Effects of fracture-system geometrical parameters on the inflow rate into a tunnel in rock: a numerical modelling experiment
Bibliographic record
Abstract
The relationship between the inflow rate to a rocky tunnel and the effective parameters controlling the inflow rate (e.g. aperture, spacing, orientation, tunnel radius and water head) is investigated by numerical modelling. Response surface methodology is adopted to optimize the number of simulations and their meaningful interpretation, and Design-Expert software is used for this purpose. Consequently, numerical simulations are performed, using 3DEC version 7 software, for 88 scenarios based on different values for the parameters related to the fracture-system geometry and boundary conditions. Accordingly, the relations between the inflow rate to the tunnel and the effective parameters, as well as their interactions, are determined and presented in the form of empirical equations. In addition, the mean value of each parameter is used to develop another equation for calculating the inflow rate. Specifically, the aperture and spacing, as well as the interaction between these parameters and other effective parameters, have the most important impact on the value of the inflow rate. Furthermore, the impact of the tunnel radius on the unit inflow rate is negligible. Using numerical simulations, two empirical equations have been developed for the calculation of the unit inflow rate to the tunnel: one for exact values of parameters and another for their mean values. Supplementary material: Supplementary information on the interaction between the parameters and the statistical analysis are available at https://doi.org/10.6084/m9.figshare.c.6292560
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".