A Large-Scale Triaxial Apparatus for Prototype Railroad Ballast Testing
Bibliographic record
Abstract
Abstract Shear strength and compressibility of large grain-size materials are critical parameters for the geotechnical design of road bases, rock fill embankments, and railroad sub-base. However, due to the correspondingly large scale of triaxial specimens necessary for rock-fill and railroad ballast material testing, the numbers of facilities that are capable of testing these materials are few. In this paper, a cost effective design is documented for a triaxial apparatus capable of testing prototype railroad ballast material containing particle sizes up to 63.5 mm (2.5 in.). Unique to this testing apparatus is the use of vacuum as confinement to allow an unobstructed digital image measurement of specimen volume change during testing. The specimen preparation methodology, manufacture of latex membrane, and instrumentation are also discussed. Finally, the results of a cyclical triaxial test are presented to demonstrate the quality of the testing data from this triaxial apparatus.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".