Mine Backfilling in the Permafrost, Part I: Numerical Prediction of Thermal Curing Conditions within the Cemented Paste Backfill Matrix
Bibliographic record
Abstract
The mechanical behavior of cemented paste backfill (CPB) in permafrost regions may depend on the thermal curing conditions. However, few experimental data are available for calibrating and validating numerical models used to predict these conditions. To fill this gap, a three-dimensional (3D) laboratory heat transfer test was conducted on CPB placed in an instrumented barrel and cured under a constant temperature of −11 °C. Results were used to calibrate and validate a numerical model built with COMSOL Multiphysics®. The model was then used to predict the evolution of the temperature field for CPB cured under the thermal boundary conditions for a backfilled mine stope in the permafrost (at −6 °C). Numerical results indicated that the CPB temperature gradually decreased with time such that the entire CPB mass was frozen about five years after stope backfilling. However, the permafrost equilibrium temperature of −6 °C was not reached throughout the entire CPB mass even after 20 years of curing. In addition, the evolution of the temperature field in the permafrost rock showed that the thickness of the thawed portion reached about 1 m within 120 days. Afterwards, the temperature continues to drop over time and the thawed portion of the permafrost refreezes after 365 days.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".