Field trials of subsurface chaotic advection: Stirred reactive reservoirs
Bibliographic record
Abstract
Chaotic advection refers to the mixing of fluid elements which arise from repeated stretching and folding of fluid parcels [7,8]. Chaotic advection can be generated by time-dependent Darcy flows and has the potential to enhance mixing under laminar conditions in subsurface reservoirs or other porous media [3,4,10]. Enhanced mixing has many possible applications in environmental science and engineering. Remediation of contaminated aquifers is particularly relevant where mixing between the injected reagent and contaminant is a critical step. To assess whether chaos can be invoked at scale in a natural porous medium, a field trial is being designed in the sandpit area at the University of Waterloo Groundwater Research Facility at CFB Borden located near Alliston, ON, Canada, where we propose to use a transient reoriented dipole flow for subsurface stirring. This paper describes the design criteria associated with this phase of the field trial and presents preliminary modelling results for the determination of key flow system parameters. The Borden aquifer was modelled using Visual MODFLOW® Flex, a 3-D software for groundwater flow and heat/contaminant transport. Assumptions included aquifer homogeneity and isotropic and confined flow. At this initial screening stage, focus was given to horizontal flow fields generated. Simulation results showed that after at least four periodic reorientations of dipoles spaced 1.50 m apart with a pumping rate and duration of 2.50 m3/d and 3 hours, respectively, there is significant crossing of flow paths in the Borden aquifer that indicates high potential for rapid mixing.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 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".