Response of cohesive–frictional soils at small to medium shear strain levels from thermo-controlled resonant column testing
Bibliographic record
Abstract
The shear modulus and damping ratio are arguably the two most crucial soil parameters to be used in seismic site-response analyses and a wide variety of other geotechnical engineering applications involving soil materials subjected to dynamic loading. The dependency of these parameters on the level of load-induced shear strains in the field has been investigated rather extensively for different types of soils. Most experimental studies, however, have relied on a limited set of controlled environmental factors and stress variables, mainly soil moisture and confinement. The present work is an attempt to gain further insights into the possible impact of an additional critical factor: soil temperature. A resonant column apparatus was upgraded to assess the dynamic response of three types of cohesive–frictional soils as they transitioned from linear to nonlinear behavior under thermo-controlled cyclic torsional loading. Emphasis was placed on shear modulus degradation, and hence variation in damping ratio, with increasing shear strain amplitude (cyclic torque magnitude). Results showed a mostly detrimental effect of increasing soil temperature on the normalized shear modulus, damping ratio, and threshold shear strain of clayey, silty, and sandy soils when subject to small to medium shear strain levels.
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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 | 0.000 | 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) | 0.002 | 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".