Measurement of small-strain shear modulus <i>G</i><sub>max</sub> of dry and saturated sands by bender element, resonant column, and torsional shear tests
Bibliographic record
Abstract
The bender element method is an experimental technique used to determine the small-strain shear modulus (Gmax) of a soil by measuring the velocity of shear wave propagation through a sample. Bender elements have been applied as versatile transducers to measure the Gmax of wet and dry soils in various laboratory apparatuses. However, certain aspects of the bender element method have yet to be clearly specified because of uncertainties in determining travel time. In this paper, the bender element (BE), resonant column (RC), and torsional shear (TS) tests were performed on the same specimens using the modified Stokoe-type RC and TS testing equipment. Two clean sands, Toyoura and silica sands, were tested at various densities and mean effective stresses under dry and saturated conditions. Based on the test results, methods of determining travel time in BE tests were evaluated by comparing the results of RC, TS, and BE tests. Also, methods to evaluate Gmax of saturated sands from the shear-wave velocity (Vs) obtained by RC and BE tests were investigated by comparing the three sets of test results. Biot’s theory on frequency dependence of shear-wave velocity was adopted to consider dispersion of a shear wave in saturated conditions. The results of this study suggest that the total mass density, which is commonly used to convert Gmax from the measured Vs in saturated soils, should not be used to convert Vs to Gmax when the frequency of excitation is 10% greater than the characteristic frequency (fc) of the soil.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 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".