Numerical investigation on the thermo-mechanical behaviour of twin energy tunnels
Bibliographic record
Abstract
Energy tunnel provides an innovative and efficient approach to harvesting geothermal energy. Some investigations on a single energy tunnel have been reported in the literature. This study investigated the behaviour of twin energy tunnels in two configurations (i.e., parallel and perpendicularly crossing) by using a thermo-hydro-mechanical coupled numerical model developed and validated in previous work. The responses of ground and a tunnel (denoted by ET1) to three thermo-activation modes were determined: cooling ET1 itself alone (ET1active), cooling a nearby tunnel alone (ET2active), cooling both tunnels simultaneously ((ET1 + ET2)active). The computed results reveal that the interaction between two tunnels becomes negligible when the clear distance reaches four times the tunnel diameter. When the clear distance is smaller, the interaction could impact the tunnel and soil displacements. In ET1active and (ET1 + ET2)active, the vertical responses (i.e., ground settlement, ET1 settlement and vertical convergence) in both tunnel configurations can be close to or even exceed the allowable values in tunnel management guidelines, depending on ground and tunnel conditions. The horizontal responses of ET1 (i.e., horizontal displacement and convergence) are always insignificant. The thermo-activation of ET2 alone has minor effects on ET1, except a strong impact on ET1 settlement in the case of crossing tunnels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".