Significance and evaluation of Poisson's ratio in Rayleigh wave testing
Bibliographic record
Abstract
Important progress has been made in the past 20 years in the use of surface-wave testing in soil characterization. However, the effect of Poisson's ratio on the construction of the theoretical dispersion relationships, associated with the inversion process, has not received enough attention and remains poorly documented. Five ideal profiles with different degrees of variation of shear-wave velocity with depth and three published case records are considered in this paper to study the effect of Poisson's ratio on Rayleigh wave phase velocities. The effect of the variation of Poisson's ratio on the evaluation of shear-wave velocity profiles (V s ) is also examined. Poisson's ratio is generally assumed in surface-wave testing, and therefore the paper also examines the possibility of evaluating its value using a multi-mode inversion process. The results of surface-wave testing obtained at two experimental sites are then used to illustrate the potential of surface-wave testing to evaluate the Poisson's ratio profile in addition to the V s profile. The impact of Poisson's ratio in Rayleigh wave testing is shown to be significantly more important than previously demonstrated. The error resulting from Poisson's ratio does not depend solely on the magnitude of the inaccuracy. A multi-mode inversion process is shown to be a useful tool to determine the Poisson's ratio profile, leading to a more accurate soil characterization.
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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 | 0.001 | 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) | 0.001 | 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 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".