Impact of evolving fabric anisotropy on CPT simulations for subsurface characterization
Bibliographic record
Abstract
In geotechnical site characterization, Cone Penetration Testing (CPT) is a fundamental method for evaluating subsurface conditions of granular materials such as sands, silts, and non-plastic tailings. This study advances CPT simulations by incorporating the fabric anisotropy variable A into the SANISAND-F model and utilizing the Material Point Method (MPM), with a specific focus on the role of evolving fabric within an anisotropic critical state framework. The objective is to deepen the understanding of how the evolving fabric of soils influences macroscopic site characterization outcomes. Through carefully controlled initial conditions, including void ratio and confining pressure, the study aims to demonstrate the impact of fabric anisotropy on CPT resistance measurements. Assessment of the evolution of material state based on the key constitutive ingredient of the model allows for explaining the reason behind the respective values of cone tip resistance observed from the CPT simulations, considering fabric anisotropy and the anisotropic critical state framework. This approach enhances the modeling of this site characterization method, providing a more comprehensive framework for interpreting soil mechanical behavior and enhancing predictive modeling capabilities
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".