Aziznejad, S. and Esmaieli, K. 2015. Effects of joint intensity on rock fragmentation by impact, 11th International Symposium on Rock Fragmentation by Blasting, 24-26 August, Sydney, Australia
Bibliographic record
Abstract
Impact-induced rock fragmentation is a mechanism that is commonly used for rock breakage in drilling andcrushing. Additionally, rock fragmentation by blasting is frequently used in rock excavation operations.Experience shows that presence of discontinuities in rock can significantly influence the impact-induceddamage and fragmentation of rock. Quantification of the response of jointed rock masses to impact loads iscomplicated by the fact that the available laboratory tests are mainly designed for aggregates or intact rocks.It can be argued that neither of these tests adequately represent a jointed rock mass. This paper presentsthe results of a series of numerical simulations used to investigate the influence of pre-existingdiscontinuities on the impact-induced fragmentation of rock masses. The methodology includesdetermination of the static and dynamic mechanical properties of a rock unit by conducting a series oflaboratory tests on intact rock samples collected from a quarry in Canada. A 2D distinct element code,Particle Flow Code (PFC2D), was used to generate a bonded particle model in order to simulate both staticmechanical properties (Uniaxial Compressive Strength, Elastic Modulus, Poisson’s Ratio and indirect TensileStrength) and dynamic mechanical property (drop weight tensile strength) of the intact rock. The calibratednumerical model was then used to construct large-scale synthetic rock mass samples by incorporatingdiscontinuity networks of different intensity into the bonded particle model. Finally, the impact-inducedfragmentation inflicted by a rigid projectile particle on the jointed rock mass samples, simulated by asynthetic rock mass model, was determined. More fragmentation was observed for the rock mass sampleswith higher joint intensity.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".