxides of nitrogen (NO, NO2) and carbon monoxide and their percentage will be also quantified. This will be achieved by:

Subtask 2.1.1 Assessment of the effective energy of civil explosives30‒40 cylinder tests on different diameters with civil explosives and loading configurations to be used/developed in the project (UPM, LTU).
Impact test to calibrate the parameters of JWL EoS for unreacted explosive (LTU)
30‒40 tests to measure the detonation front and the velocity of detonation of explosives to be used/developed in the
project in different diameters and confinements (LTU).
Modelling with LS-Dyna of non-ideal detonation model (UPM, LTU).
Numerical investigation of the energy release of explosives using calibrated JWL EOS (UPM, LTU).
Calculation of explosive energy using thermodynamic codes (UPM, LTU).

Subtask 2.1.2 Performance of explosives in the field
On site measurement of in-hole explosive pressure and VOD (UPM).

Subtask 2.1.3 Investigation of detonation fumes
Up to 20 tests in a blasting chamber (LTU).
The components of toxic fumes for different charge diameters will be analysed (LTU).
Evaluate results for commercial explosives used in mines in European Union. (LTU).

2.2. ROCK CHARACTERISATION PRE AND POST-BLAST

LTU (lead), UPM, ARNO, ERZBERG, MINERA ORGIVA

Production activities can be planned with high adaptation to varying rock conditions and improved quality of the overall mining process. In particular blasting can significantly be improved if charging can be adapted to varying rock conditions, providing better fragmentation, less boulders, less fines and selective mining where ore and waste can be taken out separately. Due to changing geo-mechanical and geological conditions the geo information model need to be integrated with a cost estimation and scheduling tools in order to evaluate the consequences of different ore
production alternatives. The objective is to identify and monitor rock mass characteristic parameters, adapt blasting and other unit operations to these varying conditions and predict the impact on the mining operations such as productivity, environmental effects and waste rock.
At present, post blast characteristics of the rock are not monitored in a production environment. This information is essential to ensure safer operations and to guide blast design towards a minimum rock fracturing on the remaining rock mass, so that more efficient operations are obtained (decrease in rock support requirements in underground excavation and decrease of stripping ratio in open pits).
The systems/techniques that have been identified and show potential to be implemented in the mining process are Measurement While Drilling (MWD), Photogrammetry and Cross-hole monitoring. MWD can estimate variances in the rock mass’ hardness, fracturing, hydraulically conditions etc. with a high resolution and also potentially give a detailed map of the mineralization. Photogrammetry can describe the rock mass structures in a non-destructive way. Cross-hole measurements have the potential to assess rock damage between pairs of drillholes. The following actions will be carried out in this working package:

Subtask 2.2.1 Geomechanical rock models
Identification of available, suitable MWD equipped test sites (LTU, UPM)
Selection and adaptation for rig and drilling technique (percussive, rotary, ITH, pneumatic, hydraulic etc.) (LTU, UPM)
If required installation and commissioning of MWD system (UPM, ARNO, ERZBERG, ORGIVA).
Drilling Monitoring with MWD in production blasts (PB) (UPM, LTU, ARNO, ERZBERG, ORGIVA).
Filtering, analysis, modeling of MWD data response (LTU)
Modeling rock mass impact on blasting (LTU)
Rock characterization with MWD and photogrammetry (UPM, LTU).
Development of cost model for blasting adaptation to rock mass quality (LTU)
Compilation of data, analysis and reporting (UPM, LTU).

Subtask 2.2.2. Post blast rock characterisation
Cross-hole monitoring: variation in p-wave velocity before and after PBs (UPM, ARNO).
Accelerometers to measure seismic activity in the near field from PBs (UPM, ARNO).
Measurement of gas penetration around blastholes during blasting (UPM, LTU, ARNO).

2.3. CONTROLLING ROCK FRAGMENT SIZE DISTRIBUTION: LARGE AND SMALL-SCALE TESTING

UPM (lead), LTU, ARNO

This task aims to assess fragmentation at varying blasting conditions. Emerging technologies will be used to monitor blast characteristics and precise delay detonators will be employed in order to ensure accurate initiation times.
Fragmentation monitoring will be assessed by different means with special emphasis of aerial imagery to acquire a complete model of muck piles.

Subtask 2.3.1. Monitoring of production blasts (PBs)
Design and implementation of 10-15 PBs (UPM, ARNO).
Development of geomechanical models of the blocks (input from 2.2.1).
Geometric control by photogrammetry and/or LIDAR (UPM, ARNO)
Hole deviation monitoring by borehole probes (UPM, ARNO).
High-speed video recording to determine rock movement (UPM, ARNO).
Compilation of data, analysis and reporting (UPM).

Subtask 2.3.2. Fragmentation monitoring of Run of Mine (ROM)
Size distribution measurements from PB s with mobile screens (UPM, ARNO).
Installation and commissioning of 3D imaging LIDAR based system in selected sites (LTU, ORGIVA, UPM).

Subtask 2.3.3. Small scale-tests
Design and implementation of small scale tests (LTU)
High-speed video recording to investigate the crack generation process and rock motion (LTU).
Quantification of fines and very fines generation: this will be an input for WP3.3.2 (LTU).

2.4. FRAGMENTATION PREDICTION: NUMERICAL MODELLING

LTU (lead), UPM

The main goal of rock blasting is the fragmentation of the rock mass. Prediction of the size distribution of the fragmented rock from the rock mass characteristics, the blast design parameters (both in terms of the geometry and of the initiation sequence) and the explosive properties is a challenge that has been undertaken for decades, and is currently available to the blasting engineer in the form of formulae that relate the parameters of a given size distribution function to the rock properties and the blast design parameters. Most of these models yield fragmentation predictions of limited accuracy. A paradigmatic evidence of this is the strong controversy on what distribution functions better represent the size distribution of blasted rock. Numerical methods are becoming increasingly popular in rock blasting. Considerable efforts have been directed towards developing blasting numerical simulation and various numerical methods have been developed. Finite Element Method (FEM), Discrete Element Method (DEM) and Smoothed Particle Hydrodynamics (SPH) have been used to predict blast results in different environments and materials. FEM can be used to model precisely the detonation of explosives, blast-induced vibration and blast-induced damage. While DEM and SPH are more suitable to model the fragmentation of rock mass well, although with the latter the explosive detonation can be also modelled. This will be achieved by:

Subtask 2.4.1. Modelling of fragmentation and flyrocks with LS-Dyna, PBM-BPM models

Characterisation of rock mass properties needed to model them, such as density, elastic modulus, Poisson’s ratio, uniaxial compressive strength, uniaxial tensile strength, cohesive strength (LTU).
Numerical modelling of fragmentation and fly- rocks combining particle Blast Method (PBM) and Bonded Particle Model (BPM) (LTU, UPM).

Subtask 2.4.2. Engineering models for rock fragmentation prediction.

Definition of a blastability index (based on output from 2.2.1) (UPM,LTU)
Engineering tools (numerical model) towards fragmentation control (UPM)

WP OVERVIEW