Testing and prediction of mechanical characteristics of sensitive marine clays stabilized by deep mixing method
Why this work is in the frame
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Bibliographic record
Abstract
Sensitive marine clays (SMCs) often pose considerable problems in the construction of embankments for transportation structures. In this study, extensive mechanical, microstructural, and monitoring experiments were carried out to evaluate the evolution of mechanical properties of SMCs stabilized via Deep Mixing Method. The results indicate that unconfined compressive strength and secant modulus increase with curing time. A significant improvement in mechanical properties is observed at early ages. Higher binder contents produce higher mechanical properties after same curing period. However, excess binder content does not provide significant improvement effects. The addition of ground granulated blast furnace slag (GGBFS) results in higher mechanical properties after long-term curing, and the enhancing degree is more evident with a higher proportion of GGBFS. But the situations are reversed at young age due to the “retarding effect” of GGBFS. These observations are also supported by results of physical properties, mercury instruction porosimetry, suction monitoring, and X-ray diffraction analyses. In addition, predictive models are established based on elastic-plastic theory and binder hydration model. The developed models are implemented in COMSOL Multiphysics and validated against experimental results. A good agreement is observed between experimental and predicted results which confirms the ability of developed models to predict the mechanical characteristics.
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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 it