Evaluation of equivalent hydraulic aperture (EHA) for rough rock fractures
Bibliographic record
Abstract
Most existing models for fluid transportation within a single rock fracture tend to use a channel with two smooth parallel plates, whereas real fracture surfaces are usually rough and tortuous, which can produce a flow field significantly different from the smooth plate model. For fluid flow in a rough fracture, there are surface concave areas (SCA), where the fluid velocity is extremely low, contributing little to the fluid transportation. It is of great significance to quantitatively evaluate the impact of rough surfaces on fluid flow. Therefore, a numerical model for simulating Newtonian fluid through rough fractures is proposed, where synthetic surfaces are generated according to statistical analysis of natural rock fractures and can be quantified by several characteristic parameters. Equivalent hydraulic aperture (EHA) is proposed as one quantitative indicator for evaluating the impact of fracture roughness. Systematic studies were conducted for evaluating EHAs of rough fractures, which, combined with characteristic parameters of fractures, are used to build surrogate models for EHA prediction. It is found that the EHA is directly correlated with the fracture roughness, the mean mechanical aperture, and the standard deviation of aperture distribution. The developed surrogate models were verified to have a high accuracy for EHA prediction.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".