Parametric study of fully grouted cable bolts subjected to axial loading
Bibliographic record
Abstract
The laboratory short encapsulation pull-out test (LSEPT) has been widely accepted as the most efficient method to characterize the mechanical behaviour of cable bolts under axial loading. In this study, a number of LSEPTs was performed on conventional (Plain SuperStrand) and modified (MW9S) cable bolts using the improved pull-out test design. The effects of several parameters including the uniaxial compressive strength (UCS) of the confining medium and grout and the borehole diameter on the mechanical behaviour of MW9S and Plain SuperStrand cable bolts were investigated. Response surface methodology (RSM) was employed to quantify the contribution of these parameters on the responses including peak and residual loads and initial stiffness. RSM revealed that the UCS of the confining medium is a key contributing factor to the mechanical behaviour of both cable bolts. Also, it was demonstrated that the borehole diameter had a negligible impact on the overall behaviour of the MW9S cable bolt while the peak load of the SuperStrand cable bolt was increased due to an increase in the diameter of the borehole. Finally, from a comparative analysis, it was confirmed that the improved design can better represent the field mechanical behaviour of cable bolts through maintenance of the embedment length during large deformation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".