Measurement of Energy and Strength of Sand at Critical State
Bibliographic record
Abstract
Abstract The energy input during shear deformation of sand is expended by three components: resistance against particle-to-particle frictional deformation, volumetric or nonrecoverable plastic deformation, and elastic deformation of the soil grains. These three components are identified for the shearing deformation of sand in triaxial compression using the energy balance principle. A new experimental technique to measure the elastic energy of sands is proposed. Shear resistance against particle-to-particle frictional deformation is then determined after applying corrections to the measured shear strength for plastic volumetric and elastic deformations. The shear resistance against particle-to-particle frictional deformation is shown to be the critical state strength of sand. The technique is illustrated with drained triaxial compression tests on Ottawa Sand. It has been found that the shear resistance against particle-to-particle friction deformation or the critical state strength attains a constant value at small strains. The conventional techniques to determine the critical state strength require it to be strained to large strains. At such large strains, it is not possible to achieve the critical state condition uniformly throughout the sample in a laboratory setup. This has led to many problems with the reliable measurement of the shear strength of sands at the critical state and the establishment of the critical state condition. The ability to measure the critical state strength at small strain levels overcomes such difficulties.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".