Influence mechanism of strong seepage on the development of single-circle pipe artificial freezing curtain in gravelly soil layer
Bibliographic record
Abstract
Artificial freezing model tests have been conducted to explore the influence of strong seepage on the development of frozen curtain. Compared with the low seepage velocities below 5.0 m/d, the strong seepage of 7.5 m/d has further extended the varying ranges of freezing front developing rates and temperature gradients, changing the temperature fields to be more asymmetric, and delaying the freezing stages. The freezing process experiences four stages including “first rapid decrease-gradual decrease-second rapid decrease-stabilizing”, and the initial frozen time has been extended to 2–4 times. The closure time is generally increasing exponentially with seepage velocity, and the frozen curtain may not close under a critical value (15 m/d). As for the morphology of frozen curtain, its thickness at the upstream side gets thinner and that at the downstream side gets thicker, and its asymmetry has been increased to 4–7 times. To describe the unfrozen water content variation with temperature, a Boltzmann unfrozen water content function is proposed considering the initial and residual unfrozen water content, as well as the varying characteristics. Additionally, a hydro-thermal coupling model has been derived to present the artificial freezing process considering the seepage flow states from laminar to transitional state, and its simulating results including temperature variations and the morphology of frozen curtain are well consistent with the model test data. This research reveals the influencing mechanism of strong seepage flow on the generating of frozen curtain, and it provides theoretical support for predicting its formation process.
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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".