Studies of Residual Stress in Single-Row Countersunk Riveted Lap Joints
Bibliographic record
Abstract
Variations of stress and strain from the riveting process through the tensile loading stage in lap joints with a single countersunk rivet were studied experimentally and numerically. The joint specimen consisted of two 2.03 mm thick 2024-T3 Al alloy bare sheets and one 2117-T4 Al alloy countersunk MS20426AD8-9 rivet. A force-controlled riveting method was employed to install the rivets in the joints using three different rivet squeeze forces, 35.59 kN, 44.48 kN, and 53.38 kN. After releasing the squeeze forces, the lap joints were then loaded in tension to a maximum stress of 98.5 MPa. In-situ micro-strain gauges were used to measure the strain variations during the entire loading sequence. Three-dimensional (3D) finite element (FE) models were generated to simulate the experimental set up. The material elasto-plastic constitutive relationship and geometric non-linear properties as well as nonlinear contact boundary conditions were included in the numerical simulations. The numerical modeling techniques were validated using the experimental data. The residual minimum principal stress resulting from the riveting process and maximum principal stress when the joints were in tension determined from the FE analyses are present. The stress variations along a prescribed path are also presented. The aim of the research is to develop an accurate 3D numerical technique to study the residual stress and strain as well as the stress and strain variations that occur during the entire loading history.
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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) | 0.000 | 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".