Analysis of cycle excavation and productivity of large-scale rock tunnel projects - lesson learned in Taiwan
Bibliographic record
Abstract
Tunnel construction has become a major part of infrastructure development in Taiwan in the 1990s. This study compares and analyzes the productivity difference in the construction of two large-scale long rock tunnels, i.e., the Pengshan and Nangkang No. 2 tunnels. These two tunnels, which are 3.8 and 2.7 km in length, respectively, are part of the Taipei-Ilan Expressway. The cross section, construction method, and contract type are all similar. Both projects utilized multi-skilled working crews for improving productivity. However, essential differences in productivity and monthly progress were recorded. This study analyzes the key factors for these differences regarding the geological condition, working crews, equipment and facilities, and management approach. Based on the productivity data analysis of the two tunnels, the key points for productivity improvement of large-scale rock tunnel projects are then pinpointed.Key words: cycle excavation, productivity, rock tunnel, Taiwan.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".