Unified Design Approach for Rock Fissure Grouting—Best Design Practice for Pre-Grouting of Rock Tunnels in Sweden
Bibliographic record
Abstract
In general, all tunneling contracts in Sweden are based on performance contracts. There has been a large increase in the knowledge and understanding during the last decades in Sweden regarding sealing of rock tunnels using mostly cementitious rock fissure grouting. This increased know-how derives from extensive research and execution of continuous pre-grouting throughout different rock tunneling works in Sweden. However, there is still a large variety in grouting designs as well as in performance between, and even, within projects. In order to make sealing of tunnels more efficient the Swedish Transport Administration has initiated a project to establish a unified design approach for rock fissure grouting in hard crystalline rock. The aim of the design approach is to have a coherent and structured process and methodology for grouting design, resulting in an appropriate, similar and transparent design approach independent of designer. The purpose is thus to introduce explicit guidelines for grouting design and its presentation as grouting classes that will be used in technical specifications, bill of quantities and prognosis for further procurement of grouting works in performance contracts. The improved tendering document should result in reduced costs due to efficient design works followed by an easier procurement process for performance contracts along with improved grouting performance and hopefully also less claims/disputes. The design approach is not yet implemented. However, the design approach is based on known theories and experience that are now compiled into one comprehensive methodology.
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".