Temperature effects on dredged slurry performance under vacuum preloading
Bibliographic record
Abstract
Under appropriate temperature conditions, vacuum preloading can effectively accelerate the rate of soil consolidation. If the temperature is low (30 °C), vacuum preloading is less effective at consolidating the soil. If temperature is extremely high, vacuum preloading is less efficient at consolidating the soil due to the consummation of excess energy consumed. In this study, a series of laboratory tests was conducted to analyse the effects that temperature has on dredged slurry consolidation via vacuum pressure using constant and variable heating modes. During these tests, heat transfer, water discharge, surface settlement, and pore-water pressure dissipation were observed in the soil samples. Based on the laboratory test measurements, each soil sample’s horizontal coefficient of consolidation, water content, and shear strength were determined. To quantify the energy consumption of the different heating modes, the ratios of energy consumption as a function of the soil’s total water discharge and mean shear strength were determined. Using these parameters, an optimal soil consolidation temperature was obtained. The results indicated that vacuum preloading was most effective in consolidating the soil under a constant temperature of 75 °C rather than variable temperatures.
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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 | 0.001 | 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) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".