Measuring unsaturated soil deformations during triaxial testing using a photogrammetry-based method
Bibliographic record
Abstract
When characterizing an unsaturated soil using the triaxial test apparatus, it is required to measure the soil deformation during loading. Recently, a photogrammetry-based method has been developed for total and localized volume change measurements on unsaturated soils during triaxial testing. In this study, more in-depth discussions on the photogrammetry-based method are addressed, such as system setup, the measurement procedure, accuracy self-check, data post-processing, and differences from conventional image-based methods. Also, an application of the photogrammetry-based method on unsaturated soil deformation measurements is presented through a series of undrained triaxial tests with different loading paths. After testing, three-dimensional (3D) models of the tested soils at different loading steps were constructed based on the 3D coordinates of measurement targets on the soil surface. Clear barreling processes for soils during deviatoric loading were observed through the constructed 3D models at different axial strain levels. Soil volume changes and volumetric strain nonuniformities during isotropic and deviatoric loadings were extracted based upon detailed analyses of different soil layers. Through a full-field strain distribution analysis, a shear band evolution process was captured for the soil during deviatoric loading at a low confining stress. The photogrammetry-based method proved to be very powerful for in-depth soil deformation characteristics investigation.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".