Analytical methods to reduce uncertainty in tunnel construction projects
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents a method to quantify uncertainty using simulation techniques and approximate geotechnical methods. Unknown soil conditions are major contributors to uncertainty in any underground construction project. Soil conditions are unknown because generally soil samples taken from vertical boreholes show only the soils present in the discrete borehole locations. The soil profiles between the boreholes therefore contribute to project uncertainty, and construction practitioners must make assumptions about these soil profiles for construction planning and scheduling purposes. Analytical and simulation methods are presented to accurately predict soil profiles between boreholes and reduce uncertainty in a "rough and ready" fashion. These methods use existing borehole data to create an analytical model for soil prediction, which is then incorporated with a process interaction simulation model of the construction project using special purpose simulation concepts and advanced geotechnical characterization techniques. The application of these methods to an Edmonton tunnel construction project is also detailed. Construction engineers or managers can use these simulation methods to strengthen the geological data obtained for the construction project.Key words: borehole data, construction, risk, soil families, soil profiles, soil transitions, special purpose simulation, tunnelling, uncertainty.
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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 | 0.001 | 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) | 0.000 | 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 it