Rock Engineering Design in Frozen and Thawing Rock: Current Approaches and Future Directions
Bibliographic record
Abstract
The purpose of this review is to present the state-of-the-art methods, problems and potential future design techniques used for rock engineering in frozen ground, with particular regard to the design of mine openings in rock masses that may be subject to thawing. The impetus for this work is the recognition that civil and mining infrastructure is extending into such frozen material, and the design procedures currently available may not be optimal. Additionally, civilian infrastructure in frozen ground in alpine regions (e.g. central Europe) is also becoming subject to thawing conditions. In any such scenario, increased heat exchange with an exposed rock mass surface will cause thawing to occur. In general, a rock mass is stronger in frozen conditions than in dry conditions (i.e. without ice or water), but a rock mass will be least strong at the time ice-filled discontinuities are thawing, resulting in a significant shear strength reduction. In this review, we will discuss the various existing design methods in the context of the phenomena involved in the formation of frozen rock and the behaviour of thawing rock. We will show the deficiencies of these methods and highlight potential developments that will lead to future robust design protocols.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".