Benchmarking NAPL Redirection and Matrix Entry at Fracture Intersections Below the Water Table
Bibliographic record
Abstract
Abstract This paper examines a numerical modeling approach for two‐phase flow and considers the contribution of a simple network of fracture intersections to the whole discrete fracture‐matrix flow system; it develops a benchmark problem for a non‐wetting, dense, non‐aqueous phase liquid invading a water‐saturated, discretely fractured, porous medium near a fracture intersection under cases of invader fluid redirection at the intersection, breakthrough to a constricted fracture branch, or breakthrough into the rock matrix using capillary entry pressures. Numerical simulation is performed with a multiphase, compositional DFM software, using a finite difference discretization of the governing equations. In these simulation cases, the “star‐delta” method for eliminating line‐ and point‐control volumes at fracture intersections is contrasted to retaining all control volumes, the goal being to test the efficacy of the star‐delta simplification. Flux over the domain's boundaries and mass storage are comparison metrics. Results indicate that conduits (or lack thereof) have a strong effect on NAPL architecture with an accompanying change in efflux in the case of redirection; they have some early‐time effects on architecture and efflux in constricted fracture cases. The scenario presented herein leads to multiphase flow forecasts in intersection conduits which can serve as an experimentally testable hypothesis and as a benchmark for comparisons of simulator forecasts.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".