Development of a PPV-strain-based approach for monitoring clay softening induced by construction vibration
Bibliographic record
Abstract
Abstract Construction activities, such as blasting, pile driving, and other heavy operations, near sensitive clay deposits can disturb and soften the soil structure, causing both transient and permanent deformations, thereby reducing the soil’s shear strength. These disturbances can impact clay slopes and adjacent structures, threatening their stability. In practice, vibration monitoring is based on the Peak Particle Velocity (PPV) concept, which was initially developed for rock blasting and is used to control damage to structures, rock slopes, and clay slopes, thereby preventing failures triggered by vibrations from various construction activities. However, current standards fail to provide acceptable PPV thresholds for clay deposits and slopes as these thresholds were originally adopted from rock surface measurements during blasting; additionally, applying the same threshold to different soil types is impractical due to their unique characteristics. Each type of clay has a critical shear strain (γt), below which negligible or no pore pressure and strength degradation occur. Therefore, this paper aims to develop a new practical approach to control vibration and avoid failures of clay slopes by correlating the PPV at the soil surface at a given distance from the loading source with the maximum shear strain experienced by the soil medium along a vertical section at the same distance. The validity of the correlation has been verified by numerical analysis using the FLAC2D finite difference program and by a field experiment in a natural soil deposit. The results show good accuracy of the developed equation in calculating the maximum shear strain induced in the soil at a specific section. Moreover, the equation demonstrates independence from the load characteristics at locations distant from the loading area.
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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".