Reactive Transport Simulation of Low-pH Cement Interacting with Opalinus Clay Using a Dual Porosity Electrostatic Model
Bibliographic record
Abstract
Strong chemical gradients between clay and concrete porewater lead to diffusive transport across the interface and subsequent mineral reactions in both materials. These reactions may influence clay properties such as swelling behaviour, permeability or radionuclide retention, which are relevant for the safety of a radioactive waste repository. Different cement types lead to different interactions with Opalinus Clay (OPA), which must be understood to choose the most suitable material. The consideration of anion-depleted porosity due to electrostatic repulsion in clay modelling substantially influences overall diffusive transport and pore clogging at interfaces. The identical dual porosity model approach previously used to predict interaction between Portland cement and OPA is now applied to low-alkali cement—OPA interaction. The predictions are compared with corresponding samples from the cement-clay interaction (CI) experiment in the Mont Terri underground rock laboratory (Switzerland). Predicted decalcification of the cement at the interface (depletion of C–S–H and absence of ettringite within 1 mm from the interface), the Mg enrichment in clay and cement close to the interface (neoformation of up to 17 vol% Mg hydroxides in concrete, and up to 6 vol% in OPA within 0.6 mm at the interface), and the slightly increased S content in the cement 3–4 mm away from the interface qualitatively match the sample characterisation. Simulations of Portland cement—OPA interaction indicate a weaker chemical disturbance over a larger distance compared with low-pH cement—OPA. In the latter case, local changes in porosity are stronger and lead to predicted pore clogging.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".