Fully coupled THM behaviour of argillaceous rocks subject to excavation and thermal loading
Bibliographic record
Abstract
This study analyses the coupled thermo-hydro-mechanical (THM) response of argillaceous rocks in high-temperature settings. The changes in the damage zone due to underground excavation and subsequent thermal loading caused by the heat emitted by the high-level waste (HLW) package have been examined. For this purpose, a fully coupled THM formulation has been used that includes a stress update algorithm, implemented in CODE_BRIGHT, to cater for an anisotropic porous medium using Biot’s effective stress. An advanced hyperbolic Mohr–Coulomb elasto-viscoplastic model with damage and nonlocal formulation has been used to simulate the mechanical behaviour of the argillaceous rock. The generalised Darcy’s law and Fourier’s law have been adopted for the description of liquid flow and heat conduction, respectively. Anisotropies of stiffness, strength, permeability, and thermal conductivity have been considered. It has also been assumed that permeability depends on the accumulated viscoplastic strains. Fully coupled THM analyses have been conducted to investigate the evolution of temperature, pore water pressure, and damaged zones. The thermally-induced pore pressure rise is identified as a key mechanism in the development and evolution of the damaged zone. The analyses reported provide a better understanding of the THM response of HLW disposal schemes in argillaceous rocks under high temperatures.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 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".