An investigation of the ambient temperature field and thermal response of the Calgary Airport Trail Tunnel
Bibliographic record
Abstract
Thermal loads must be considered in the design of many types of structures including buildings, dams, bridges, and tunnels. In some cases, thermal loads may have the same order of magnitude as dead and live loads. Determining the thermal load is a complex problem since it depends on several variables such as structural material, geometry of the structure, and the environment the structure is exposed to. The thermal response of the structure, which includes stresses and displacements, is also equally complex. There is currently a lack of design provisions in structural codes and literature that address design temperatures and the location of movement joints in tunnel structures. In this context, the main focus of this thesis is to study the temperature distribution and thermal response in concrete road tunnels due to ambient temperature using a case study. The main body of this thesis is comprised of two parts. The first part involves the study of temperature distributions and the resulting thermal response in the tunnel structure using numerical modelling. The second part involves the analysis of long term temperature and displacement sensor monitoring data collected from the Airport Trail Tunnel in Calgary, Alberta, which is a case study for this thesis. The aim of the study is to evaluate findings from the numerical analysis and sensor data with current structural code provisions that address design temperature and the location of movement joints. From the investigation, it was determined that the design temperature range was within CSA S6, however CSA S6 underestimates the temperature gradient effects in the walls and slabs of the tunnel. Recommendations and future work are addressed to conclude the thesis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".