Monitoring blasting-induced vibrations in a Québec clay deposit
Bibliographic record
Abstract
Abstract Blasting operations carried out as part of road projects can generate vibrations that affect the stability of surrounding slopes. However, the effects of these vibrations on clay soils remain poorly documented. To date, few cases of landslides or major deformations have been recorded in these types of soils following blasting. Currently, blasting is controlled by peak particle velocity (PPV) thresholds. In Queébec, existing regulations are becoming increasingly restrictive, leading to a significant increase in blasting costs. This article is a continuation of the recommendations from previous studies, which highlighted a lack of field data on vibrations caused by blasting in sensitive clay deposits, as well as the absence of a clear methodology for carrying out measurements (number of devices, distances between recording sites, etc.). One of the objectives of this article is to show vibration recording data produced by blasting activities in clays in order to gain a better understanding of these problems. As part of this project, two blasting operations were carried out near a clay deposit. Various installation devices and techniques were used to measure vibrations and are presented in this article. These field tests highlighted limitations in the surface recordings, which affect our understanding of blasting wave propagation mechanisms in clay soils. These understanding of blasting wave propagation mechanisms in clay soils. These limitations will be discussed in detail and provide the basis for a subsequent phase of research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".