Influence of Specimen Geometry on Sample Disturbance Observed in Oedometric Testing of Clay Shales
Bibliographic record
Abstract
Abstract There has been a significant amount of research investigating the relationship between sample disturbance and laboratory test results in soft soils. As a result of this research, the general rule adopted is that using larger specimens results in less sample disturbance. When testing these larger specimens in the laboratory, the results are more representative of in situ behavior of the materials. In contrast, there has been relatively little corresponding research performed on hard soils whose behavior typically lies on the boundary between rock and soil. Extensive unloading in hard soils, from sampling, results in large suctions (negative pore pressures) and the formation of fractures that are uncharacteristic of the material in its natural state. This poses the question of whether the use of small specimens would produce more reliable laboratory results. This paper investigates the following two hypotheses within the context of oedometric testing: (1) testing smaller diameter specimens will produce results more representative of the in situ behavior of the material, and (2) an aspect ratio of 2.5 may reduce disturbance to the specimen during preparation are tested. The results of this testing program, including the intact material properties, and a characterization of the compression behaviour of clay shale from the Bearpaw Formation is also presented herein. Results show that a reduced specimen size, when working with a hard clay shale, minimizes the effect of disturbance and produces results that are the most representative of the intact material. Decreased specimen size also aids in determining preconsolidation pressure by not only reducing the disturbance to the sample resulting from unloading, but also by enabling these high stresses to be achieved in conventional testing equipment. Two criteria from the literature were used to assess disturbance within the oedometer specimens. Overall, the methods provide a good baseline of assessing disturbance, however, there is less gradation to the quality of a specimen in a hard soil. Parameters Cc and σ′p were sensitive to sample disturbance, however, other parameters such as cv and K were less dramatically affected by disturbance. Therefore, care must be taken when assessing the compression of a hard soil as failing to achieve sufficiently higher stresses and the presence of disturbed specimens may lead to misleading Cc and σ′p values.
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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 | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".