Characterization of Glyben for Seismic Applications
Bibliographic record
Abstract
Abstract Glyben is artificial clay that is prepared by mixing sodium bentonite powder and glycerin. It is used for laboratory tests and scale modeling for geotechnical applications. The mechanical properties of glyben depend on the bentonite and glycerin mix proportions. The shear strength, dynamic shear modulus, damping ratio, and Poisson’s ratio were evaluated for glyben samples prepared with different glycerin/bentonite ratios. Vane shear tests, T-bar tests, hammer tests, and resonant column tests were conducted on glyben specimens and the shear strength and dynamic properties were evaluated considering a wide range of strain values and confining pressure. The measured glyben properties were compared with properties of natural cohesive soils to verify the range of applicability of glyben as a test bed material. It was found that glyben has the same range of strength and dynamic properties as soft to medium stiff clay. The trend of variation of the shear modulus and damping ratios of glyben is similar to that of natural clays. It is noted, however, that the damping ratio of glyben is higher than that of natural clays for shear strains below 0.01%. It was concluded that glyben can reasonably model the nonlinear behavior of natural soil under strong dynamic excitation.
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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 | 0.000 |
| 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 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".