A simple approach for characterizing the performance of metallic tubular adhesively-bonded joints under torsion loading
Bibliographic record
Abstract
Adhesive bonding of joints is one of the most commonly and widely used joining methods in piping systems. This work is concerned with the investigation of the influence of the non-linear behavior of the adhesive used in such bonded joints on their performance. The parametric analysis module of ABAQUS was used to model the joint. The model facilitated the analysis of different geometric, loading and material characteristics of the system, in particular the adhesive nonlinearity, which is of prime interest in this work. By using the Ramberg–Osgood plasticity model, the failure threshold of the adhesive for various joint lengths (hereafter referred to overlap length) was characterized. The plasticity model used in this study was fine-tuned using only a limited number of known parameters, through comparison with the results of the finite element (FE) simulation. The results obtained from the FE analysis were verified by experimental results. The FE strategy is demonstrated to be an effective means for predicting the capacity of such joints, where conducting a pure shear test is either impossible or difficult to accomplish. Contrary to the findings based on the elastic finite element analysis, the plasticity analysis revealed that the overlap length affects the ultimate strength of the joint.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | low |
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".