Effect of preload and shim types on the mechanical properties of composite-aluminium bolted joints
Bibliographic record
Abstract
The influence of both preload and the presence of shim types on the mechanical properties of composite-aluminium single-bolt, single-lap joints were studied in this paper. The load-displacement curve and surface strain field of joints in different shim types and preloads were obtained through tensile experiments. A progressive damage model was established using the UMAT subroutine in ABAQUS. A hybrid failure criterion and a linear continuous degradation model were used to describe the progressive damage of composite laminates. The results show that for joints with no shim and for those with various types of shims, the tensile stiffness, peak load and initial damage load could be reduced when the preload is insufficient or too large. Compared with joints with no shims or with peelable fibreglass shims, joints with liquid shims required a larger preload to achieve the best mechanical properties. As the proportion of peelable fibreglass shim increased, the tensile stiffness and peak load continued to increase in joints with a mixed shim of liquid and peelable fiberglass shim. Shims can serve as tension bearings, but have little effect on the initiation and development of bearing failure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".