Re-visiting the Beam Models for Adhesively Bonded Single-Lap Joints Part II: Comparison of Adhesive Stress Predictions
Bibliographic record
Abstract
In the Part I of this paper, bending-moment predictions for single-lap joints in tension from four theoretical beam models were compared. One of the models evaluated included the corrected form of the original Hart-Smith expression. The authors then, using Hart-Smith's approach, developed a closed-form solution to evaluate the effects of different boundary conditions on the bending moment. For practical applications, the study showed that, except for the Hart-Smith simplified solution, all four models were able to predict similar bending moments at the overlap edge for both long and short overlap joints. In this Part II of the paper, the work in Part I has been extended to compare the estimates of adhesive peel and shear stresses along the overlap region of single-lap joints obtained using the modified Goland-Reissner, Oplinger, and the authors' models. Hart-Smith did not offer expressions for predicting adhesive stresses. However, his analytical approach was combined with the Goland-Reissner's equilibrium analysis of the overlap region to develop an alternative closed-form solution for both the bending moment and adhesive stresses in Part I. When all three models were compared numerically, it was found that the predictions of the adhesive stresses were very similar for applied adherend stresses up to 100 MPa. This was verified for long and short joints with relatively thick adherends. The results led to two main conclusions. Firstly, it is not necessary to consider explicitly the transverse overlap deflection of the joint since that does not significantly affect the maximum peel and shear adhesive stress predictions. Secondly, the different boundary conditions used in the models also do not significantly affect the prediction of maximum adhesive stresses.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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, 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".