Numerical Study of Cone Penetration in Calcareous Sands: Investigating Cone Tip Resistance Correction Factors for Crushable Soils
Bibliographic record
Abstract
The cone penetration test (CPT) is used to characterize the behaviour and properties of soils, including the cyclic strength against earthquake liquefaction triggering. The cone tip resistance relates to cyclic strength through relative density, where relative density is closely related to both cone tip resistance and liquefaction susceptibility. Currently, published methods of estimating liquefaction potential (i.e., cyclic resistance ratio) are based on silica sands and do not properly characterize calcareous sands. The measured cone tip resistance in calcareous sands is lower than in silica sands at the same relative density; this difference is generally attributed to the higher compressibility of calcareous sands due to particle crushing during cone penetration. Consequently, application of CPT-based liquefaction triggering evaluations in calcareous sands result in over-conservative analysis. To avoid over-conservative analysis, projects may develop site-specific correction factors to adjust the cone tip resistance in calcareous sand to the equivalent value in silica sand at the equivalent relative density. This study aims to investigate cone penetration in calcareous sands compared to silica sands by examining the roles of soil compressibility and other fundamental soil parameters. The study is performed with a direct axisymmetric penetration model and the MIT-S1 constitutive model calibrated against published mechanical behaviour for a calcareous sand; the simulated cone penetration results are compared with simulated cone penetration in Ottawa F-65 sand. Compressibility of the calibrations is adjusted to explore the role of compressibility on cone tip resistance. The numerical results show that differences in compressibility only partially account for differences in cone tip resistance between calcareous and silica sands at the same initial state. However, the results support that critical state line position does strongly relate to differences in cone tip resistance between the two soil types. The study results provide a basis to investigate differences in critical state line position as a basis for site-specific cone tip resistance correction factors for calcareous soils.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".