A Modeling Study of Large-Scale Solute Transport in Fractured Carbonate Rock
Bibliographic record
Abstract
Fractures influence aqueous contaminant transport by allowing for rapid migration over long distances through complex pathways and through diffusion into the adjacent rock matrix. While there have been many studies examining transport at smaller scales, there have been far fewer investigations at larger distances (> 50-100 m) due to the cost and difficulty of such research. This study focused on identifying key properties governing large-scale solute transport in sparsely fractured rock. Numerical models which accommodate flow and transport in fractures were used to simulate the results of two divergent tracer experiments previously conducted at large scale in a fractured dolostone. One of the experiments was conducted in what is believed to be a discrete horizontal fracture, and the other conducted in a fracture network. Both experiments had observation points > 100 m from the injection well. As the numerical analysis required estimates of fracture aperture, an improved method of determining fracture transmissivities from the bulk values obtained in constant head testing was also developed. The results of fitting the measured data with simulations determined that fracture aperture heterogeneity was likely the key property for simulating the tortuous transport observed in the experiments. Simulation of the discrete fracture experiment identified the errors inherent in the use of scaling parameters (e.g. matrix porosity) to the scale-up of experimental results. This study also highlights the significant issues with non-uniqueness that can arise in the interpretation of large-scale tracer experiments in fractured rock. Aperture heterogeneity and complex interconnections can produce an extensive number of equally plausible networks, the difference between which can have significant impact on transport predictions. The error resulting from this non-uniqueness and the application of scaling parameters needs to be better recognized and can be used to more accurately quantify risk assessment for potable water supplies in the vicinity of contaminated sites.
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 | 0.000 | 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 | 0.000 |
| 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".