Impact of mixing on groundwater age and life expectancy simulations in density-dependent flow systems
Bibliographic record
Abstract
Abstract Groundwater flow above deep geological repositories in salt domes may lead to the transport of radionuclides into the biosphere. To mitigate this risk, groundwater age is used as an exclusion criterion for repository site selection, and groundwater life expectancy is an established measure for radionuclide travel times. Complexities arise in computing age since groundwater flow above salt domes is highly density-dependent due to the presence of brines. Groundwater flow and solute transport are therefore strongly coupled and are also affected by mixing processes, including diffusion and mechanical dispersion, which are aquifer-specific and highly uncertain. Numerical simulations have been carried out to address this uncertainty for 2D topography-driven and density-dependent groundwater flow above salt domes. Simulation results show that the components of longitudinal and transverse dispersion have a strong influence on the density-dependent flow system and therefore, along with diffusion, significantly affect groundwater age and life expectancy. Underestimation of the associated parameters may lead to overestimation of life expectancy and the critical overestimation of repository safety. Selecting appropriate parameter values and consideration of their uncertainty for mixing processes is therefore critical when modeling life expectancy in the safety assessment of repository sites.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".