Coefficient of consolidation from the linear segment of the <i>t</i><sup>1/2</sup> curve
Bibliographic record
Abstract
The coefficient of consolidation is commonly determined by fitting the Terzaghi theoretical time factor, T, versus average degree of consolidation, U, relationship to the measured oedometer consolidation curve. A simplified version of the Taylor t1/2 method is proposed in this paper. Since the theoretical T1/2 versus U relationship is linear up to 60% consolidation, the measured t1/2 consolidation curve may also present a linear segment that ends at 60% consolidation. Samples of 10 natural soft clays with liquid limits ranging from 40 to 152% were used to carry out conventional oedometer tests with consolidation increments in the recompression range, spanning the preconsolidation pressure, and in the compression range. Based on the oedometer test results, the effects of secondary compression on the shape of the t1/2 consolidation curve are evaluated and found limited between 60% and 90% consolidation. In the proposed simplified t1/2 method, the time of 60% consolidation is recognized from the lower end of the linear segment and is used together with the Terzaghi theoretical time factor of 0.286 and the maximum drainage distance of the oedometer specimen to determine the coefficient of consolidation. A large amount of the oedometer coefficient of consolidation data obtained from the simplified t1/2 method are in good agreement with those from the Taylor t1/2 method and are within one to two times those from the Casagrande logarithm of t method.Key words: laboratory tests, coefficient of consolidation, curve fitting method, settlement.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".