Validating the Use of Material Point Method and SANISAND Model for Relating the State Parameter with Cone Tip Resistance
Bibliographic record
Abstract
Numerical simulations of cone penetration test (CPT) can provide valuable insights into the mechanical behavior and in situ state of geomaterials. However, adequate simulation of CPT is challenging due to the large deformations occurring during penetration and the need for representative soil constitutive models. This study investigates the use of the material point method (MPM) and a version of the SANISAND family of models as a representative constitutive model to simulate CPTs in dry sand. The numerical model is validated against experimental data on CPT in a calibration chamber. The simulations are done on a range of soil overburden pressures and void ratios. The results illustrate the sufficient adequacy of the numerical configuration in capturing the cone tip resistance for the soil states considered. Additionally, the variation of void ratio versus mean effective stress in selected material points is presented to explore details of material state evolution during the cone penetration.
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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".