Sand-specific interpretation of state via a modified relative dilatancy index
Bibliographic record
Abstract
This paper presents a new, simple strength–dilatancy framework for interpreting the state parameter ( ξ0) in sands using cone penetration test (CPT) data. The approach employs the relative density ( Dr) as a state variable, alongside the mean effective stress ( p′), instead of the traditionally used void ratio ( e). Existing industry-acknowledged CPT– ξ0 correlations are generally found to be challenged by a stress level bias. This paper argues that stress dependency is often better captured in widely used CPT– Dr correlations than in CPT– ξ0 correlations, suggesting that inferring ξ0 through correlations with Dr may improve in situ interpretations. To facilitate this, a modified parameter ( IRx) is introduced, adapted from Bolton’s (1986) relative dilatancy index ( IR) to ensure compatibility with the widely accepted linear approximation of the critical state line (CSL) in e–log10 p′ space. The IRx-based approach is considered applicable for stress levels below approximately 0.5–2.0 MPa, depending on sand type, due to the bilinear nature of the CSL in e–log10 p′ space. Based on recent laboratory studies, this paper also investigates sand-specific dependencies in the parameters of Bolton’s IR, which share similarities with the parameters of IRx. This way, IRx is presented as a parameter useful for stress ranges covering many engineering applications, offering a promising pathway for incorporating sand-specific dependencies into strength–dilatancy relationships and CPT-based state parameter interpretation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".