Numerical simulation of solute transport in argillaceous rock under thermal gradient with a coupled THM-solute transport model
Bibliographic record
Abstract
Argillaceous rocks have many favourable characteristics for deep geological disposal of high-level radioactive waste (HLW) such as low permeability resulting in slow solute transport dominated by diffusion processes . However, waste-generated heat can increase pore pressure through Thermal-Hydraulic-Mechanical (THM) coupled processes, potentially enhancing advective transport . In this study, the authors developed a mathematical model to simulate a laboratory and a large-scale in situ experiment at an underground research facility (URF), to investigate (1) T-solute transport coupling (via the Soret effect and temperature-dependent diffusion coefficient) and (2) THM-solute transport coupling in argillaceous rock. The findings suggest that the Soret effect is significant in the laboratory experiments with relatively high thermal gradient , but negligible in the URF experiment where the thermal gradient is much smaller. Instead, the effect of temperature on the diffusion coefficient appears to play a more crucial role for the URF experiment. In addition, the advection enhancement due to thermal pressurization as a result of THM processes shows an insignificant effect on solute transport . The modelling of the URF experiment, as confirmed by observational evidence, shows the importance of anisotropy of the THM-transport properties as well as the effects of the excavation damage zone (EDZ). Finally, the model captures the key features of both experiments, highlighting its capability in enhancing comprehension of transport processes from a deep geological repository (DGR) built in argillaceous rocks. This improved understanding is valuable for safety assessments of DGRs in such rock types.
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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 | 0.000 | 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) | 0.000 | 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".