Design of Foundations on Sensitive Champlain Clay Subjected to Cyclic Loading
Bibliographic record
Abstract
Sensitive clay subjected to cyclic loading may experience gradual loss of its shear strength, which may lead to liquefaction. Foundations built on this clay would suffer extensive settlement and significant loss of bearing capacity or perhaps catastrophic failure. This paper presents an experimental investigation on sensitive (Champlain) clay obtained from the city of Rigaud, Quebec (Canada). Consolidation tests, static and cyclic undrained and drained triaxial tests were performed on representative samples of this clay. The objective of this investigation was to examine the influence of the physical and mechanical parameters, which govern the shear strength of sensitive clay subjected to cyclic loading. Based on the results of the present investigation and those available in the literature, it can be reported herein that the undrained response is the most critical for these foundations; furthermore, the preconsolidation pressure is considered as an important parameter in establishing the shear strength of sensitive clay. A design procedure is developed to determine the safe zone for the undrained and drained responses, within which a combination of the cyclic deviator stress and the number of cycles for a given soil/loading/site conditions can achieve a quasielastic resilient state without reaching failure. The proposed design procedure is applicable to all regions around the world, where sensitive clays can be found. Furthermore, this procedure can be adopted to examine the conditions of existing foundations built on sensitive clay at any time during its lifespan.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".