A Case Study on Trim Blast Fragmentation Optimization Using MBF and MSW Models at an Open Pit Mine in Canada
Bibliographic record
Abstract
ABSTRACT: A project for monitoring, analysis, and modelling trim blasting at an open pit copper/molybdenum mine in Canada in 2021 was conducted using Orica’s in house developed proprietary tools, which includes the accelerometer near-field vibration monitoring system, the Multiple Seed Waveform (MSW) near- and far-field blast vibration model, and the Multiple Blasthole Fragmentation (MBF) model. Both MSW and MBF models are built on the fundamentals and empirical aspects of blasting mechanics. The blast vibration at the highwalls from trim blasts was predicted with MSW model. The effects of parameters from the blast design scenarios at the mine site were simulated and optimized designs were proposed based on the MBF and MSW modelling. The MBF model explicitly simulates all blast design parameters. The MSW blast vibration model uses multiple seed waveforms at different distances from a blasthole to a point of interest and is suitable for near-field blast vibration at the highwalls. Through the application of the MBF in conjunction with the MSW, various design scenarios can be explored, and rock fragmentation can be optimized while controlling blast vibration levels. These models have been successfully applied to many open pit mines and quarries around the world. 1. INTRODUCTION For a large open pit mine, it is of vital importance to optimize trim blasts. A trim blast is next to the presplit. To minimize the negative impact on the highwall, trim blasts are often loaded with a low powder factor that results in much coarser fragmentation than the production blasts. The coarser fragmentation increases the cost of the downstream operations. On the other hand, trim blasts with a high powder factor could impact the highwall causing the highwall instability. Over the recent years, Orica developed a unique system for blast optimization projects. The system includes near-field blast vibration monitoring using accelerometers, the multiple blasthole fragmentation (MBF) model, and the multiple seed waveform (MSW) blast vibration model. The three components of the system are used together to improve blast performance at a site.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".