Evolutive phase field modelling of fracture behavior of cemented paste backfill under Mode-I loading condition
Bibliographic record
Abstract
An evolutive phase field model (PFM) that incorporates cement hydration process is developed to predict Mode-I fracture behavior in cemented paste backfill (CPB). The model seamlessly integrates hydration-dependent stiffness and toughness evolution into a standard finite element framework, regularizing sharp cracks through a diffusive phase field variable. In all three case studies, the PFM reproduces key experimental observations-narrow crack bands and stable propagation in single-edge notched bending (SENB) test, mode-I dominated crack paths and post-peak softening in semi-circular bending (SCB) test, and wide, diffuse fracture zones in splitting tensile tests. The coupled hydration damage formulation captures the time- and temperature-sensitive strengthening of CPB, successfully matching the delayed crack initiation and gradual load-bearing increases seen across varied curing ages and temperatures. The robustness of a single parameter set across multiple test configurations underscores the model potential for generalized CPB fracture prediction without geometry-specific calibration. By accurately forecasting crack patterns and load-displacement responses, this evolutive PFM offers a powerful tool for optimizing CPB mix design, service-life prediction, and curing protocol development in deep-mine applications.
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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".